ML Ops Engineer Jobs

ML Ops Engineer Fully REMOTE - working mostly East Coast/Central hours Compensation up to $180,000 depending on location, experience and skills We're seeking an experienced ML Ops Engineer to build and scale the infrastructure, automation, and operational processes that support production machine learning and AI systems. This role will partner closely with Data Science, Data Engineering, and Product teams to ensure models are deployed, monitored, governed, and continuously improved in a secure, regulated environment. Experience in healthcare and/or HIPAA compliance highly desired! Responsibilities: - Build and maintain end-to-end ML pipelines for model training, validation, deployment, and monitoring. - Manage model lifecycle processes including versioning, promotion, deployment, and retirement. - Design scalable infrastructure for real-time and batch model serving using APIs, containers, and cloud-native technologies. - Develop feature store, data versioning, and training-serving consistency solutions. - Support generative AI and LLM applications, including RAG architectures, prompt management, API integrations, guardrails, and usage monitoring. - Implement monitoring for model drift, performance degradation, latency, and pipeline health. - Establish CI/CD and continuous training workflows for machine learning systems. - Automate infrastructure provisioning, security controls, secrets management, and compliance processes. - Partner with technical teams to improve reliability, scalability, governance, and operational excellence across AI platforms. - Provide technical leadership and mentor team members on MLOps best practices. Qualifications: - Master's degree in Computer Science, Software Engineering, or a related technical discipline. - 7+ years of experience in DevOps, Data Engineering, ML Engineering, or related disciplines. - 4+ years supporting production machine learning systems and model operations. - Experience in healthcare, HIPAA, health technology, or other regulated environments preferred. - Strong understanding of model deployment, observability, governance, and platform engineering. - Docker, Kubernetes, EKS - Terraform and/or AWS CloudFormation - MLflow - Databricks (Delta Lake, Spark, Unity Catalog, Workflows, Vector Search) - AWS: SageMaker, Bedrock, S3, Lambda, API Gateway, DynamoDB, Redshift, Athena, Glue, Step Functions, Kinesis, Secrets Manager - Kafka and/or Kinesis streaming architectures - Feature stores and data versioning frameworks - LLM operations, RAG infrastructure, prompt versioning, and AI governance - Python, Bash, SQL - Experience with REST APIs, event-driven architectures, and distributed systems - Go or Java experience is a plus - Strong communicator who can collaborate across Data Science, Engineering, and Product teams. - Detail-oriented with a focus on reliability, scalability, security, and compliance. - Passionate about modern AI infrastructure, MLOps best practices, and continuous improvement. - Experienced in building production-grade machine learning platforms that support advanced analytics, NLP, and generative AI applications. Benefits Medical/Dental/Vision 401K with 40% match up to first 6% of associated contributions PTO, Holidays, Personal Days, Community Service Day

ML Ops Engineer

Eli Lilly

US: South San Francisco

At Lilly, the work is demanding because patients are waiting. We unite caring with discovery to help make life better for people around the world, knowing that every decision, every detail, and every day matters. Headquartered in Indianapolis, Indiana, our over 50,000 employees around the globe take on complex challenges to discover and deliver life-changing medicines, strengthen how health is understood and managed, and support the communities we serve. This is hard, urgent, selfless work—but it’s work worth doing. If you’re driven by purpose and ready to bring your best to work that truly matters for patients, we invite you to join us. Where AI Meets Medicine: Build the Future of Drug Discovery in the Heart of Silicon Valley! Making medicine that’s never been made means doing what’s never been done. If you’re an engineer, scientist, or builder who thrives on problems no one has solved before, this is your invitation; we want you on the team. We are ready to challenge the status quo and push medicine forward, all in the name of health. Are you up for the challenge? If so, join us! About the Lilly and NVIDIA Partnership Lilly and NVIDIA are launching a new AI co-innovation lab in the heart of Silicon Valley — an up-to-$1 billion, multi-year commitment to solve drug discovery’s toughest challenges. The lab brings Lilly scientists, technologists, chemists and biologists together with NVIDIA engineers under one roof. Together, we are building purpose-built foundation and frontier AI models trained on Lilly data at scale, tightening the feedback loop between automated wet labs and computational dry labs, designing the next generation of medicines for millions of patients across the globe. What You’ll Be Doing As an ML Ops Engineer, you build and operate the platforms that run the end-to-end machine learning lifecycle. You enable reliable model deployment, operation, monitoring, retraining, and reproducibility at scale. You optimize infrastructure and GPU resources to support research and discovery workloads. You will work closely with engineering and scientific teams to deliver production-ready AI capabilities. How You’ll Succeed Lead the operational lifecycle of ML models, including deployment, monitoring, and ongoing reliability. Operate and optimize large-scale inference platforms that support scientific discovery and AI workloads. Ensure models can be deployed, scaled, monitored, and maintained in production environments. Test, refine, and improve model accuracy. Work with data scientists, business analysts and partners to integrate ML models into broader strategies. Automate the platform with infrastructure-as-code and CI/CD, and document it well enough that someone else can operate it. What You Should Bring Strong Python skills and experience working with machine learning frameworks such as PyTorch, JAX, or TensorFlow. Experience deploying, operating, and scaling production machine learning platforms, including model serving, monitoring, and large-scale inference workloads. Experience with MLOps platforms and tools like MLflow, Weights & Biases, KServe, or similar technologies. Proficiency with containerization, orchestration, and distributed compute environments (Docker, Kubernetes, Slurm, Ray). Experience operating large-scale AI platforms that deploy, host, and optimize machine learning models for production use, using technologies such as Triton, vLLM, or TensorRT-LLM. Experience with infrastructure automation and CI/CD practices using tools such as Terraform, Ansible, GitHub Actions, or related. Experience supporting cloud platforms (AWS, Azure, or GCP) and on-premises GPU infrastructure. Knowledge of observability and operational monitoring, including metrics, logging, tracing, and performance tuning. Ability to identify and address system, infrastructure, and model performance issues through automation and continuous improvement. Ability to collaborate effectively with research scientists, AI engineers, and infrastructure teams in a fast-paced environment. Your Basic Qualifications Bachelor’s in Computer Science, Engineering, Statistics, Mathematics, or a related technical field 4+ years of experience in machine learning engineering, ML Ops, or platform engineering. Location & Work Flexibility This role is based at our Silicon Valley Hub. We offer a flexible hybrid work model, with three days onsite and two days working remotely each week , supporting both collaboration and work‑life balance. Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form ( https://careers.lilly.com/us/en/workplace-accommodation ) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response. Lilly is proud to be an EEO Employer and does not discriminate on the basis of age, race, color, religion, gender identity, sex, gender expression, sexual orientation, genetic information, ancestry, national origin, protected veteran status, disability, or any other legally protected status. Our employee resource groups (ERGs) offer strong support networks for their members and are open to all employees. Our current groups include: Africa, Middle East, Central Asia (AMECA), Black Employees at Lilly (BE@Lilly), Chinese Culture Network (CCN), EnAble, Evolve, Lilly Indian Network (LIN), Organization of Latinx at Lilly (OLA), Pride (LGBTQ+ Allies), Veterans Leadership Network (VLN) and Women’s Initiative for Leading at Lilly (WILL). Actual compensation will depend on a candidate’s education, experience, skills, and geographic location. The anticipated wage for this position is $147,000 - $268,400 Full-time equivalent employees also will be eligible for a company bonus (depending, in part, on company and individual performance). In addition, Lilly offers a comprehensive benefit program to eligible employees, including eligibility to participate in a company-sponsored 401(k); pension; vacation benefits; eligibility for medical, dental, vision and prescription drug benefits; flexible benefits (e.g., healthcare and/or dependent day care flexible spending accounts); life insurance and death benefits; certain time off and leave of absence benefits; and well-being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities).Lilly reserves the right to amend, modify, or terminate its compensation and benefit programs in its sole discretion and Lilly’s compensation practices and guidelines will apply regarding the details of any promotion or transfer of Lilly employees. #WeAreLilly Global pharmaceutical company leading in diabetes, obesity, oncology, and neuroscience treatments. Headquartered in Indianapolis, IN. lilly.com

ML Ops Engineer

Icf

United States

Please note: This role is contingent upon a contract award. While it is not an immediate opening, we are actively conducting interviews and extending offers in anticipation of the award. The Work At ICF our Digital Modernization Division is an information technology and management consulting organization that delivers integrated, strategic solutions to federal clients. We bring expertise in cloud, cybersecurity, enterprise architecture, data modernization, and digital transformation to support mission-critical government programs. Join a team accelerating the modernization of a large federal agency's enterprise data and analytics ecosystem. This cloud-based platform provides data storage, analytics, governance, and AI/ML capabilities that enable thousands of users to transform data into actionable insights. As demand continues to grow, the team is focused on migrating legacy workloads, streamlining onboarding and support, expanding platform capabilities, and helping organizations across the enterprise adopt modern data and AI solutions at scale. The ML Ops Engineer will develop and maintain machine learning pipelines, model registries, deployment frameworks, monitoring solutions, and automated workflows that support enterprise AI initiatives. Working closely with data scientists, data engineers, cloud architects, platform engineers, and Trustworthy AI stakeholders, this role enables the successful operationalization of machine learning capabilities across cloud-based environments. Job Location: Remote, however, strong preference for candidates who live in the Washington DC Metro Area. There will be occasional onsite meetings on the client site in Washington, DC. *If you accept this position, you should note that ICF does monitor employee work locations, blocks access from foreign locations/foreign IP addresses, and prohibits personal VPN connections. What You'll Do Design, build, and maintain production-grade MLOps pipelines for model training, evaluation, validation, registration, deployment, monitoring, retraining, rollback, and retirement. Develop reusable MLOps and LLMOps patterns using Azure Databricks, Databricks ML, MLflow, Unity Catalog, Azure Machine Learning, Python, and approved Azure AI services. Implement experiment tracking, model versioning, model registries, lineage, quality metrics, model cards, and approval workflows using MLflow and Unity Catalog to ensure models are discoverable, reusable, and auditable. Build automated CI/CD pipelines using GitHub Actions, Azure DevOps, Databricks Asset Bundles, and Terraform to promote models, code, configurations, and supporting infrastructure consistently across development, test, and production environments. Deploy and maintain scalable model-serving infrastructure for batch, streaming, real-time, and API-based inference workloads using Databricks Model Serving, Azure Machine Learning, Databricks compute, serverless capabilities, and GPU-enabled configurations, as applicable. Establish automated testing and evaluation gates for model performance, data quality, fairness, safety, explainability, robustness, privacy, and release readiness. Implement model and feature monitoring, drift and bias detection, logging, tracing, alerting, and operational dashboards using MLflow Model Monitoring, Lakehouse Monitoring, and the broader platform monitoring stack. Develop automated retraining, champion/challenger promotion, rollback, and model-retirement workflows that prevent performance degradation and support reliable production operations. Integrate ML workflows with source control, infrastructure provisioning, secrets management, identity and access controls, environment management, and enterprise release processes. Implement Trustworthy AI controls, including model documentation, impact assessments, audit logging, content safeguards, human oversight, and evaluation evidence aligned with Government-approved standards and the NIST AI Risk Management Framework. Partner with data scientists, AI engineers, data engineers, platform engineers, DevSecOps, Security, and Governance personnel to make models repeatable, testable, deployable, and operationally supportable. Monitor compute and serving utilization, tune cluster and endpoint configurations, apply tagging conventions, and implement cost-optimization strategies for training and inference workloads. Troubleshoot failed pipelines, deployment issues, model-serving incidents, performance degradation, and monitoring alerts while supporting root-cause analysis and corrective actions. Create and maintain deployment templates, reusable repositories, operational runbooks, model documentation, release evidence, and technical standards that accelerate responsible AI/ML adoption across the enterprise. Basic Qualifications U.S. Citizenship is required due to federal contract requirements. Candidate must reside in the U.S., be authorized to work in the U.S., and all work must be performed in the U.S. Candidate must have lived in the U.S. for three (3) full years out of the last five (5) years. Bachelor's degree in Computer Science, Software Engineering, Machine Learning, Data Science, Engineering, or a related field or a high school diploma with four (4) additional years of relevant experience in lieu of a bachelor's degree. 6+ years of experience designing and supporting production machine learning solutions in cloud environments. Master's degree may substitute for two (2) years of relevant experience. Preferred Qualifications Experience with machine learning operations (MLOps), automated deployment pipelines, and model lifecycle management. Proficiency in Python and modern software development practices. Experience with source control systems and CI/CD frameworks. Hands-on experience with Azure Machine Learning, Databricks, MLflow, or comparable ML platforms. Experience implementing model monitoring, automated retraining, and performance tracking solutions. Knowledge of cloud-native architecture, containerization, and scalable model serving patterns. Experience supporting Responsible AI, AI governance, or Trustworthy AI initiatives. Familiarity with infrastructure-as-code and automated environment provisioning. Strong understanding of cloud cost optimization practices for AI/ML workloads. #Indeed Bot and Third-Party Applications Please note that this application must be submitted directly by the applicant for consideration. Failure to do so may result in the application being excluded for consideration. Applicants needing an accommodation for disability or religious purposes in connection with the application process should contact for assistance. Working at ICF ICF is a global advisory and technology services provider, but we’re not your typical consultants. We combine unmatched expertise with cutting-edge technology to help clients solve their most complex challenges, navigate change, and shape the future. We can only solve the world's toughest challenges by building a workplace that allows everyone to thrive. We are an equal opportunity employer.Together, our employees are empowered to share theirexpertiseand collaborate with others to achieve personal and professional goals. For more information, please read our EEOpolicy. We will consider for employment qualified applicants with arrest and conviction records. Reasonable Accommodations are available, including, but not limited to, for disabled veterans, individuals with disabilities, and individuals withsincerely heldreligious beliefs, in all phases of the application and employment process. To requestan accommodation,please email and we will be happy toassist. All information you provide will be kept confidential and will be used only to the extentrequiredto provide needed reasonable accommodations. Read more about workplace discrimination rightsor our benefit offerings which are included in the Transparency in (Benefits) CoverageAct. Candidate AI Usage Policy At ICF, we are committed to ensuring a fair interview process for all candidates based on their own skills and knowledge. As part of this commitment, the use of artificial intelligence (AI) tools to generate orassistwith responses during interviews (whether in-person or virtual) is notpermitted. This policy is in place tomaintainthe integrity and authenticity of the interview process. However, we understand that some candidates may require accommodation that involves the use of AI. Ifsuch anaccommodation is needed, candidates are instructed to contact us in advance at . Weare dedicated to providingthe necessary support to ensure that all candidates have an equal opportunity to succeed. Pay Range - There are multiple factors that are considered in determining final pay for a position, including, but not limited to, relevant work experience, skills, certifications and competencies that align to the specified role, geographic location, education and certifications as well as contract provisions regarding labor categories that are specific to the position. The pay range for this position based on full-time employment is: $98,614.00 - $167,644.00Nationwide Remote Office (US99) Originally posted on Himalayas

Senior ML Ops Engineer

Elsevier

United States

Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About the team, this team that powers Elsevier’s Health platforms: Clinical Key AI, Sherpath AI, and AI-driven automated clinical and content workflows. You will bridge Data Science and Engineering to turn experimental NLP/IR/GenAI models into secure, reliable, and scalable services. Our systems operate over one of the world’s largest medical and scholarly landscapes. About the role, as a Senior Machine Learning Engineer you’ll work on AI-based features (GenAI, Agentic AI, RAG, etc.) search/ranking quality, and knowledge graph aware retrieval while enforcing content rights and editorial confidentiality. Key Responsibilities ML & LLM Engineering, Search and Recommendation Engines Automate and orchestrate machine learning workflows across major cloud and AI platforms (AWS, Azure, Databricks, and foundation model APIs such as OpenAI). Maintain and version model registries and artifact stores to ensure reproducibility and governance. Develop and manage CI/CD for ML, including automated data validation, model testing, and deployment. Implement ML Engineering solutions using popular MLOps platforms such as AWS SageMaker, MLflow, Azure ML. Scale end-end custom Sagemaker pipelines. Design and implement the engineering components of GAR+RAG systems (e.g., query interpretation and reflection, chunking, embeddings, hybrid retrieval, semantic search), manage prompt libraries, guardrails and structured output for LLMs hosted on Bedrock/SageMaker or self-hosted. Design and implement ML pipelines that utilize Elasticsearch/OpenSearch/Solr, vector DBs, and graph DBs . Build evaluation pipelines: offline IR metrics (NDCG, MAP, MRR), LLM quality metrics (faithfulness, grounding), and A/B testing. Optimize infrastructure costs through monitoring, scaling strategies, and efficient resource utilization. Stay current with the latest GAI research, NLP and RAG and apply the state-of-the-art in our experiments and systems. Collaboration Partner with Subject-Matter Experts, Product Managers, Data Scientists and Responsible AI experts to translate business problems into cutting edge data science solutions Collaborate and interface with Operations Engineers who deploy and run production infrastructure. Qualifications Current experience in ML Engineering, MLOps platforms, shipping ML or search/GenAI systems to production. Strong Python, Java, and/or Scala experience will be considered a plus. Hands-on‑ experience with major cloud vendor solutions (AWS, Azure and/or Google) Experience with Search/vector/graph technologies (e.g., Elasticsearch / OpenSearch / Solr / Neo4j). Experience in evaluating LLM models. A strong understanding of the Data Science Life Cycle including feature engineering, model training, and evaluation metrics. Background in health technology and/or medical content workflows is preferred. Familiarity with ML frameworks, e.g., PyTorch, TensorFlow, PySpark. Experience with large-scale data processing systems, e.g., Spark. Experience with statistical analysis, machine learning theory and natural language processing. Elsevier is a renowned global information analytics company that primarily focuses on providing scientific, technical, and medical (STM) research content, tools, and services. It is one of the largest publishers of academic journals and scholarly literature in the world. Elsevier operates in various domains, including science, technology, medicine, social sciences, and more. They publish a vast number of peer-reviewed journals covering a wide range of disciplines. These journals act as platforms for researchers and academics to share their findings and contribute to the advancement of knowledge in their respective fields. U.S. National Base Pay Range: $95,300 - $158,800. Geographic differentials may apply in some locations to better reflect local market rates.If performed in Maryland, the base pay range is $100,100 - $166,800.If performed in New Jersey, the base pay range is $112,574 - $179,826.This job is eligible for an annual incentive bonus. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-855-833-5120. Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here. Please read our Candidate Privacy Policy. We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. USA Job Seekers: EEO Know Your Rights. Originally posted on Himalayas

Senior ML Ops Engineer

Confido

New York, NY

Own and build Confido's ML platform: design and operate end-to-end ML pipelines, infrastructure-as-code and CI/CD, optimize training/inference and agent workloads for latency/cost/throughput, integrate model data flows with data engineering, and ensure reliability, observability, security, and production model quality with online evals and human-in-the-loop review. Top Skills: Airflow, Aurora/Rds, AWS, Bedrock, Bentoml, Github Actions, Gpu, Java, Kafka, Kubernetes, Mlflow, Onnx, Python, Ray, Redis, Ruby On Rails, Sagemaker, Snowflake, Tensorrt, Terraform, Vector Databases, Vertex Ai, Vllm Industry: Artificial Intelligence , Fintech , Financial Services

Abbott is a global healthcare leader that helps people live more fully at all stages of life. Our portfolio of life-changing technologies spans the spectrum of healthcare, with leading businesses and products in diagnostics, medical devices, nutritionals and branded generic medicines. Our 122,000 colleagues serve people in more than 160 countries. Our medical devices help more than 10,000 people have healthier hearts, improve quality of life for thousands of people living with chronic pain and movement disorders, and liberate more than 500,000 people with diabetes from routine fingersticks. **Working at Abbott** At Abbott, you can do work that matters, grow, and learn, care for yourself and family, be your true self and live a full life. You’ll also have access to: + Career development with an international company where you can grow the career you dream of. + Employees can qualify for free medical coverage in our Health Investment Plan (HIP) PPO medical plan in the next calendar year + An excellent retirement savings plan with high employer contribution + Tuition reimbursement, the Freedom 2 Save (https://www.abbott.com/corpnewsroom/strategy-and-strength/tackling-student-debt-for-our-employees.html) student debt program and FreeU (https://www.abbott.com/corpnewsroom/strategy-and-strength/college-degree-for-free-its-possible-with-freeu.html) education benefit - an affordable and convenient path to getting a bachelor’s degree. + A company recognized as a great place to work in dozens of countries around the world and named one of the most admired companies in the world by Fortune. + A company that is recognized as one of the best big companies to work for as well as a best place to work for diversity, working mothers, female executives, and scientists. **THE OPPORTUNITY** This **Senior Staff ML Ops Engineer** position can work out of our **Santa Clara, CA location.** Senior Staff ML Ops Engineer will provide technical leadership for Abbott's Medical Devices Digital (MDD) AI initiatives, driving the architecture, scalability, and operational excellence of enterprise AI platforms. This role bridges advanced AI innovation with production-grade engineering, defining technical strategy, establishing best practices for MLOps and AI governance, and leading the design and evolution of robust, scalable AI infrastructure. The Senior Staff ML Ops Engineer will partner closely with data scientists, algorithm developers, infrastructure teams, product leaders, and cross-functional stakeholders to accelerate the deployment of AI solutions, ensure reliability and compliance, and influence the long-term AI technology roadmap across the organization. **What You’ll Work On** + Architect a highly available, secure, scalable cloud/on-prem hybrid ML infrastructure that includes data ingestion, annotation, feature engineering, training, validation, deployment, and monitoring. + Engage directly with ML scientists and act as the team’s bridge/glue between science and engineering. + Implement robust CI/CD workflows for ML models, including testing, rollout, rollback strategies, and compliance governance. + Ensure strict compliance with regulatory and privacy standards such as HIPAA, GDPR, and Software as a Medical Device (SaMD) guidelines. + Drive alignment and adoption of architecture strategy with business leaders. + Mentor and guide ML engineers and SW engineers, establish coding standards, and conduct detailed design and architectural reviews. **Qualifications** + Bachelors Degree in Computer Science, Engineering Mathematics, or related field. + **Minimum 8+** years of experience, Master’s Degree with 6+ years of related experience, or Ph.D. with 4+ years of related experience. + Deep experience building ML infrastructure for experiment tracking, model training, data versioning, annotation tools, model serving, monitoring and observability. + Experience with GenAI and Agentic AI development infrastructure including grounding, RAG, MCP and prompt engineering. ​ + Experience developing AI products on cloud computing platforms (e.g., AWS, Azure, Google Cloud), containerization technologies (e.g., Docker, Kubernetes), pipeline orchestration tools (e.g. Airflow), IaC (e,g., Terraform). + Proficient in tools like Azure ML SDK, Azure Data Factory, Databricks, Spark, or related technologies. + Strong understanding of database technologies (e.g., SQL, NoSQL) and data modeling principles. + Significant experience working with agile software development methods, such as scrum and Kanban and working within CI/CD pipelines. + Experience incorporating Security by Design principles into AI product development. + Experience of senior executive/leadership engagement. + Exposure to various aspects of architecture practices and frameworks: business, application, data, security, infrastructure and governance. + Experience with microservices architecture and distributed systems. + Experience in reviewing and selecting Technical and Applications Architectures solutions. + Certifications and specializations in AI/ML, LLMs and Cloud platforms. + Excellent oral, written and presentation communication skills. + Team leadership experience and demonstrated mentorship capabilities. **Preferred** + Experience working in an FDA-regulated business (e.g. validated software related to medical, pharmaceutical, or life sciences products). + Experience with FDA 510(k) submissions and clinical-grade ML product development. + Solid understanding of the design thinking process, as well as a passion and know-how for influencing design strategy. + Publications, patents, or notable contributions to open-source projects. + Background in signal processing, computer vision, or multimodal learning. + Familiarity with data security best practices, data anonymization, synthetic data generation, and federated learning. Apply Now (https://www.jobs.abbott/us/en) **Learn more about our health and wellness benefits, which provide the security to help you and your family live full lives:** www.abbottbenefits.com (http://www.abbottbenefits.com/pages/candidate.aspx) Follow your career aspirations to Abbott for diverse opportunities with a company that can help you build your future and live your best life. Abbott is an Equal Opportunity Employer, committed to employee diversity. Connect with us at www.abbott.com , on Facebook at www.facebook.com/Abbott and on Twitter @AbbottNews and @AbbottGlobal \#software The base pay for this position is $130,700.00 – $261,300.00. In specific locations, the pay range may vary from the range posted. An Equal Opportunity Employer Abbot welcomes and encourages diversity in our workforce. We provide reasonable accommodation to qualified individuals with disabilities. To request accommodation, please call 224-667-4913 or email corpjat@abbott.com

Abbott is a global healthcare leader that helps people live more fully at all stages of life. Our portfolio of life-changing technologies spans the spectrum of healthcare, with leading businesses and products in diagnostics, medical devices, nutritionals and branded generic medicines. Our 122,000 colleagues serve people in more than 160 countries. Our medical devices help more than 10,000 people have healthier hearts, improve quality of life for thousands of people living with chronic pain and movement disorders, and liberate more than 500,000 people with diabetes from routine fingersticks. Working at Abbott At Abbott, you can do work that matters, grow, and learn, care for yourself and family, be your true self and live a full life. You’ll also have access to: Career development with an international company where you can grow the career you dream of. Employees can qualify for free medical coverage in our Health Investment Plan (HIP) PPO medical plan in the next calendar year An excellent retirement savings plan with high employer contribution Tuition reimbursement, the Freedom 2 Save student debt program and FreeU education benefit - an affordable and convenient path to getting a bachelor’s degree. A company recognized as a great place to work in dozens of countries around the world and named one of the most admired companies in the world by Fortune. A company that is recognized as one of the best big companies to work for as well as a best place to work for diversity, working mothers, female executives, and scientists. THE OPPORTUNITY This Senior Staff ML Ops Engineer position can work out of our Santa Clara, CA location. Senior Staff ML Ops Engineer will provide technical leadership for Abbott's Medical Devices Digital (MDD) AI initiatives, driving the architecture, scalability, and operational excellence of enterprise AI platforms. This role bridges advanced AI innovation with production-grade engineering, defining technical strategy, establishing best practices for MLOps and AI governance, and leading the design and evolution of robust, scalable AI infrastructure. The Senior Staff ML Ops Engineer will partner closely with data scientists, algorithm developers, infrastructure teams, product leaders, and cross-functional stakeholders to accelerate the deployment of AI solutions, ensure reliability and compliance, and influence the long-term AI technology roadmap across the organization. What You’ll Work On Architect a highly available, secure, scalable cloud/on-prem hybrid ML infrastructure that includes data ingestion, annotation, feature engineering, training, validation, deployment, and monitoring. Engage directly with ML scientists and act as the team’s bridge/glue between science and engineering. Implement robust CI/CD workflows for ML models, including testing, rollout, rollback strategies, and compliance governance. Ensure strict compliance with regulatory and privacy standards such as HIPAA, GDPR, and Software as a Medical Device (SaMD) guidelines. Drive alignment and adoption of architecture strategy with business leaders. Mentor and guide ML engineers and SW engineers, establish coding standards, and conduct detailed design and architectural reviews. Qualifications Bachelors Degree in Computer Science, Engineering Mathematics, or related field. Minimum 8+ years of experience, Master’s Degree with 6+ years of related experience, or Ph.D. with 4+ years of related experience. Deep experience building ML infrastructure for experiment tracking, model training, data versioning, annotation tools, model serving, monitoring and observability. Experience with GenAI and Agentic AI development infrastructure including grounding, RAG, MCP and prompt engineering. ​ Experience developing AI products on cloud computing platforms (e.g., AWS, Azure, Google Cloud), containerization technologies (e.g., Docker, Kubernetes), pipeline orchestration tools (e.g. Airflow), IaC (e,g., Terraform). Proficient in tools like Azure ML SDK, Azure Data Factory, Databricks, Spark, or related technologies. Strong understanding of database technologies (e.g., SQL, NoSQL) and data modeling principles. Significant experience working with agile software development methods, such as scrum and Kanban and working within CI/CD pipelines. Experience incorporating Security by Design principles into AI product development. Experience of senior executive/leadership engagement. Exposure to various aspects of architecture practices and frameworks: business, application, data, security, infrastructure and governance. Experience with microservices architecture and distributed systems. Experience in reviewing and selecting Technical and Applications Architectures solutions. Certifications and specializations in AI/ML, LLMs and Cloud platforms. Excellent oral, written and presentation communication skills. Team leadership experience and demonstrated mentorship capabilities. Preferred Experience working in an FDA-regulated business (e.g. validated software related to medical, pharmaceutical, or life sciences products). Experience with FDA 510(k) submissions and clinical-grade ML product development. Solid understanding of the design thinking process, as well as a passion and know-how for influencing design strategy. Publications, patents, or notable contributions to open-source projects. Background in signal processing, computer vision, or multimodal learning. Familiarity with data security best practices, data anonymization, synthetic data generation, and federated learning. Apply Now Learn more about our health and wellness benefits, which provide the security to help you and your family live full lives: www.abbottbenefits.com Follow your career aspirations to Abbott for diverse opportunities with a company that can help you build your future and live your best life. Abbott is an Equal Opportunity Employer, committed to employee diversity. Connect with us at www.abbott.com , on Facebook at www.facebook.com/Abbott and on Twitter @AbbottNews and @AbbottGlobal #software The base pay for this position is $130,700.00 – $261,300.00. In specific locations, the pay range may vary from the range posted.

Architect and operate end-to-end ML pipelines for training and deployment on GCP and AWS. Maintain system monitoring, alerting, and CI/CD automation for ML artifacts and infrastructure.

Azure AI/ML Ops Engineer

Everest Technologies

Remote

•             Total of 3-6 years of experience in managing machine learning projects end-to-end, with the last 18 months focused on MLOps •             Strong programming skills, preferably in languages like Python, Java, or Scala •             Proficiency in machine learning libraries and frameworks, such as TensorFlow, PyTorch, or scikit-learn •             Experience with containerization technologies, like Docker and Kubernetes •             Familiarity with ML model deployment tools, such as MLflow or Kubeflow •             Automation of machine learning model deployment.

Greetings Everyone Who are we? For the past 20 years, we have powered many Digital Experiences for the Fortune 500. Since 1999, we have grown from a few people to more than 4000 team members across the globe that are engaged in various Digital Modernization. For a brief 1 minute video about us, you can check https://youtu.be/uJWBWQZEA6o . Must Have - Tech Skills: 1. Hands on with designing end to end scalable ML system (should have worked on recent projects within last 12 months). 2. Hands on with implementation of scalable ML system. Proven ownership across entire or partial ML and MLOps lifecycle: a. Evaluation Techniques. b. Machine Learning Algorithms. c. Statistical Modeling. d. End to end deployment. e. Metric generation. f. Model monitoring and deployment. g. Prompt Engineering, 3. Hand on with ML Model optimization - quantization, pruning, or speculative decoding etc. 4. Hand on with ML Model system optimizations ie ability to quickly identify bottlenecks and resolve them from System perspective. 5. Programming & Frameworks: Hands on and have worked on recent projects (within last 12months) in: a. Java i. library/dependency management ii. Package and distribution management iii. Algorithms b. Python c. Tensorflow / PyTorch 6. Knowledge of DevOps principles and tools (e.g., CI/CD pipelines, Terraform). 7. Strong understanding of containerization technologies (e.g., Docker, Kubernetes). Must Have - Soft Skills: 1. Good Team worker & good collaborations skills. 2. Ability to abstract out details, define problem & have clear technical communication. 3. Ability to lead inter team communication. 4. Ability to write crisp and effective documentation. 5. Ensures that deadlines are met. Good To Have - Tech Skills: 1. GCP ML Tech stack. 2. Experienced with Infrastructure as Code (IaC). 3. Experience with big data technologies such as Apache Spark or Hadoop. 4. Stay informed about the ethical implications of machine learning eg: selection bias. 5. Model Training 6. Data Analytics - figure out anomalies , skew , discrepancies 7. Hands on with developing on device ML System. Good To Have - Soft Skills: 1. Mentoring and Leadership. 2. Project Management. Compensation, Benefits and Duration Minimum Compensation: USD 51,000 Maximum Compensation: USD 178,000 Compensation is based on actual experience and qualifications of the candidate. The above is a reasonable and a good faith estimate for the role. Medical, vision, and dental benefits, 401k retirement plan, variable pay/incentives, paid time off, and paid holidays are available for full-time employees. This position is available for independent contractors No applications will be considered if received more than 120 days after the date of this post

Payer Dev, Git & ML-Ops Engineer, Senior Associate

PricewaterhouseCoopers LLP

Boston, MA

Industry/Sector Health Services Specialism Operations Management Level Senior Associate Job Description & Summary The Opportunity As a Payer Dev, Git & ML-Ops Engineer, Senior Associate, you will engage with clients in the Health Services sector to drive modernization initiatives within our Operations Consulting practice. You will leverage your skills to analyze complex problems and develop innovative solutions that enhance operational efficiency. As a Senior Associate, you will build meaningful client connections and guide junior team members, fostering a collaborative environment. You will navigate complex situations, using your critical thinking to anticipate client needs and deliver quality outcomes. In this role, you will be part of our Payer Modernization team, focusing on developing and implementing cutting-edge solutions that align with client objectives. You will have the opportunity to deepen your technical skills and grow your personal brand within the firm. By embracing ambiguity and utilizing a broad range of methodologies, you will contribute to the delivery of impactful client solutions. This position offers a dynamic environment where you can expand your professional skills and make a significant impact on client engagements. Responsibilities - Analyzing complex operational challenges to develop innovative solutions for client engagements - Managing and optimizing operations processes to enhance business performance and efficiency - Utilizing analytical thinking and business data analytics to drive data-informed decision-making - Engaging with stakeholders to understand and address their operational needs and objectives - Implementing quality standards and operational excellence practices to improve service delivery models - Supporting business transformation initiatives through effective change management strategies - Conducting market research to inform operations strategy and planning - Collaborating with teams to foster creativity and embrace change in operational processes - Developing and maintaining operational support frameworks to streamline service delivery - Applying management consulting techniques to guide clients through payer modernization efforts What You Must Have - At least a Bachelor's degree - At least 4 years of experience What Sets You Apart - Preference for at least one of the following fields of study: Accounting, Actuarial Science, Analytics/Data Science, Business Administration/Management, Computer Science/Information Systems, Economics, Engineering, Finance, Government/Public Policy, Health Administration/Public Health, Mathematics/Statistics, Operations/Supply Chain, Organizational Management/Behavior, Risk Management/Insurance - Demonstrating proficiency in Business Data Analytics and Operations Strategy - Utilizing analytical thinking to drive business transformation initiatives - Excelling in stakeholder engagement and communication within health services - Embracing change and fostering creativity in operational processes - Implementing quality standards in service delivery models - Navigating complexity in payer modernization projects Travel Requirements Up to 80% Job Posting End Date The salary range for this position is: $77,000 - $202,000. Actual compensation within the range will be dependent upon the individual's skills, experience, qualifications and location, and applicable employment laws. All hired individuals are eligible for an annual discretionary bonus. PwC offers a wide range of benefits, including medical, dental, vision, 401k, holiday pay, vacation, personal and family sick leave, and more. To view our benefits at a glance, please visit the following link: ;br> As PwC is an equal opportunity employer, all qualified applicants will receive consideration for employment at PwC without regard to race; color; religion; national origin; sex (including pregnancy, sexual orientation, and gender identity); age; disability; genetic information (including family medical history); veteran, marital, or citizenship status; or, any other status protected by law. PwC does not intend to hire experienced or entry level job seekers who will need, now or in the future, PwC sponsorship through the H-1B lottery, except as set forth within the following policy: ;br> Learn more about how we work: ;br> For only those qualified applicants that are impacted by the Los Angeles County Fair Chance Ordinance for Employers, the Los Angeles' Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, San Diego County Fair Chance Ordinance, and the California Fair Chance Act, where applicable, arrest or conviction records will be considered for Employment in accordance with these laws. At PwC, we recognize that conviction records may have a direct, adverse, and negative relationship to responsibilities such as accessing sensitive company or customer information, handling proprietary assets, or collaborating closely with team members. We evaluate these factors thoughtfully to establish a secure and trusted workplace for all. Applications will be accepted until the position is filled or the posting is removed, unless otherwise set forth on the following webpage. Please visit this link for information about anticipated application deadlines:

Lead Databricks ML & AI Ops Engineer

KData Inc.

United States

This is a remote position. We are seeking a Lead Databricks ML & AI Ops Engineer to architect, scale, and govern the machine learning and AI platforms that power our enterprise data products. In this role, you will define the technical vision and engineering strategy for our end-to-end MLOps lifecycle—spanning from exploratory data science to global-scale production deployment on Databricks, Delta Lake, and Unity Catalog. As a Lead Engineer, you will serve as the primary architect and technical authority for our ML platform. You will lead and mentor a talented team of senior engineers , collaborate closely with data science executives, and align with product teams to deliver robust, high-performance AI features. This role requires a balance of advanced distributed computing expertise, cutting-edge Generative AI platform design, and a strong DevOps/GitOps mindset. Key Responsibilities Technical Leadership & Strategy Platform Vision: Define the architectural roadmap for the enterprise ML platform, steering the migration away from legacy systems (e.g., Apache Airflow) to modern Databricks Workflows and Asset Bundles. Standards & Governance: Establish, document, and enforce global engineering standards for code quality, CI/CD pipelines, and automated testing. Lead enterprise-wide ML governance and data security strategies utilizing Unity Catalog. Team Mentorship: Lead, mentor, and coach senior and mid-level engineers. Conduct advanced design and code reviews to foster a culture of technical excellence. Vendor & Community Engagement: Act as the primary technical point of contact for Databricks account teams. Represent the company at external conferences and contribute to tech blogs. ML & LLM Platform Architecture Enterprise Pipelines: Architect reusable, highly efficient batch and streaming feature pipelines using Delta Live Tables, Spark Structured Streaming, and Databricks Feature Store. Compute Optimization: Standardize cluster configurations (including multi-node GPU training) to optimize complex AutoML and deep learning workloads (PyTorch, Hugging Face) for cost and performance. Generative AI Infrastructure: Design secure, production-grade frameworks for Large Language Model (LLM) operations (LLMOps), including robust RAG pipelines, agentic workflows, and Vector Search indexing using Mosaic AI and LangChain. Model Lifecycle Management: Oversee the global setup of MLflow, defining enterprise staging gates, automated retraining loops, and instant rollback strategies. Infrastructure & Operations (Ops) Production Serving: Architect high-availability, low-latency model serving frameworks utilizing Databricks Model Serving, Mosaic AI Gateway, and containerized deployments via Kubernetes/FastAPI. Infrastructure-as-Code: Lead the standardization of Infrastructure-as-Code (IaC) using Terraform or Pulumi to automate environment provisioning across multiple cloud regions. Observability & SLAs: Establish advanced, proactive monitoring for data drift, model performance decay, hallucination rates, and pipeline SLAs using Databricks Lakehouse Monitoring, Prometheus, and Grafana. Requirements Required Qualifications Experience: 8+ years of software, data, or DevOps engineering experience, with at least 5 years dedicated specifically to production-grade ML/AI systems. Proven experience in a technical lead or architectural capacity. Databricks Mastery: Deep, expert-level knowledge of the Databricks ecosystem, including Workflows, Delta Live Tables, Unity Catalog, Mosaic AI, and Databricks Asset Bundles. Distributed Systems: Advanced understanding of Spark internals (DAG optimization, shuffle tuning, memory management) at an enterprise, multi-terabyte scale. Core Engineering: Exceptional Python skills (writing highly optimized, type-annotated, and modular code) alongside deep familiarity with frameworks like PyTorch, scikit-learn, and XGBoost. DevOps & GitOps: Strong background in enterprise GitOps workflows (e.g., trunk-based development), Docker containerization, Kubernetes orchestration, and complex GitHub Actions CI/CD pipelines. Cloud Architecture: Extensive hands-on experience provisioning and securing cloud infrastructure on AWS, Azure, or GCP. Preferred Qualifications Certification: Databricks Certified Machine Learning Professional and/or Databricks Certified Enterprise Architect. Advanced AI/Governance: Direct experience implementing Responsible AI frameworks, model cards, bias auditing, and cost-tracking guardrails for LLMs. Open Source: Active contributor to open-source ML, MLOps, or data engineering projects (e.g., MLflow, Delta Lake, LangChain). Data Mesh: Experience designing Lakehouse architectures within a decentralized Data Mesh organizational framework. Technical Environment Platform & Storage: Databricks (AWS/Azure/GCP), Delta Lake, Unity Catalog, S3/ADLS Gen2. Orchestration & CI/CD: Databricks Workflows, Databricks Asset Bundles, GitHub Actions, Terraform. ML & LLM Frameworks: MLflow, PyTorch, Hugging Face, Mosaic AI, LangChain, Databricks Vector Search, GPT-4 / Claude APIs. Serving & Observability: Databricks Model Serving, FastAPI, Docker, Kubernetes, Databricks Lakehouse Monitoring, Prometheus, Grafana. Originally posted on Himalayas

No Description

Senior Software Engineer - ML Ops Truveta is the world’s first health provider led data platform with a vision of Saving Lives with Data. Our mission is to enable researchers to find cures faster, empower every clinician to be an expert, and help families make the most informed decisions about their care. Achieving Truveta’ s ambitious vision requires an incredible team of talented and inspired people with a special combination of health, software and big data experience who share our company values . This position is based out of our headquarters in the Greater Seattle area. #LI-hybrid Who We Need Truveta is rapidly building a talented and diverse team to tackle complex health and technical challenges. We are seeking candidates inspired by the opportunity to apply data in the development of real-world health solutions. Beyond core capabilities, we are seeking problem solvers, passionate and collaborative teammates, and those willing to roll up their sleeves while making a difference. If you are interested in the opportunity to pursue purposeful work, join a mission-driven team, and build a rewarding career while having fun, Truveta may be the perfect fit for you. This Opportunity If you are seeking a sense of purpose in your software job and are motivated by solving computing problems that can have a direct impact on people’s lives, then we have opportunities for you in an exciting startup environment. We are looking for a Senior Engineer to participate in note processor. This role requires deep technical expertise in cloud-native infrastructure, distributed systems, as well as strong product thinking. You will partner closely with Compute Platform, security, ML engineering, and applied AI teams to understand business needs, define platform requirements, and build self-service capabilities that help teams move quickly and safely. Success in this role will directly influence how Truveta delivers data at using AI development and tools. Responsibilities Leverage software engineering skills to build and deliver reliable, secure and scalable software solutions using modern cloud-based paradigms across different components in Truveta. Collaborate closely with partner teams inside & outside of Truveta. Show creativity and curiosity to build integration proof of concepts across the Truveta and partner ecosystems. Bring your curiosity, entrepreneurial spirit, and passion to deliver on the promise of technology in the difficult, competitive, and exciting industry of healthcare. We are seeking software engineers who: Have proven experience designing and building reliable, secure, and scalable software solutions using modern cloud-based architectures and engineering practices. Have hands-on experience with machine learning infrastructure , including scaling GPU resources to optimize model throughput, performance, and efficiency at scale. Are familiar with vLLM and GPU optimization techniques , with an understanding of how to maximize compute utilization and improve inference performance. Have experience working with large language models (LLMs), generative AI, and related applications . Have experience deploying and operating large-scale machine learning models in production environments . Ideally, have prior experience building or working with agentic AI platforms and systems . Are quick learners who can iterate on and evolve distributed software systems while thoughtfully balancing privacy, security, reliability, and rapidly changing product requirements . Have strong knowledge of distributed systems, data pipelines, APIs, and data consumption experiences , with experience designing and building these systems at scale. Demonstrate a strong commitment to the Truveta principles and to advancing responsible and ethical innovation. Are committed to ongoing learning and training in critical areas such as privacy, ethics, and security . Key Qualifications: 5+ years of experience building production quality software in a team setting. 2+ years of experience working on modern cloud-native platforms and languages (AWS, GCP, Azure) Some familiarity with crafting modular APIs and building engaging and intuitive web experiences. B.S. or M.S. in Computer Science or related field. Why Truveta? Be a part of building something special. Now is the perfect time to join Truveta. We have strong, established leadership with decades of success. We are well-funded. We are building a culture that prioritizes people and their passions across personal, professional, and everything in between. Join us as we build an amazing company together. We Offer: Interesting and meaningful work for every career stage Great benefits package Comprehensive benefits with strong medical, dental and vision insurance plans 401K plan Professional development & training opportunities for continuous learning Work/life autonomy via flexible work hours and flexible paid time off Generous parental leave Regular team activities (virtual and in-person) The base pay for this position is $155,000 to $190,000. The pay range reflects the minimum and maximum target. Pay is based on several factors including location and may vary depending on job-related knowledge, skills, and experience. Certain roles are eligible for additional compensation such as incentive pay and stock options. If you are based in California, we encourage you to read this important information for California residents linked here. Truveta is committed to creating a diverse, inclusive, and empowering workplace. We believe that having employees, interns, and contractors with diverse backgrounds enables Truveta to better meet our mission and serve patients and health communities around the world. We recognize that opportunities in technology historically excluded and continue to disproportionately exclude Black and Indigenous people, people of color, people from working class backgrounds, people with disabilities, and LGBTQIA+ people. We strongly encourage individuals with these identities to apply even if you don’t meet all of the requirements. Please note that all applicants must be authorized to work in the United States for any employer as we are unable to sponsor work visas or permits (e.g. F-1 OPT, H1-B) at this time. We appreciate your interest in the position and encourage you to explore future opportunities with us.

Lead Machine Learning Engineer - Merchandising AI (ML Ops)

Target Corporation

Brooklyn Park, MN

The pay range is $132,000.00 - $238,000.00 Pay is based on several factors which vary based on position. These include labor markets and in some instances may include education, work experience and certifications. In addition to your pay, Target cares about and invests in you as a team member, so that you can take care of yourself and your family. Target offers eligible team members and their dependents comprehensive health benefits and programs, which may include medical, vision, dental, life insurance and more, to help you and your family take care of your whole selves. Other benefits for eligible team members include 401(k), employee discount, short term disability, long term disability, paid sick leave, paid national holidays, and paid vacation. Find competitive benefits from financial and education to well-being and beyond at ;br> JOIN US AS A LEAD MACHINE LEARNING ENGINEER - MERCHANDISING AI About Us: Working at Target means helping all families discover the joy of everyday life. We bring that vision to life through our values and culture. Learn more about Target here. A role with Target Data Sciences means the chance to help develop and manage state of the art predictive algorithms that use data at scale to automate and optimize decisions at scale. Whether you join our Applied Data Sciences or Machine Learning teams, you'll be challenged to harness Target's impressive data breadth to build the algorithms that power solutions our partners in Digital Marketing, Supply Chain Optimization, Advanced AI, Search and Personalization rely on. Every Scientist on Target's Data Sciences team can expect modeling and data science, software/product development of highly performant code for model performance at scale. As the Lead Machine Learning Engineer - Merchandising, you will join a Data Sciences team responsible for creating and optimizing the data and models used to build a world-class merchandising product. You will play a crucial role in designing, implementing, and optimizing production machine learning solutions. We will also expect you to understand best practice software design, participate in code reviews, and create a maintainable well-tested codebase with relevant documentation. At an organizational level, you may conduct training sessions, present work to technical and non-technical peers/leaders, build knowledge on business priorities/strategic goals and leverage this knowledge while building requirements and solutions for each business need. Core responsibilities of this job are articulated within this job description. Job duties may change at any time due to business needs. About you: 4-year degree in Quantitative disciplines (Science, Technology, Engineering, Mathematics) or equivalent experience MS in Computer Science, Applied Mathematics, Statistics, Physics or equivalent work or industry experience in applied machine learning 5 plus years of experience in end-to-end machine learning application development, including data pipelining, model optimization, deployment and API design Extensive experience with applied machine learning frameworks and the ability to developing highly distributed machine learning systems at scale Highly proficient in Python programming Strong understanding of CI/CD practices for machine learning systems and ML Ops principles Extensive experience with Google Cloud's Vertex AI and/or the broader cloud-based ML ecosystem Demonstrated knowledge of various testing frameworks and containerization like Docker and Kubernetes Lead the development of agentic AI solutions that connect data, tools, APIs and business rules into end-to-end decisioning workflows Demonstrated experience in REST API design and development Extensive understanding of Big Data technologies including Hadoop, Spark and Kafka Proven ability to collaborate with data scientists, software engineers and product managers to deliver scalable machine learning solutions Excellent communication skills with an ability to tell data-driven stories through visualizations and narratives Ability to mentor engineers and help establish engineering standards, architecture patterns, and best practices for AI/ML and cloud-native development. Self-driven, results-oriented and able to meet tight deadlines Motivated team player who thrives in a collaborative global environment This position may be considered for a Remote or Hybrid (known internally at Target as "Flex for Your Day") work arrangement based on Target's needs. A Remote work arrangement means the team member works full-time from home or an alternate location that's not a Target location, does not have a desk at a Target location and may travel to HQ up to 4 times a year. A Hybrid/Flex for Your Day work arrangement means the team member's core role may be performed either remote or onsite at a Target location depending upon what your role, team and tasks require for that day. Work duties cannot be performed outside of the country of the primary work location, unless otherwise prescribed by Target. Benefits Eligibility Please paste this url into your preferred browser to learn about benefits eligibility for this role: _E Americans with Disabilities Act (ADA) In compliance with state and federal laws, Target will make reasonable accommodations for applicants with disabilities. If a reasonable accommodation is needed to participate in the job application or interview process, please reach out to Non-accommodation-related requests, such as application follow-ups or technical issues, will not be addressed through this channel. Application deadline is : 10/29/2026

Your work days are brighter here. We’re obsessed with making hard work pay off, for our people, our customers, and the world around us. As a Fortune 500 company and a leading AI platform for managing people, money, and agents, we’re shaping the future of work so teams can reach their potential and focus on what matters most. The minute you join, you’ll feel it. Not just in the products we build, but in how we show up for each other. Our culture is rooted in integrity, empathy, and shared enthusiasm. We’re in this together, tackling big challenges with bold ideas and genuine care. We look for curious minds and courageous collaborators who bring sun-drenched optimism and drive. Whether you're building smarter solutions, supporting customers, or creating a space where everyone belongs, you’ll do meaningful work with Workmates who’ve got your back. In return, we’ll give you the trust to take risks, the tools to grow, the skills to develop and the support of a company invested in you for the long haul. So, if you want to inspire a brighter work day for everyone, including yourself, you’ve found a match in Workday, and we hope to be a match for you too. About the Team Your work matters here. At Workday Government, we focus on outcomes that serve a larger mission. Our work supports U.S. federal agencies as they modernize and transform the full employee lifecycle experience and finance operations—so they can operate with greater clarity, accountability, and trust. As a Fortune 500 company and a proven enterprise cloud platform, Workday brings modern technology, responsible AI, and secure infrastructure to some of the most complex environments in the world. The work isn’t theoretical. It’s operational. It’s high-impact. And it demands rigor, integrity, and long-term thinking. From day one, you’ll be part of a team that values collaboration, follow-through, and doing the right thing—especially when the stakes are high. Our culture is grounded in integrity, respect, and shared responsibility. We challenge each other to think clearly, act thoughtfully, and build solutions that stand up to real-world demands. Here, curiosity is matched with accountability. Ambition is paired with trust. You’ll have the space to do your best work, the support to keep growing, and the backing of a company committed to long-term investment in both its people and the federal mission. If you’re looking to apply your experience to meaningful, mission-driven work—alongside colleagues who take pride in building things that last—you’ll find that opportunity at Workday Government. About the Role This role will support one or more direct or indirect contracts with the U.S. Federal Government which, due to federal government security requirements, mandates that all Workday personnel working on the contracts be United States citizens (naturalized or native). The Workday ML Runtime team is seeking an energetic and determined Software Engineer to design, implement, and deliver highly scalable features for our Machine Learning Runtime platform. As a member of this fast paced group you will have a unique and rewarding opportunity to shape and contribute towards microservices that power Workday Machine Learning features in production. You will partner with Data Scientists, ML Engineers, and other Software Engineers to create the technology that brings these features to life. Key Responsibilities : Developing frameworks, automation, and tooling to foster a culture of efficiency and innovation. Apply technologies like Kubernetes, Docker, and Python to enhance developer scalability in creating innovative ML Runtime Inference applications. Implementation and operation of distributed systems and software development including the conception, specifying, designing, programming, documenting, testing, and bug fixing involved in creating and maintaining applications, frameworks, or other software components. Developing products and services that empower developers to streamline their interactions with the ML platform. Working with public clouds (such as IAAS, AWS, GCP) and applying capacity management principles. Deploying and orchestrating containers in production environments, including technologies like Containers, Kubernetes, Service Mesh, ArgoCD and related tools. Actively engage with Tech Leads and ML Engineers across teams to elaborate on requirements and drive technical solutions. Own and develop features from end to end including infrastructure as code. Research, evaluate, prototype and drive adoption of new ML tools with reliability and scale in mind Strong dedication to proactively addressing and resolving issues, automating processes, and empowering engineers to self-service their operational needs for improved productivity. Availability for on-call support on a rotational basis. This role will support one or more direct or indirect contracts with the U.S. Federal Government which, due to federal government security requirements, mandates that all Workday personnel working on the contracts be United States citizens (naturalized or native). About You This role may require a security clearance at the TS/SCI w/CI Poly level. Applicants must have the ability to obtain and maintain a U.S. government issued security clearance. An active TS/SCI w/CI Poly is preferred. We need creative and dedicated Software Engineers, like you, who really want to move the needle. You should enjoy working on projects that can significantly improve developer satisfaction and save the company millions of dollars. By nature, you are inquisitive and ready to question the status quo. You have a passion for exploring and implementing innovative techniques and approaches to solve complex and challenging problems. Most importantly of all you are a superlative collaborator and teammate and bring out the very best in everyone. You feel happiest when working with a highly capable and motivated team of people passionate about software and technology. Basic qualifications: US Citizenship is required. 3 or more years of DevOps experience including Infrastructure automation, building CICD pipelines. Good in System design and writing comprehensive technical design docs Proficient in Python programming. Design, implement, and maintain robust DevOps pipelines for deploying, monitoring, and scaling machine learning runtime environment. Experience using technologies like Kubernetes/Docker to help developers scale their efforts in creating new and innovative products. Collaborate with other Machine Learning teams to improve not just the product, but efficiencies in engineering processes. Other Qualifications: Machine learning background. Experience with communication protocols, RESTful services, service-oriented architecture, distributed systems, and microservices. Building comprehensive monitoring services. Prior experience with enterprise SaaS products. Experience with monitoring tools like Grafana. Passion for creating and maintaining documentation and fixing run books. Availability for on-call support on a rotating basis. Proficiency in infrastructure automation tools like Terraform, implementing CI/CD pipelines using Git and Jenkins, and applying continuous deployment tool such as ArgoCD BS/MS in Computer Science or a related technical field. Excellent problem-solving skills with a focus on creating and maintaining accurate documentation. Experience in leading or mentoring other team members and proven team collaboration experience, i.e. understanding group dynamics, effective communication strategies, conflict resolution techniques, and the ability to foster a positive and inclusive team. Workday Pay Transparency Statement The annualized base salary ranges for the primary location and any additional locations are listed below. Workday pay ranges vary based on work location. As a part of the total compensation package, this role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus, as well as annual refresh stock grants. Recruiters can share more detail during the hiring process. Each candidate’s compensation offer will be based on multiple factors including, but not limited to, geography, experience, skills, job duties, and business need, among other things. For more information regarding Workday’s comprehensive benefits, please click here . Primary Location: USA.VA.Reston Primary Location Base Pay Range: $137,000 USD - $205,400 USD Additional US Location(s) Base Pay Range: $123,900 USD - $222,000 USD Our Approach to Flexible Work With Flex Work, we’re combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so rather than a number of required days in-office each week, we simply spend at least half (50%) of our time each quarter in the office or in the field with our customers, prospects, and partners (depending on role). This means you'll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together. Those in our remote "home office" roles also have the opportunity to come together in our offices for important moments that matter. Pursuant to applicable Fair Chance law, Workday will consider for employment qualified applicants with arrest and conviction records. Workday is an Equal Opportunity Employer including individuals with disabilities and protected veterans. Workday is committed to providing reasonable accommodations for qualified individuals during our application process, in order to perform one or more essential functions of their job, as well as regarding the use of AI tools for employment decision-making to any degree. Please see below for more details including how to request an accommodation as a qualified veteran, due to a disability or for religious reasons, or as otherwise provided under applicable law. Workday prohibits taking adverse action against any candidate or employee for reporting a possible violation of this policy, requesting one or more work accommodations, exercising a privacy right, or cooperating in an investigation in accordance with applicable law. Any employee who retaliates against a candidate or employee for doing so may be subject to disciplinary action, up to and including termination of employment, to the fullest extent allowable under applicable law. If you require a reasonable accommodation, you may email accommodations@workday.com , as far in advance as possible. Are you being referred to one of our roles? If so, ask your connection at Workday about our Employee Referral process! At Workday, we value our candidates’ privacy and data security. Workday will never ask candidates to apply to jobs through websites that are not Workday Careers. Please be aware of sites that may ask for you to input your data in connection with a job posting that appears to be from Workday but is not. In addition, Workday will never ask candidates to pay a recruiting fee, or pay for consulting or coaching services, in order to apply for a job at Workday.

Senior ML Engineer - Search & LLM Ops

RavenPack

United States

About us At RavenPack, we are at the forefront of developing the next generation of generative AI tools for the finance industry and beyond. With 20 years of experience as a leading big data analytics provider for financial services, we empower our clients—including some of the world's most successful hedge funds, banks, and asset managers—to enhance returns, reduce risk, and increase efficiency by integrating public information into their models and workflows. Building on this expertise, we are launching a new suite of GenAI and SaaS services, designed specifically for financial professionals. Join a Company that is Powering the Future of Finance with AI RavenPack has been recognized as the Best Alternative Data Provider by WatersTechnology and has been included in this year’s Top 100 Next Unicorns by Viva Technology. RavenPack has launched Bigdata, our Gen-AI platform tailored for finance, which is already being recognized as the #1 platform for powering financial AI agents. European legal working status is required. Join RavenPack RavenPack is looking for an experienced Senior Machine Learning Engineer to join our Search & Recommendation team. Your mission will be to architect and build the next generation of our search and recommendation intelligence. You will take ownership of the full machine learning lifecycle, from ideation and data exploration to model deployment. By creating sophisticated, scalable, and personalized content delivery systems, you will directly shape how top financial professionals worldwide discover and interact with the critical information that drives their decisions. This is a unique opportunity to solve complex challenges at the intersection of information retrieval, NLP and finance. The ability to communicate effectively in English both in writing and verbally is a must. European legal working status is required. What You'll Be Doing As a key member of the team, you will have the autonomy to innovate and the responsibility to deliver robust, high-impact solutions. Own Model Development: Lead the end-to-end design, development, and deployment of advanced ranking algorithms and retrieval models to deliver highly relevant search results and content. Innovate in Semantic Search: Fine-tune and distill Language Models to enhance their domain-specific expertise. You'll implement cutting-edge semantic embedding techniques (e.g., binary, matryoshka, late interaction models) to optimize for speed and accuracy. Build & Scale Recommender Systems: Architect and implement sophisticated recommender systems that personalize the user experience, driving engagement and content discovery. Collaborate & Mentor: Work closely with product managers, software engineers, and data scientists to translate business needs into technical solutions. Stay Ahead of the Curve: Actively research and evaluate emerging trends and academic research in ML, NLP, and Information Retrieval, prototyping new ideas to maintain our competitive edge. What We're Looking For We are seeking a seasoned expert with a passion for building intelligent systems and solving complex problems. • A Master’s or PhD in Computer Science, Machine Learning, Data Science, or a related quantitative field. • 3+ years of hands-on professional experience in building and deploying machine learning models in a production environment, with a significant focus on Information Retrieval, Search, or Recommender Systems. • Strong programming skills in Python and familiarity with SQL or other query languages. • Deep knowledge of ML frameworks like PyTorch or TensorFlow, and libraries like Scikit-learn and Hugging Face. • Hands-on experience with vector databases. • Analytical Mindset: Exceptional quantitative and problem-solving skills, with a proven ability to apply rigorous statistical and mathematical reasoning to complex, real-world challenges. • Excellent verbal and written communication skills in English. You are a clear and precise communicator who excels in a collaborative, agile team environment. Bonus Points: • Experience in the financial domain. • Experience with MLOps tools and cloud platforms. What's in it for You? Growth Opportunity: Join a rapidly growing company with 180+ team members with offices in New York, Madrid, and Marbella, building AI that truly matters for business and finance. Competitive Salary: In RavenPack, we believe that your time and experience needs to be fairly rewarded. Continuous learning:We provide the support needed to grow within the team. Innovation: Innovation is the key to our success, so we encourage you to speak up and tell us about your vision. Diversity is in our DNA! You will work in an international environment (over 29 nationalities and 24 languages spoken!) We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. Originally posted on Himalayas

Your work days are brighter here. We’re obsessed with making hard work pay off, for our people, our customers, and the world around us. As a Fortune 500 company and a leading AI platform for managing people, money, and agents, we’re shaping the future of work so teams can reach their potential and focus on what matters most. The minute you join, you’ll feel it. Not just in the products we build, but in how we show up for each other. Our culture is rooted in integrity, empathy, and shared enthusiasm. We’re in this together, tackling big challenges with bold ideas and genuine care. We look for curious minds and courageous collaborators who bring sun-drenched optimism and drive. Whether you're building smarter solutions, supporting customers, or creating a space where everyone belongs, you’ll do meaningful work with Workmates who’ve got your back. In return, we’ll give you the trust to take risks, the tools to grow, the skills to develop and the support of a company invested in you for the long haul. So, if you want to inspire a brighter work day for everyone, including yourself, you’ve found a match in Workday, and we hope to be a match for you too. About the Team Your work matters here. At Workday Government, we focus on outcomes that serve a larger mission. Our work supports U.S. federal agencies as they modernize and transform the full employee lifecycle experience and finance operations—so they can operate with greater clarity, accountability, and trust. As a Fortune 500 company and a proven enterprise cloud platform, Workday brings modern technology, responsible AI, and secure infrastructure to some of the most complex environments in the world. The work isn’t theoretical. It’s operational. It’s high-impact. And it demands rigor, integrity, and long-term thinking. From day one, you’ll be part of a team that values collaboration, follow-through, and doing the right thing—especially when the stakes are high. Our culture is grounded in integrity, respect, and shared responsibility. We challenge each other to think clearly, act thoughtfully, and build solutions that stand up to real-world demands. Here, curiosity is matched with accountability. Ambition is paired with trust. You’ll have the space to do your best work, the support to keep growing, and the backing of a company committed to long-term investment in both its people and the federal mission. If you’re looking to apply your experience to meaningful, mission-driven work—alongside colleagues who take pride in building things that last—you’ll find that opportunity at Workday Government. About the Role Employees may be required to be on site at client locations in the DC, MD, and VA (DMV) area The Workday ML Runtime team is seeking an energetic and determined Software Engineer to design, implement, and deliver highly scalable features for our Machine Learning Runtime platform. As a member of this fast paced group you will have a unique and rewarding opportunity to shape and contribute towards microservices that power Workday Machine Learning features in production. You will partner with Data Scientists, ML Engineers, and other Software Engineers to create the technology that brings these features to life. Key Responsibilities: Developing frameworks, automation, and tooling to foster a culture of efficiency and innovation. Apply technologies like Kubernetes, Docker, and Python to enhance developer scalability in creating innovative ML Runtime Inference applications. Implementation and operation of distributed systems and software development including the conception, specifying, designing, programming, documenting, testing, and bug fixing involved in creating and maintaining applications, frameworks, or other software components. Developing products and services that empower developers to streamline their interactions with the ML platform. Working with public clouds (such as IAAS, AWS, GCP) and applying capacity management principles. Deploying and orchestrating containers in production environments, including technologies like Containers, Kubernetes, Service Mesh, ArgoCD and related tools. Actively engage with Tech Leads and ML Engineers across teams to elaborate on requirements and drive technical solutions. Own and develop features from end to end including infrastructure as code. Research, evaluate, prototype and drive adoption of new ML tools with reliability and scale in mind Strong dedication to proactively addressing and resolving issues, automating processes, and empowering engineers to self-service their operational needs for improved productivity. Availability for on-call support on a rotational basis. This role will support one or more direct or indirect contracts with the U.S. Federal Government which, due to federal government security requirements, mandates that all Workday personnel working on the contracts be United States citizens (naturalized or native). About You This role may require a security clearance at the TS/SCI w/CI Poly level. Applicants must have the ability to obtain and maintain a U.S. government issued security clearance. An active TS/SCI w/CI Poly is preferred. Basic Qualifications (P4 Sr. SDE) 7+ years of professional experience in DevOps engineering, infrastructure automation, and CI/CD pipeline development. 7+ years of experience with Python programming and container orchestration platforms (e.g., Docker, Kubernetes). Bachelor’s degree in Computer Science, STEM field, or equivalent practical experience. Other / Preferred Qualifications MLOps & Domain Experience: Hands-on experience designing, deploying, and scaling Machine Learning runtime platforms and inference pipelines in partnership with ML teams. Tooling & Infrastructure: Proficiency with Infrastructure as Code (e.g., Terraform), Git SCM workflows, and GitOps/CD engines (e.g., ArgoCD, Jenkins). Observability: Experience building end-to-end monitoring, metrics, and alerting pipelines using telemetry stacks like Grafana or Prometheus. Architecture & Code Quality: Strong understanding of distributed systems, SaaS microservices, Object-Oriented Design (OOD), and automated testing methodologies (unit, integration, e2e). Leadership & Operations: Proven experience leading technical initiatives and mentoring team members; willingness to participate in a rotating on-call schedule. Basic Qualification (P3 SDE) 5+ years of professional DevOps experience, including infrastructure automation and CI/CD pipeline development. 5+ years of experience with Python programming and containerization technologies (e.g., Docker, Kubernetes). Bachelor’s degree in Computer Science, STEM field, or equivalent practical experience. Other Qualifications: MLOps Experience: Hands-on experience deploying, monitoring, and scaling Machine Learning runtime environments or pipelines alongside ML teams. Tooling & Infrastructure: Experience with Infrastructure as Code (e.g., Terraform), Git workflows, and GitOps/CD engines (e.g., ArgoCD, Jenkins). Observability: Experience building monitoring, metrics, and alerting systems using telemetry stacks such as Grafana or Prometheus. Software Fundamentals: Solid understanding of Object-Oriented Design (OOD), distributed systems, and SaaS microservice architectures. Quality & Operations: Familiarity with automated testing frameworks (unit, integration, e2e) and willingness to participate in a rotating on-call schedule. Workday Pay Transparency Statement The annualized base salary ranges for the primary location and any additional locations are listed below. Workday pay ranges vary based on work location. As a part of the total compensation package, this role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus, as well as annual refresh stock grants. Recruiters can share more detail during the hiring process. Each candidate’s compensation offer will be based on multiple factors including, but not limited to, geography, experience, skills, job duties, and business need, among other things. For more information regarding Workday’s comprehensive benefits, please click here . Primary Location: USA.VA.Reston Primary Location Base Pay Range: $163,800 USD - $245,800 USD Additional US Location(s) Base Pay Range: $148,200 USD - $264,000 USD Our Approach to Flexible Work With Flex Work, we’re combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so rather than a number of required days in-office each week, we simply spend at least half (50%) of our time each quarter in the office or in the field with our customers, prospects, and partners (depending on role). This means you'll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together. Those in our remote "home office" roles also have the opportunity to come together in our offices for important moments that matter. Pursuant to applicable Fair Chance law, Workday will consider for employment qualified applicants with arrest and conviction records. Workday is an Equal Opportunity Employer including individuals with disabilities and protected veterans. Workday is committed to providing reasonable accommodations for qualified individuals during our application process, in order to perform one or more essential functions of their job, as well as regarding the use of AI tools for employment decision-making to any degree. Please see below for more details including how to request an accommodation as a qualified veteran, due to a disability or for religious reasons, or as otherwise provided under applicable law. Workday prohibits taking adverse action against any candidate or employee for reporting a possible violation of this policy, requesting one or more work accommodations, exercising a privacy right, or cooperating in an investigation in accordance with applicable law. Any employee who retaliates against a candidate or employee for doing so may be subject to disciplinary action, up to and including termination of employment, to the fullest extent allowable under applicable law. If you require a reasonable accommodation, you may email accommodations@workday.com , as far in advance as possible. Are you being referred to one of our roles? If so, ask your connection at Workday about our Employee Referral process! At Workday, we value our candidates’ privacy and data security. Workday will never ask candidates to apply to jobs through websites that are not Workday Careers. Please be aware of sites that may ask for you to input your data in connection with a job posting that appears to be from Workday but is not. In addition, Workday will never ask candidates to pay a recruiting fee, or pay for consulting or coaching services, in order to apply for a job at Workday.