ML Engineer Jobs

ML Engineer

AgreeYa Solutions

Plano, TX

Job Title: ML Engineer Location: Plano, TX (onsite) Need local candidates only, F2F interview Job Description: This role is ML Engineering with hands-on Software Engineering skills using Python and Pyspark, Databricks. Strong Python, Databricks and PySpark experience with Spark, Kafka, Snowflake, MongoDB, PostgreSQL, Redis, Azure cloud. Advanced No-SQL (MongoDB) and SQL (Postgres) and data modeling for slowly changing dimensions / temporal mappings. Experience building production-grade ML pipelines, and data pipelines. Solid Python development skills with APIs development (FastAPIs) and familiarity with ML workflows. Delta Lake, MLflow, and workflow orchestration experience. Agentic development and GenAI experience will be a big plus Familiarity with ELK (Elastic Kibana) Please note that DE with GenAI knowledge will not be shortlisted; The candidate must have classical ML/DS exposure with production pipeline design and development experience. About AgreeYa: AgreeYa is a global systems integrator delivering a competitive advantage for its customers through software, solutions, and services. Established in 1999, AgreeYa is headquartered in Folsom, California, with a global footprint and a team of more than 1,800+ professionals across offices. AgreeYa works with 550+ organizations ranging from Fortune 100 firms to small and large businesses across industries such as Telecom, Banking, Financial Services & Insurance, Healthcare, Utility & Energy, Technology, Public Sector, Pharma & Biotech, Retail, Client, and others. Please visit us at for more information. Equal Opportunity: AgreeYa is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, gender identity, sexual orientation, national origin, disability, veteran status or other protected characteristics. Visit our website at to learn about our Career & Cultures.

ML ENGINEER

Learn Beyond Consulting LLC

Atlanta, GA

Job Overview Job Code: JPC - 1333 Title: Sr. ML Engineer Location: Atlanta, GA Rate: USD 52/hr Account: New Logo Positions: 1 Role Summary & Responsibilities Delivery and Execution (70%): Design, build, and deploy secure, scalable machine learning and AI solutions through daily pairing, collaborate with cross-functional product teams, write custom code for infrastructure automation and testing, and monitor production systems via dashboards and logging. Support and Enablement (20%): Provide production application support, monitor service-level objectives, troubleshoot performance and capacity, and field questions from peer teams. Learning (10%): Participate in communities of practice, continuous learning, and exploring emerging software and machine learning technologies. Key Qualifications Experience: 5+ years in Machine Learning Engineering, AI Engineering, or Software Engineering building production-grade solutions. Core Technical Skills: Python, PyTorch, TensorFlow, Scikit-learn, Pandas, SQL, NoSQL, and data pipelines. AI/ML Specializations: Agentic AI applications, LLM-powered solutions, RAG systems, knowledge graphs, graph engineering, vector databases, and semantic search. Cloud & MLOps: Google Cloud Platform (Vertex AI, BigQuery), distributed systems, microservices, APIs, CI/CD, and automated testing.

ML Engineer

Solventum

United States

Thank you for your interest in joining Solventum. Solventum is a new healthcare company with a long legacy of solving big challenges that improve lives and help healthcare professionals perform at their best. At Solventum, people are at the heart of every innovation we pursue. Guided by empathy, insight, and clinical intelligence, we collaborate with the best minds in healthcare to address our customers’ toughest challenges. While we continue updating the Solventum Careers Page and applicant materials, some documents may still reflect legacy branding. Please note that all listed roles are Solventum positions, and our Privacy Policy: applies to any personal information you submit. As it was with 3M, at Solventum all qualified applicants will receive consideration for employment without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. Job Description: ML Engineer 3M Health Care is now Solventum At Solventum, we enable better, smarter, safer healthcare to improve lives. As a new company with a long legacy of creating breakthrough solutions for our customers’ toughest challenges, we pioneer game-changing innovations at the intersection of health, material and data science that change patients' lives for the better while enabling healthcare professionals to perform at their best. Because people, and their wellbeing, are at the heart of every scientific advancement we pursue. We partner closely with the brightest minds in healthcare to ensure that every solution we create melds the latest technology with compassion and empathy. Because at Solventum, we never stop solving for you. The Impact You’ll Make in this Role As an ML Engineer, you will be responsible for building and maintaining the pipelines that power AI in our Healthcare Information Systems (HIS). We are looking for a practical, detail-oriented engineer who is passionate about MLOps, data reliability, and production stability. In this role, you won’t just be building models; you will be ensuring those models work reliably in the real world. You will help bridge the gap between data science and software engineering by implementing automated workflows, managing cloud infrastructure, and ensuring our AI services are secure and scalable. Key Responsibilities 1. MLOps & Deployment Pipeline Development: Build and maintain CI/CD pipelines for machine learning, focusing on automated testing, model deployment, and version control (using tools like MLflow or Git). Model Serving: Deploy ML models as scalable APIs and microservices, ensuring they meet performance and latency requirements for clinical use. Monitoring: Implement basic monitoring tools to track model performance, data drift, and system health in production. 2. Data Engineering & Integration Data Pipelines: Develop and optimize ETL processes to transform healthcare data (FHIR, HL7) into clean, usable datasets for model training and inference. Feature Management: Help build and maintain feature stores and data layers that ensure consistency between training and production environments. System Integration: Work closely with backend teams to integrate ML outputs into our core healthcare applications. 3. Engineering Best Practices Code Quality: Write clean, maintainable, and well-documented Python code. Participate in code reviews to ensure system reliability. Containerization: Use Docker and Kubernetes to package and orchestrate ML workloads across different environments. Security & Compliance: Follow established protocols to ensure all data handling and deployments meet HIPAA and HITRUST security standards. Your Skills and Expertise To set you up for success in this role from day one, Solventum requires (at a minimum) the following qualifications: Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Engineering, or a related field. 3–5 years of professional experience in software engineering or data engineering, with at least 2 years focused on machine learning production environments. AND Programming: Strong proficiency in Python and familiarity with SQL. Knowledge of a compiled language (like Go or Java) is a plus. Cloud & Infrastructure: Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP) and containerization (Docker). ML Tools: Familiarity with ML libraries (PyTorch or Scikit-learn) and MLOps tools (like Airflow, Prefect, BentoML, or Kubeflow). Data Tools: Experience with data processing frameworks (like Pandas, Spark, or dbt). Additional qualifications that could help you succeed even further in this role include: Familiarity with deploying Large Language Models (LLMs) or using frameworks like LangChain. Experience working in a regulated environment (Healthcare, Finance, etc.). Understanding of API design and microservices architecture. Work location: Remote Travel: May include up to 10% domestic Must be legally authorized to work in country of employment without sponsorship for employment visa status (e.g., H1B status). Supporting Your Well-being Solventum offers many programs to help you live your best life – both physically and financially. To ensure competitive pay and benefits, Solventum regularly benchmarks with other companies that are comparable in size and scope. Onboarding Requirement: To improve the onboarding experience, you will have an opportunity to meet with your manager and other new employees as part of the Solventum new employee orientation. As a result, new employees hired for this position will be required to travel to a designated company location for on-site onboarding during their initial days of employment. Travel arrangements and related expenses will be coordinated and paid for by the company in accordance with its travel policy. Applies to new hires with a start date of October 1st 2025 or later.Responsibilities of this position include that corporate policies, procedures and security standards are complied with while performing assigned duties. Solventum is committed to maintaining the highest standards of integrity and professionalism in our recruitment process. Applicants must remain alert to fraudulent job postings and recruitment schemes that falsely claim to represent Solventum and seek to exploit job seekers. Please note that all email communications from Solventum regarding job opportunities with the company will be from an email with a domain of @solventum.com. Be wary of unsolicited emails or messages regarding Solventum job opportunities from emails with other email domains. Please note, Solventum does not expect candidates in this position to perform work in the unincorporated areas of Los Angeles County.Solventum is an equal opportunity employer. Solventum will not discriminate against any applicant for employment on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or veteran status. Please note: your application may not be considered if you do not provide your education and work history, either by: 1) uploading a resume, or 2) entering the information into the application fields directly. Solventum Global Terms of Use and Privacy Statement Carefully read these Terms of Use before using this website. Your access to and use of this website and application for a job at Solventum are conditioned on your acceptance and compliance with these terms. Please access the linked document by clicking here. Before submitting your application you will be asked to confirm your agreement with the terms. Originally posted on Himalayas

ML Engineer

Micro1

Remote

Job Description Pay: $100–$150/hour Location: Global, fully remote Job Type: Contractor (~15 hours per week) Schedule: Flexible—you choose the hours and days you work, including weekends if desired We are looking for highly skilled Machine Learning Experts to contribute to an AI training project involving model development, training and inference systems, numerical computing, performance optimization, and Python. The work involves creating, solving, reviewing, and validating challenging machine-learning engineering tasks. A representative task may require implementing or modifying a model, constructing a reproducible training or inference workflow, optimizing memory or throughput, debugging numerical or system-level failures, and verifying that the resulting implementation satisfies objective correctness and performance requirements. This role is designed for experienced ML engineers and researchers who understand the systems beneath high-level APIs. Candidates should have meaningful practical experience with multiple tools from the modern ML stack and be able to explain what they personally built, optimized, or operated. What You’ll Work On Develop and validate machine-learning models, training pipelines, inference systems, and supporting infrastructure. Implement model components, data pipelines, evaluation systems, and numerical methods. Build reproducible programmatic workflows using Python and command-line tools. Work with tensor operations, automatic differentiation, model architectures, tokenization, batching, and generation. Optimize training or inference for latency, throughput, memory usage, and hardware utilization. Diagnose numerical instability, incorrect tensor behavior, memory bottlenecks, distributed-system failures, and performance regressions. Compare model implementations and determine whether results are correct and reproducible. Review AI-generated code and technical solutions for correctness, efficiency, and engineering quality. Design objective tests, benchmarks, and verification criteria. Clearly document technical decisions, trade-offs, and limitations. Required Qualifications A master’s degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Statistics, Engineering, or a closely related quantitative discipline. Strong professional or research experience in machine learning. Practical proficiency with Python. Meaningful experience with at least two relevant ML frameworks, libraries, or inference tools. Strong understanding of model training, evaluation, numerical computation, or inference. Ability to debug ML systems beyond surface-level API usage. Ability to explain implementation decisions, performance trade-offs, and failure modes clearly. Experience building reproducible technical workflows. Relevant tools may include: PyTorch JAX NumPy and SciPy SGLang vLLM llama.cpp Hugging Face Transformers Hugging Face Tokenizers Equivalent tools may also be considered when the candidate demonstrates directly relevant depth. Experience at a well-established technology company, AI laboratory, research organization, or other recognized engineering environment is strongly preferred. Exceptional open-source or academic experience may also qualify. Process Apply to the role and complete the screening questions. Complete an AI interview of approximately 30 minutes. Complete a technical assessment, if required. Complete the hiring manager review. Compensation Structure Compensation is output-based. Experts are paid per task that meets the project specifications. The time required to complete each task may vary depending on the expert’s experience and workflow. Minimum submission requirements apply. Start Timeline & Availability We typically fill roles within 48 hours and are looking for experts who are ready to begin immediately. If selected, you will be expected to start your first task within 24–48 hours of completing onboarding. Originally posted on Himalayas

ML Engineer

Apex Systems

New Ulm, MN

Job#: 3050994 Job Description: Machine Learning Engineer (MLOps) Location: Remote / Hybrid Duration: Contract-to-Hire Overview We are seeking a Machine Learning Engineer to join a growing AI team focused on building and scaling production machine learning solutions in a highly regulated environment. This role will be responsible for developing MLOps infrastructure, supporting machine learning deployments, optimizing data pipelines, and ensuring AI models operate reliably and securely in production. The ideal candidate will have a strong software engineering background, hands-on experience with cloud technologies, and a passion for building scalable machine learning systems. Key Responsibilities Machine Learning & MLOps Develop and maintain CI/CD pipelines for machine learning workflows. Automate model testing, deployment, versioning, and monitoring. Deploy machine learning models as scalable APIs and microservices. Monitor production model performance, system health, and data quality. Support end-to-end ML lifecycle management. Data Engineering Design and optimize ETL and data processing pipelines. Transform structured and unstructured data for machine learning applications. Build and maintain feature stores and data infrastructure supporting AI initiatives. Ensure consistency between training and production environments. Cloud & Infrastructure Deploy and manage machine learning workloads within AWS, Azure, or Google Cloud Platform environments. Utilize Docker and Kubernetes for containerization and orchestration. Improve scalability, reliability, and performance of AI systems. Support infrastructure automation and operational best practices. Engineering Excellence Write clean, maintainable, and well-documented Python code. Participate in code reviews and engineering best practices. Collaborate with cross-functional teams including software engineers, data engineers, and data scientists. Ensure adherence to security, compliance, and data governance requirements. Required Qualifications Bachelor`s or Master`s degree in Computer Science, Software Engineering, Data Engineering, or related field. 3+ years of software engineering, machine learning engineering, or data engineering experience. 2+ years supporting production machine learning environments. Strong Python development experience. Experience with SQL and modern data processing frameworks. Hands-on experience with AWS, Azure, or Google Cloud Platform. Experience with Docker and containerized applications. Experience with machine learning frameworks such as PyTorch or Scikit-Learn. Familiarity with MLOps tools including MLflow, Kubeflow, Airflow, Prefect, BentoML, or similar. Experience with Pandas, Spark, dbt, or related data technologies. Preferred Qualifications Experience deploying and supporting Large Language Models (LLMs). Experience with LangChain or similar AI frameworks. Background working within healthcare, life sciences, financial services, or other regulated industries. Knowledge of API development and microservices architecture. Familiarity with healthcare interoperability standards such as HL7 and FHIR. Technical Skills Python Machine Learning MLOps Kubernetes Docker AWS Azure Google Cloud Platform MLflow Kubeflow Airflow Spark Pandas SQL ETL LangChain LLMs API Development Microservices Everforth Apex is a world-class IT services company that serves thousands of clients across the globe. When you join Everforth Apex, you become part of a team that values innovation, collaboration, and continuous learning. We offer quality career resources, training, certifications, development opportunities, and a comprehensive benefits package. Our commitment to excellence is reflected in many awards, including ClearlyRateds Best of Staffing in Talent Satisfaction in the United States and Great Place to Work in the United Kingdom and Mexico. Everforth Apex uses a virtual recruiter as part of the application process. Click for more details. By applying for this job, you agree to receive calls, AI-generated calls, text messages, or emails from Everforth Apex and its affiliates, and contracted partners. Frequency varies for text messages. Message and data rates may apply. Carriers are not liable for delayed or undelivered messages. You can reply STOP to cancel and HELP for help. You can access our privacy policy at Everforth Apex Benefits Overview: Everforth Apex offers a range of supplemental benefits, including medical, dental, vision, life, disability, and other insurance plans that offer an optional layer of financial protection. We offer an ESPP (employee stock purchase program) and a 401K program which allows you to contribute typically within 30 days of starting, with a company match after 12 months of tenure. Everforth Apex also offers a HSA (Health Savings Account on the HDHP plan), a SupportLinc Employee Assistance Program (EAP) with up to 8 free counseling sessions, a corporate discount savings program and other discounts. In terms of professional development, Everforth Apex hosts an on-demand training program, provides access to certification prep and a library of technical and leadership courses/books/seminars once you have 6+ months of tenure, and certification discounts and other perks to associations that include CompTIA and IIBA. Everforth Apex has a dedicated customer service team for our Consultants that can address questions around benefits and other resources, as well as a certified Career Coach. You can access a full list of our benefits, programs, support teams and resources within our `Welcome Packet` as well, which an Everforth Apex team member can provide. Everforth Apex Systems is an equal opportunity employer. We do not discriminate or allow discrimination on the basis of race, color, religion, creed, sex (including pregnancy, childbirth, breastfeeding, or related medical conditions), age, sexual orientation, gender identity, national origin, ancestry, citizenship, genetic information, registered domestic partner status, marital status, disability, status as a crime victim, protected veteran status, political affiliation, union membership, or any other characteristic protected by law. Everforth Apex will consider qualified applicants with criminal histories in a manner consistent with the requirements of applicable law. If you require an accommodation under the Americans with Disabilities Act to participate in an interview with a virtual recruiter or to use our website for a search or application, please contact our Benefits Department at or . Please note that this contact information is strictly to be used for medical ADA accommodations and that no other inquiries will be answered. UnitedHealthcare creates and publishes the Transparency in Coverage Machine-Readable Files on behalf of Everforth Apex Systems.

At Trunk Tools, we’re the leading AI company revolutionizing construction, the second-largest industry on earth. We recently raised a $40M Series B led by Insight Partners, bringing our total funding to $70M from top-tier investors including Redpoint and Innovation Endeavors. This new round is fueling our next phase of growth as we scale AI agents across the jobsite. Our mission is to build the future of construction through intelligent automation. Despite being a $13+ trillion industry, construction still runs largely on analog processes, we’re changing that by embedding AI directly into field operations. Founded by builders and technologists (Stanford, MIT), our team has delivered software used by over 140,000 field professionals, impacting millions of users and contributing to $10B+ in built projects. Many of us come from the field ourselves, giving us a deep understanding of the industry’s unique challenges. After years of building the “brain” of construction, we’re now launching production-ready AI agents, starting with intelligent document processing and Q&A, and rapidly expanding into core operational workflows. Our team has doubled in the past year, and with 65+ employees (25+ engineers), we’re scaling fast and entering a period of hypergrowth. This is a rare opportunity to join at an inflection point. What you will do and achieve: Own and evolve core parts of our AI platform, spanning search, retrieval, and multi-agent orchestration. Lead the design and build-out of a multi-agent system, including defining new agent “pillars” and how they collaborate in production. Architect and scale document processing pipelines (Kubernetes-based), including ingestion, parsing, chunking, indexing, and structured data extraction across heterogeneous document types. Design and iterate on search and retrieval systems (ranking, query understanding, QA) grounded in real user behavior and product needs. Help build and expand our knowledge graph, modeling entities and relationships to power downstream reasoning and retrieval. Drive ambiguous, high-impact projects end-to-end, from problem definition through experimentation and productionization. Establish and improve evaluation and experimentation frameworks to measure system quality and guide iteration. Write clean, maintainable, production-grade code and raise the bar for engineering quality across the team. Who you are: 7+ years of experience building and shipping production ML/AI systems. Proven track record of leading complex, ambiguous projects and driving them to impact. Strong experience with agentic systems, LLM-based applications, or orchestration frameworks. Deep experience in document processing pipelines (e.g., parsing, chunking, indexing, structured extraction), ideally in distributed systems (Kubernetes or similar). Experience building or working with knowledge graphs / provenance graphs and modeling relationships between entities. Background in one or more of: search/ranking systems, NLP, recommendation systems, or large-scale data/ML infrastructure. Strong coding skills (Python, Go, or similar) with an emphasis on production systems. Highly analytical, product-minded, and comfortable using data to drive decisions. Bonus : experience in construction or other document-heavy industries. What we offer 🎖️ A close-knit and collaborative early-stage startup environment where every voice is heard and every opinion matters 💰 Competitive salary and stock option equity packages 🏥 4 Medical Plans to choose from including 100% covered option. Plus Dental and Vision Insurance! 🤓 Learning & Growth stipend 🏠Flexible long-term work options (remote and hybrid) 🥨 Free lunch provided in the office in NYC & Austin - you’ll never go hungry with us! 🛫 Unlimited PTO; We truly believe in work-life balance and that hard work should be balanced with time for rest and rejuvenation 🏝 IRL / In-Person retreats throughout the year Please note: All official communication from Trunk Tools will come from an email address ending in @ trunk.tools . If you receive outreach from any other domain, please disregard it or report it to us. At Trunk Tools, we’re working hard to build a more productive and safer environment within the construction industry, and we strive to live by these same values here at Trunk Tools HQ. As an equal-opportunity employer, we are committed to building an inclusive environment where you can be you. We work hard to evaluate all employees and job applicants consistently, without regard to race, color, religion, gender, national origin, age, disability, pregnancy, gender expression or identity, sexual orientation, or any other legally protected class. Please mention the word **EMINENT** and tag RMTY4LjE0NC44NS4xMzE= when applying to show you read the job post completely (#RMTY4LjE0NC44NS4xMzE=). This is a beta feature to avoid spam applicants. Companies can search these words to find applicants that read this and see they're human.

AI / ML Engineer

NTT DATA Americas, Inc

Sandy Springs, GA

Business Consultant AI/ML Engineer Location: Atlanta/Chicago Employment Type: Contract/Permanent Role Summary NTT DATA``s Client is seeking an experienced AI/ML Engineer to design, develop, and deploy scalable Artificial Intelligence and Machine Learning solutions. The ideal candidate should have strong hands-on experience with Python, machine learning frameworks, data processing, and cloud-based AI/ML services. The role will collaborate with data scientists, data engineers, application develop

  Responsibilities: Conducting applied research in AI/ML, data analytics, and computational modelling. Designing, developing, and evaluating algorithms, models, and prototypes. Applying ML to structured and unstructured data sources, including multimodal or real-time streams. Supporting research on AI assurance, interpretability, adversarial robustness, or policy implications. Collaborating with interdisciplinary teams, including behavioural scientists, domain experts, and systems engineers. Preparing technical deliverables and briefings for government stakeholders. Contributing to the preparation of research proposals and technical work plans.   Qualification: PhD plus 5 years of research experience, or at least Mater of Science plus 10 years of engineering research experience including success capturing and leading large projects, or a Bachelor of Science plus 15 years of relevant experience and a record of significant engineering achievement and show promise of continued productivity Initiate new projects with long-term research goals, tackling more complex problems than an Assistant Research Engineer, leading work on multiple, concurrent projects, and managing cross-functional engineering teams Serve as Principal Investigator or having primary responsibility for a significant part of a project Interact with sponsor/customers Expected to identify funding opportunities and serve as Principal Investigator on large proposals Generate significant intellectual property that may be licensed by third parties Mentor junior staff and Professional Track Faculty Specialists and participating in their promotion sub-committees Recognized as an authoritative subject matter expert and receive commensurate recognition

Lead ML Engineer

Rivago infotech inc

Manor, TX

Role: Lead ML Engineer - Fraud Detection Location: Austin, TX (100% Onsite) - No flexibility Experience: 7-12 Years Role Summary We are looking for a Machine Learning Engineer to build and support production-grade fraud detection solutions. The role focuses on real-time inference, feature engineering, APIs, graph-based fraud detection, and production deployment support. Key Skills Machine Learning Engineering and Real-Time Inference Python, APIs, and Microservices Google Cloud Platform and Databricks Neo4j / Graph Databases and Feature Stores Data Pipelines and Feature Engineering MLOps, Monitoring, and Production Support Agentic AI Architecture (good to have) Responsibilities Build and deploy fraud detection services for production use. Develop low-latency inference solutions with a target of less than 250 ms. Design feature engineering pipelines for ML use cases. Integrate ML models with REST APIs and microservices. Support graph-based fraud detection using Neo4j. Improve scoring performance, reliability, and scalability. Work with MLOps teams for releases, monitoring, and production support. Support data quality, governance, and operational activities. Required Qualifications Hands-on experience in Python and ML model deployment. Experience with APIs, microservices, and production ML systems. Knowledge of data pipelines, data engineering, and feature stores. Exposure to Google Cloud Platform, Databricks, Data Lake, or Data Warehouse platforms. Basic understanding of MLOps, monitoring, and release support. Good communication and problem-solving skills. Nice to Have Fraud detection, risk analytics, or scoring model experience. Experience with Neo4j or graph-based ML solutions. Understanding of Agentic AI architecture.

AI/ML Engineer

WiselyWise

United States

Category: Technology Location: About Us: ​ WiselyWise is a leading innovator in AI-driven technology. We are seeking a highly skilled AI/ML Engineer to join our team and drive the development and deployment of advanced machine learning models and AI-driven solutions. The ideal candidate will have a strong background in machine learning algorithms, data processing, and software engineering, with a passion for solving complex problems in a dynamic environment. This role will play a critical part in the implementation of AI technologies within the upstream Oil & Gas sector, helping to optimize exploration, drilling, and production processes. Job Overview: We are seeking a highly skilled AI/ML Engineer to join our team and drive the development and deployment of advanced machine learning models and AI-driven solutions. The ideal candidate will have a strong background in machine learning algorithms, data processing, and software engineering, with a passion for solving complex problems in a dynamic environment. This role will play a critical part in the implementation of AI technologies within the upstream Oil & Gas sector, helping to optimize exploration, drilling, and production processes. Requirements Key Responsibilities: Model Development:Design, develop, and implement machine learning models and AI algorithms tailored to industry-specific use cases, particularly in predictive analytics, natural language processing, and computer vision. Data Processing:Collaborate with data engineers to build and maintain robust data pipelines, ensuring high-quality data is available for model training and deployment. Algorithm Optimization:Optimize machine learning models for performance, scalability, and accuracy, employing techniques such as hyperparameter tuning, model selection, and feature engineering. Collaboration:Work closely with data scientists, domain experts, and software developers to integrate AI models into production systems and create end-to-end solutions that meet business objectives. Model Deployment:Deploy machine learning models into production environments using industry-standard tools and frameworks, ensuring reliability and scalability. Continuous Improvement:Monitor the performance of AI models post-deployment, making iterative improvements based on feedback and changing business needs. Innovation:Stay up-to-date with the latest advancements in AI/ML technologies and best practices, and apply this knowledge to drive continuous innovation within the team. Documentation:Create comprehensive documentation for developed models, algorithms, and processes to ensure knowledge sharing and maintainability. Qualifications: Education:Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field. A Ph.D. is a plus. Experience:3+ years of experience in AI/ML engineering, with a proven track record of developing and deploying machine learning models in a production environment. Technical Skills: Proficiency in programming languages such as Python, R, or Java. Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn. Strong understanding of data structures, algorithms, and software design principles. Experience with cloud platforms like AWS, Azure, or Google Cloud for deploying AI models. Familiarity with big data technologies such as Hadoop, Spark, or Kafka is a plus. Experience with containerization and orchestration tools like Docker and Kubernetes. Analytical Skills:Strong problem-solving skills with the ability to analyze complex datasets and develop innovative AI solutions. Communication:Excellent verbal and written communication skills, with the ability to collaborate effectively across multidisciplinary teams. Industry Knowledge:Experience in the Oil & Gas sector is a plus but not required. Preferred Qualifications: Experience with natural language processing (NLP) and computer vision. Experience with real-time data processing and streaming analytics. Familiarity with ethical AI practices and the ability to implement AI models responsibly. Benefits Why Join Us: Opportunity to work on cutting-edge AI projects that have a tangible impact on critical industries. Collaborative and innovative work environment. Competitive compensation and benefits package. Opportunities for professional growth and continuous learning. Details Originally posted on Himalayas

AI/ML Engineer

Cardinal Health

United States

What Data Science contributes to Cardinal Health The Data & Analytics Function oversees the analytics life-cycle in order to identify, analyze and present relevant insights that drive business decisions and anticipate opportunities to achieve a competitive advantage. This function manages analytic data platforms, the access, design and implementation of reporting/business intelligence solutions, and the application of advanced quantitative modeling. Data Science applies base, scientific methodologies from various disciplines, techniques and tools that extracts knowledge and insight from data to solve complex business problems on large data sets, integrating multiple systems. Job Overview We are seeking a product-oriented AI/ML Engineer who partners with product managers, software engineers, data engineers, and business stakeholders to design and deliver enterprise-scale Generative AI solutions. In this role, you will be hands-on in the development of AI-powered applications, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, intelligent automation workflows, and conversational experiences. The ideal candidate combines strong software engineering fundamentals with expertise in modern AI technologies and cloud-native application development. You will be responsible for transforming business problems into scalable AI solutions, building production-grade ML systems, integrating AI capabilities into enterprise platforms, and ensuring solutions are secure, reliable, and measurable. This role is ideal for an engineer who enjoys working across the full lifecycle of AI products, from experimentation and prototyping to deployment, monitoring, optimization, and business adoption. Qualifications 4-8yearsofexperienceinSoftwareEngineering,MachineLearningEngineering,AIEngineering,orrelatedfieldspreferred. Bachelor'sdegreeinComputerScience,Engineering,DataScience,ArtificialIntelligence,orrelateddiscipline;equivalentexperienceconsidered. StrongproficiencyinPythonandexperiencedevelopingproduction-gradeapplications. ExperiencebuildingRESTAPIsusingframeworkssuchasFastAPI,Flask,orsimilartechnologies. ExperienceworkingwithinAgileandSDLCframeworks. ExperienceusingGitHubandCI/CDplatforms(GitHubActions,GitLab,AzureDevOps,Jenkins,Harness,etc.). ExperiencecontainerizingapplicationsusingDocker. ExperiencedeployingandmanagingworkloadsonKubernetesplatforms(GKE,AKS,EKS,OpenShift,etc.). ExperienceworkingwithcloudplatformssuchasGoogleCloudPlatform(GCP),Azure,orAWS. Requirements ExperiencedesigningandimplementingGenerativeAIsolutionsusingLargeLanguageModels(OpenAI,Gemini,Claude,Llama,Mistral,orsimilar). StrongunderstandingofRetrieval-AugmentedGeneration(RAG)architectureandvectordatabases. ExperiencebuildingAIAgentsandmulti-agentworkflowsusingframeworkssuchasLangGraph,LangChain,CrewAI,SemanticKernel,orequivalent. ExperienceintegratingAIservicesthroughAPIsandenterprisesystems. Knowledgeofpromptengineering,evaluationframeworks,andAIapplicationoptimizationtechniques. FamiliaritywithMLOpsandLLMOpsconcepts,includingmodeldeployment,monitoring,observability,andgovernance. ExperienceimplementingresponsibleAI,security,privacy,andcompliancecontrolsforenterpriseAIsolutions. AbilitytodevelopscalableAIsolutionsusingcloud-nativearchitecturesandevent-drivenpatterns. ExperienceworkingwithrelationalandNoSQLdatabases. Strongunderstandingofsoftwaredesignpatterns,testingstrategies,andproductionsupportpractices. ProvenabilitytocollaborateeffectivelywithproductteamstotranslatebusinessrequirementsintoAI-poweredsolutions. Excellentcommunicationskillswiththeabilitytoexplaintechnicalconceptstobothtechnicalandnon-technicalaudiences. What is expected of you and others at this level Applies comprehensive knowledge and a thorough understanding of concepts, principles, and technical capabilities to perform varied tasks and projects May contribute to the development of policies and procedures Works on complex projects of large scope Develops technical solutions to a wide range of difficult problems Solutions are innovative and consistent with organization objectives Completes work; independently receives general guidance on new projects Work reviewed for purpose of meeting objectives May act as a mentor to less experienced colleagues Anticipated salary range: $94,900 - $122,400 Bonus eligible: No Benefits: Cardinal Health offers a wide variety of benefits and programs to support health and well-being. Medical, dental and vision coverage Paid time off plan Health savings account (HSA) 401k savings plan Access to wages before pay day with myFlexPay Flexible spending accounts (FSAs) Short- and long-term disability coverage Work-Life resources Paid parental leave Healthy lifestyle programs Application window anticipated to close: 09/20/2026 *if interested in opportunity, please submit application as soon as possible. The salary range listed is an estimate. Pay at Cardinal Health is determined by multiple factors including, but not limited to, a candidate’s geographical location, relevant education, experience and skills and an evaluation of internal pay equity. Candidates who are back-to-work, people with disabilities, without a college degree, and Veterans are encouraged to apply. Cardinal Health supports an inclusive workplace that values diversity of thought, experience and background. We celebrate the power of our differences to create better solutions for our customers by ensuring employees can be their authentic selves each day. Cardinal Health is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, ancestry, age, physical or mental disability, sex, sexual orientation, gender identity/expression, pregnancy, veteran status, marital status, creed, status with regard to public assistance, genetic status or any other status protected by federal, state or local law. To read and review this privacy notice click here Originally posted on Himalayas

Closure Technologies is seeking a AI/ML Engineer who will Implement and maintain Retrieval-Augmented Generation (RAG) pipelines and integrate Large Language Models (LLMs) into applications, supported by API development and optimizing data storage through Postgres schema refinement. Clearance Requirement: TS/SCI with Polygraph Key Responsibilities: Implement and maintain RAG pipelines, including document processing, embedding generation, retrieval configuration, and prompt assembly. Integrate LLMs into applications using available APIs and frameworks. Develop and maintain REST API interactions to support data retrieval and system integration. Design or refine Postgres schemas to improve data organization and query performance. Required Qualifications: Demonstrated ability to conduct independent technical research, evaluate emerging AI/ML approaches, and apply advanced analytical problem-solving comparable to PhD-level research environments. Ability to rapidly learn and apply new AI/ML methodologies, tools, and frameworks in support of evolving mission requirements. Experience developing AI/ML applications focused on Retrieval-Augmented Generation (RAG), semantic retrieval, LLM integration, or related AI workflows. Strong proficiency in Python and modern AI/ML libraries, frameworks, and API integrations. Active/current TS/SCI with required polygraph. Willingness to work onsite full time. US citizenship required. Senior Labor Category: Minimum 8 years of experience with a Bachelor’s degree; or 7 years of experience with a Masters degree; or 6 years of experience with a Doctorate Preferred Qualifications: Advanced research experience in machine learning, deep learning, natural language processing, generative AI, reinforcement learning, computer vision, or related disciplines. Experience publishing research, contributing to open-source AI/ML initiatives, or leading experimental and prototype development efforts. Familiarity with model evaluation frameworks, fine-tuning workflows, inference optimization, and AI observability/monitoring tools. Experience with vector databases, AWS/cloud environments, Docker, and containerized AI/ML development workflows. Experience designing and integrating REST APIs and scalable data architectures.

Edge ML Engineer

Bright Vision Technologies

Charlotte — Ballantyne, NC 28277

Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential. Job Title: Edge ML Engineer Location: 100% Remote (U.S.) Position Type: Full-time, Direct W2 Salary Range: $100,000–$150,000 Annually Experience Required: 6+ years Job Summary We are looking for an Edge ML Engineer to design, optimize, and deploy machine learning models that run efficiently on resource-constrained edge devices, including mobile platforms, embedded systems, and specialized accelerators. The role requires deep expertise in model compression, quantization, and hardware-aware optimization, along with strong systems engineering skills to ship reliable AI capabilities outside the data center. The ideal candidate has shipped edge AI in production environments where compute, memory, energy, and connectivity constraints fundamentally shape the engineering trade-offs. Required Qualifications Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related field. Six or more years of experience in ML engineering, with significant work on edge or mobile AI. Strong proficiency in Python and C++. Hands-on experience with model compression, quantization, and pruning techniques. Experience with at least one major edge inference framework. Solid understanding of mobile and embedded hardware architectures. Experience deploying ML models to production on mobile or embedded platforms. Strong performance engineering and profiling skills. Familiarity with on-device privacy and security considerations. Strong communication and cross-functional collaboration skills. Preferred Qualifications Experience with custom NPU or DSP toolchains. Familiarity with federated learning or on-device personalization. Exposure to safety-critical or industrial edge deployments. Open-source contributions to edge AI frameworks. Experience optimizing LLMs for on-device inference. How to Apply Would you like to know more about this opportunity? For immediate consideration, please send your resume to jaya@bvteck.com or contact us at (908) 505-3545. Learn more about Bright Vision Technologies at www.bvteck.com. Bright Vision Technologies is an Equal Opportunity Employer. Equal Employment Opportunity (EEO) Statement Bright Vision Technologies (BV Teck) is committed to equal employment opportunity (EEO) for all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other protected status as defined by applicable federal, state, or local laws. This commitment extends to all aspects of employment, including recruitment, hiring, training, compensation, promotion, transfer, leaves of absence, termination, layoffs, and recall. BV Teck expressly prohibits any form of workplace harassment or discrimination. Any improper interference with employees' ability to perform their job duties may result in disciplinary action up to and including termination of employment.

Edge ML Engineer

Bright Vision Technologies

United States

Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential. Job Title: Edge ML Engineer Location: 100% Remote (U.S.) Position Type: Full-time, Direct W2 Salary Range: $100,000–$150,000 Annually Experience Required: 6+ years Job Summary We are looking for an Edge ML Engineer to design, optimize, and deploy machine learning models that run efficiently on resource-constrained edge devices, including mobile platforms, embedded systems, and specialized accelerators. The role requires deep expertise in model compression, quantization, and hardware-aware optimization, along with strong systems engineering skills to ship reliable AI capabilities outside the data center. The ideal candidate has shipped edge AI in production environments where compute, memory, energy, and connectivity constraints fundamentally shape the engineering trade-offs. Required Qualifications Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related field. Six or more years of experience in ML engineering, with significant work on edge or mobile AI. Strong proficiency in Python and C++. Hands-on experience with model compression, quantization, and pruning techniques. Experience with at least one major edge inference framework. Solid understanding of mobile and embedded hardware architectures. Experience deploying ML models to production on mobile or embedded platforms. Strong performance engineering and profiling skills. Familiarity with on-device privacy and security considerations. Strong communication and cross-functional collaboration skills. Preferred Qualifications Experience with custom NPU or DSP toolchains. Familiarity with federated learning or on-device personalization. Exposure to safety-critical or industrial edge deployments. Open-source contributions to edge AI frameworks. Experience optimizing LLMs for on-device inference. How to Apply Would you like to know more about this opportunity? For immediate consideration, please send your resume to or contact us at (908) 505-3545. Learn more about Bright Vision Technologies at www.bvteck.com. Bright Vision Technologies is an Equal Opportunity Employer. Equal Employment Opportunity (EEO) Statement Bright Vision Technologies (BV Teck) is committed to equal employment opportunity (EEO) for all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other protected status as defined by applicable federal, state, or local laws. This commitment extends to all aspects of employment, including recruitment, hiring, training, compensation, promotion, transfer, leaves of absence, termination, layoffs, and recall. BV Teck expressly prohibits any form of workplace harassment or discrimination. Any improper interference with employees' ability to perform their job duties may result in disciplinary action up to and including termination of employment. Originally posted on Himalayas

Edge ML Engineer

Bright Vision Technologies

United States

Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential. Job Title: Edge ML Engineer Location: 100% Remote (U.S.) Position Type: Full-time, Direct W2 Salary Range: $100,000–$150,000 Annually Experience Required: 6+ years Job Summary We are looking for an Edge ML Engineer to design, optimize, and deploy machine learning models that run efficiently on resource-constrained edge devices, including mobile platforms, embedded systems, and specialized accelerators. The role requires deep expertise in model compression, quantization, and hardware-aware optimization, along with strong systems engineering skills to ship reliable AI capabilities outside the data center. The ideal candidate has shipped edge AI in production environments where compute, memory, energy, and connectivity constraints fundamentally shape the engineering trade-offs. Required Qualifications Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related field. Six or more years of experience in ML engineering, with significant work on edge or mobile AI. Strong proficiency in Python and C++. Hands-on experience with model compression, quantization, and pruning techniques. Experience with at least one major edge inference framework. Solid understanding of mobile and embedded hardware architectures. Experience deploying ML models to production on mobile or embedded platforms. Strong performance engineering and profiling skills. Familiarity with on-device privacy and security considerations. Strong communication and cross-functional collaboration skills. Preferred Qualifications Experience with custom NPU or DSP toolchains. Familiarity with federated learning or on-device personalization. Exposure to safety-critical or industrial edge deployments. Open-source contributions to edge AI frameworks. Experience optimizing LLMs for on-device inference. How to Apply Would you like to know more about this opportunity? For immediate consideration, please send your resume to or contact us at (908) 505-3545. Learn more about Bright Vision Technologies at www.bvteck.com. Bright Vision Technologies is an Equal Opportunity Employer. Equal Employment Opportunity (EEO) Statement Bright Vision Technologies (BV Teck) is committed to equal employment opportunity (EEO) for all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other protected status as defined by applicable federal, state, or local laws. This commitment extends to all aspects of employment, including recruitment, hiring, training, compensation, promotion, transfer, leaves of absence, termination, layoffs, and recall. BV Teck expressly prohibits any form of workplace harassment or discrimination. Any improper interference with employees' ability to perform their job duties may result in disciplinary action up to and including termination of employment. Originally posted on Himalayas

AI/ML Engineer

Accenture Federal Services

Tampa, FL

Design, build, and optimize LLM and RAG pipelines for classification, summarization, Q&A, and retrieval. Develop embeddings, vector storage, retrieval logic, and LLM orchestration. Apply ML/DL frameworks, traditional ML, cloud services, containerization, and MLOps to produce secure, reliable production solutions in collaboration with cross-functional teams and mission SMEs. Top Skills: APIs, AWS, Azure, Bentoml, C++, Docker, Embeddings, Huggingface, Java, Llms, Mlflow, Mlops, Python, PyTorch, Retrieval-Augmented Generation (Rag), TensorFlow, Vector Databases Industry: Artificial Intelligence , Information Technology , Consulting , Cybersecurity

Senior ML Eng Location: NYC (onsite only – not remote) Alliance is the leading accelerator for crypto & AI founders. Since 2020 we’ve backed 300+ startups (Rain, Pump, Synthetix, Pendle, and many more), now collectively valued at $15B+. We’re hiring a Machine Learning Engineer to join our in-house engineering team. You’ll report directly to Carter (CTO) and will be responsible for owning features from the requirements definition stage to production. What You’ll Do Own applied ML end-to-end : turn a loosely defined problem into a dataset, an experiment, a model, and a production system without relying on a PM or a large engineering team. Build and operate production Python systems for data collection, enrichment, feature extraction, scoring, evaluation, and AI-assisted research. Develop models people can trust : define labels and features, build evaluation sets and backtests, catch leakage and bad source data, compare approaches, and know when a simpler model is the right answer. Move work from the model lab into production : own artifacts, feature and prompt compatibility, APIs, background jobs, observability, failure handling, and releases. Improve our LLM systems including structured extraction, research agents, prompt and model evaluation, and the guardrails needed to use untrusted external data safely. Work directly with stakeholders to decide what is worth building, explain model behavior and tradeoffs clearly, and iterate based on how the system is actually used. What we’re looking for Senior, self-directed ML engineer who can take an ambiguous problem from first experiment through a reliable production release. Deep experience with Python and applied machine learning ; comfortable moving between data exploration, training code, application code, APIs, and production debugging. Strong modeling judgment : problem and label definition, feature design, evaluation, backtesting, leakage, missing data, calibration, interpretability, and model selection. Enough software and data engineering depth to ship your own work : build pipelines and services, integrate external APIs, manage model artifacts and schemas, and maintain production workflows without heavy engineering support. Practical experience with LLM systems : structured outputs, model and prompt evaluation, observability, retries, cost and latency tradeoffs, and safe handling of untrusted inputs. Clear communicator with good product judgment who can work directly with non-technical stakeholders and turn model output into a useful decision or operating tool. Extremely high-agency , entrepreneurial, self-driven. NYC-based or willing to relocate (non-negotiable). Examples of strong qualifications (good to have but not required) Shipped ML products that people actually use , with evidence of owning the path from raw data and experimentation through deployment, monitoring, and iteration. Strong public work : a standout GitHub, useful open-source contributions, published research, technical writing, or unusually good independent experiments. Experience building prediction, ranking, classification, recommendation, or anomaly-detection systems on messy real-world data. Experience building LLM evaluation systems, structured extraction pipelines, research agents, or other production AI workflows. Founder, early ML hire, or senior individual contributor at a fast-moving startup, especially where you operated without a dedicated ML platform or large engineering team. Clear signals of exceptional technical or quantitative ability: strong research, competition results, Math/Physics Olympiad performance, or a top technical academic background. Why NOT join us Not willing to get hands dirty: doesn’t matter how important you were in past organizations; at Alliance we’re all builders, not managers (even though many of us were managers in past lives). Prioritizing work/life balance: this role demands focus, hunger, and a career-defining level of commitment. You must be locked in. Low agency: if you need someone else to set your priorities or keep you on track, you will fail. You can’t relocate to NYC. This is non-negotiable: our founders are here, and so are we. Why join us Work with the most ambitious founders in crypto and AI. Learn firsthand from hundreds of startups succeeding – or failing. Join a small, high-trust, high-performance team with outsized impact. We’re ex-Meta, WhatsApp, Coinbase, YC, and have collectively founded multiple venture-backed startups. We’re backed by S-tier investors including Initialized Capital, Founders Fund, Multicoin, and Dragonfly, along with angels such as Balaji Srinivasan (ex-Coinbase CTO), Kevin Weil (CPO at OpenAI), Kevin Lin (Twitch co-founder), and Jeremy Allaire (Circle CEO), among many others. Direct ownership and visibility: your work shapes how the next generation of founders discovers Alliance. Career accelerator: this role sets you up, experience- and network-wise, for any high-impact path in crypto/AI – at startups, venture firms, or your own company. Alliance startups are reinventing industries – from media to payments – and improving the lives of everyday people. You’ll have a front-row seat as they change the world.

What we’re doing isn’t easy, but nothing worth doing ever is. We envision a future powered by robots that work seamlessly with human teams. We build artificial intelligence that enables service robots to collaborate with people and adapt to dynamic human environments. Join our mission-driven team as we build out current and future generations of robots. As an ML Engineer, Manipulation, you will develop and deploy learning-based manipulation systems that enable mobile robots to interact reliably with the physical world in dynamic human environments. You’ll build perception-to-action models, training datasets, evaluation tooling, and deployment pipelines that improve robustness, generalization, and safety for real-world manipulation tasks at scale. Your work will directly impact the robot’s ability to perform complex interactions consistently across real sites with minimal special-case engineering. Responsibilities Develop learning-based manipulation models for end to end sensor-driven interaction (e.g., reaching, motion generation, and execution in dynamic environments). Build and maintain manipulation training pipelines: dataset creation from robot logs/teleop, action representations, augmentation, and distributed training. Design evaluation metrics and regression tests that quantify manipulation reliability, recovery behavior, and safety in real environments. Develop sim-to-real workflows for manipulation learning, including simulation environments, domain randomization, and failure-mode testing. Optimize and distill models for edge deployment; benchmark latency, memory use, and stability on target hardware. Partner with the AI platform team to integrate policies with control and safety systems, and validate end-to-end performance on robots. Analyze field performance, identify dominant failure modes, and drive iterative improvements through data collection and targeted retraining. Basic Qualifications Bachelor’s or Master’s degree in Robotics, Computer Science, Electrical Engineering, or related field (PhD a plus). 3+ years of experience applying ML to robotics manipulation, visuomotor control, or sequential to sequence models. Strong proficiency in PyTorch and experience building reliable training/evaluation pipelines. Strong software engineering skills in Python; ability to collaborate across ML and robotics teams. Preferred Qualifications Experience with Vision-Language-Action (VLA) models, behavior cloning, and/or transformer/diffusion policies for robotic control. Experience with sim-to-real training for manipulation (Isaac Sim/Mujoco or similar), including domain randomization and synthetic data. Experience deploying ML models to edge hardware (ONNX/TensorRT, quantization, performance profiling). Familiarity with safety-critical robotics integration and designing fallback/recovery behaviors.

AI/ML Engineer

Momento USA LLC

Minnetonka, MN

Momento USA is a global technology consulting, talent acquisition, and creative development firm that addresses clients' most pressing needs and challenges. We are currently looking for an AI/ML Engineer - Senior Position- AI/ML Engineer - Senior Location- Minnetonka, Minnesota (Day1 Onsite) Long Term Contract Position Overview: We are seeking a Senior AI Software Engineer to design, build, and scale our next-generation AI agents, applications, and platform capabilities. You own complex AI solutions from technical design through production operation and help establish the engineering patterns that enable teams across Medica to build with AI safely, reliably, and quickly. You combine strong software engineering fundamentals with hands-on experience using modern AI models, agent architectures, cloud infrastructure, and developer tooling. You operate with high autonomy, turn ambiguous business and technical problems into practical solutions, and make sound architectural tradeoffs. This role is expected to have an informed, opinionated perspective on how AI changes software engineering and how work gets done. You actively experiment with emerging technologies while maintaining a strong bias toward production reliability, measurable outcomes, security, maintainability, and appropriate use of AI in healthcare. Key accountability Desired key actions to successfully achieve key role accountabilities End ‑ to ‑ End AI Platform Development Design, implement, deploy, and operate AI pipelines and systems. Own evaluation setup, benchmarking, and the integration of components into products. Build reliable, secure, and observable production systems. AI Use Case Development Prototype, build, and productionize AI-powered features. Lead the technical solutioning of healthcare and enterprise challenges using modern AI tools and frameworks. Technical Collaboration & Code Quality Lead architectural discussions, code reviews, and pair programming. Establish engineering best practices and deliver clean, maintainable code. Required Skills: 5+ years of professional software engineering experience, including ownership of production systems. Strong software development skills using Python, Go, TypeScript, or comparable backend languages. Demonstrated experience designing, building, deploying, and operating cloud-native applications on AWS, Azure, Google Cloud Platform, or comparable platforms. Hands-on experience with infrastructure as code using Terraform or comparable declarative tooling. Strong working knowledge of Docker, containerization, CI/CD, GitHub, and modern software delivery practices. Experience with Kubernetes or comparable container orchestration platforms. Experience designing observable production systems using logging, metrics, tracing, alerting, and operational monitoring. Hands-on experience building applications using large language models, foundation model APIs, or modern AI development frameworks. Ability to design APIs, distributed services, asynchronous workflows, and reusable platform components. Strong understanding of software architecture, testing, reliability, security, and maintainability. Ability to independently navigate ambiguous technical problems, evaluate tradeoffs, and drive solutions from concept through production. High agency and demonstrated ability to remain current with rapidly evolving AI technologies and development practices. Strong written and verbal communication skills, including the ability to explain technical decisions and tradeoffs to technical and non-technical stakeholders. Thanks, Adam Walker (Aquib) Technical Recruiter Momento USA | Exceeding Customer Expectations… 440 Benigno Blvd, Unit#A 2nd Floor. Bellmawr, NJ 08031 Interstate Business Park Direct: || Tel : Ext 1021; Fax: Email: ; Web: . Note: Momento USA is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.

AI/ML Engineer

Rackner

United States

AI/ML Specialist Location: Remote Clearance Level: Active Secret Overview Rackner is seeking an AI/ML Specialist to support the responsible design, development, evaluation, and deployment of artificial intelligence and automation capabilities across educational and operational environments. The AI/ML Specialist will help identify high-value AI use cases, assess technical and organizational readiness, develop and deploy AI-enabled solutions, and support governance, monitoring, and adoption activities. This role will work across stakeholders, technical teams, data teams, and program leadership to integrate AI capabilities into existing business processes while ensuring solutions align with responsible AI principles, Government policy, and organizational strategy. The AI/ML Specialist will also support the evaluation of emerging AI and large language model platforms, develop intelligent automation solutions, and contribute to AI governance, procurement readiness, and enterprise adoption. Responsibilities Support the responsible integration of artificial intelligence into educational and operational business processes Design, develop, test, and deploy AI-driven solutions and process automations Conduct AI readiness assessments for proposed use cases Perform feasibility, benefit, risk, and implementation analyses using standardized evaluation frameworks Evaluate candidate AI use cases based on mission value, data readiness, technical complexity, security, governance, and expected return Develop technical supplements to enterprise AI governance frameworks, including: AI tool evaluation and adoption criteria Model performance monitoring and evaluation protocols AI risk and control requirements AI incident detection and response procedures Human oversight and escalation mechanisms Design and implement AI-enabled business process automations using Government-authorized platforms such as: Power Automate Power Apps Copilot Studio Comparable workflow and intelligent automation platforms Develop AI-enabled solutions through established solution delivery processes, including: Intake and requirements assessment Solution design Prototype development Testing and validation Security and governance review Production deployment Post-deployment monitoring Build and maintain AI agents and agent-enabled workflows Develop intelligent document processing capabilities for classification, extraction, summarization, routing, and related use cases Integrate AI capabilities with enterprise applications, data platforms, APIs, and workflow systems Develop and maintain automated workflows incorporating AI or machine learning components Support AI tool evaluation, pilot program development, and proof-of-concept initiatives Develop evaluation criteria, test plans, success metrics, and recommendations for AI pilots Evaluate emerging AI, machine learning, generative AI, and large language model platforms for organizational applicability Assess Department of Defense-developed, Government-provided, and commercially acquired AI/LLM platforms Support procurement readiness activities for AI tools, including requirements definition, technical evaluation, risk identification, and adoption criteria Develop AI-enabled analytics capabilities including: Predictive modeling Forecasting Natural-language query Classification and anomaly detection Decision-support capabilities Support development of semantic models and AI-ready data products within enterprise Lakehouse environments Develop Python-based AI/ML prototypes, integrations, evaluations, and automation components Support model and solution testing for accuracy, performance, reliability, bias, robustness, and operational suitability Establish and maintain model performance metrics and monitoring processes Support identification, triage, documentation, and response for AI-related incidents or unexpected model behaviors Collaborate with data engineers, analysts, governance teams, cybersecurity teams, and application developers to operationalize AI capabilities Translate stakeholder needs into AI use cases, technical requirements, solution designs, and acceptance criteria Support stakeholder engagement, demonstrations, workshops, training, and adoption activities Develop technical documentation, implementation guides, evaluation reports, and user-facing materials Support change management and adoption efforts for AI-enabled processes Ensure AI solutions align with applicable organizational AI strategies, AI guidelines, security requirements, and responsible AI principles Qualifications Experience designing, developing, evaluating, or implementing AI/ML solutions Experience with responsible AI frameworks, governance, or risk-management practices Experience with Power Automate, Copilot Studio, or comparable AI and workflow automation platforms Python proficiency Experience working with APIs, data sources, and enterprise applications to integrate AI-enabled capabilities Experience evaluating, piloting, or deploying AI, machine learning, generative AI, or LLM-based tools in organizational environments Understanding of the AI/ML solution lifecycle, including requirements gathering, development, testing, deployment, monitoring, and maintenance Experience developing prototypes, proofs of concept, or production AI-enabled applications Familiarity with model evaluation, performance measurement, and monitoring approaches Ability to assess technical feasibility, business value, implementation complexity, and risk for AI use cases Strong analytical, problem-solving, communication, and documentation skills Experience working with technical and non-technical stakeholders Ability to translate operational needs into practical AI-enabled solutions Active Secret clearance Preferred Qualifications Familiarity with the Department of Defense Responsible AI Strategy and related DoD AI guidance Experience developing or implementing AI governance frameworks Experience with generative AI and large language models Experience building AI agents or agentic workflows Experience with retrieval-augmented generation, embeddings, semantic search, or vector databases Experience developing intelligent document processing solutions Experience with Microsoft Fabric, Azure AI, Azure OpenAI, or related Microsoft cloud AI services Experience with Power Platform technologies, including Power Apps and Power Automate Experience developing predictive analytics, forecasting, or natural-language analytics capabilities Experience with model evaluation frameworks, guardrails, human-in-the-loop controls, or AI observability Experience evaluating AI tools for security, privacy, reliability, bias, and organizational fit Experience supporting AI procurement, technology selection, or pilot programs Familiarity with AI capabilities within enterprise Lakehouse or semantic-model architectures Experience within Department of Defense, federal, or education environments About Rackner Rackner is a software consultancy focused on building mission-critical systems for the U.S. government. Our teams work across cloud platforms, DevSecOps, AI/ML, distributed systems, and modern software engineering initiatives supporting federal agencies and national security missions. Rackner engineers and technical teams collaborate closely with leadership, program teams, and mission stakeholders to design, demonstrate, and improve software systems that address complex operational challenges. Benefits & Perks At Rackner, we believe that when our people grow, our company grows with them, and we are committed to supporting their growth, development and success. We are proud to offer a creative and forward-thinking environment that includes: • Company-supported certifications aligned to current and future program work, including cloud, Kubernetes, DevSecOps, security, AI/ML, project management, and related technical areas • Clear advancement tracks and future leadership opportunities • 401(k) with 100% match up to 6% • Comprehensive medical, dental, vision, life, and disability coverage • Generous PTO and paid holidays • Home-office equipment plan and remote work support • Fitness and wellness reimbursement • Weekly pay schedule and modern perks, including team events Equal Opportunity Rackner is an equal opportunity employer and considers all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or other protected characteristics. Originally posted on Himalayas