Senior AI/ML Engineer

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.

Primary Responsibilities:

• Shift Time: 11:00 AM - 8:30 PM
• Design, develop, and deploy AI/ML solutions using LLMs, RAG, and Agentic AI patterns
• Leverage frameworks such as LangGraph, LangChain, PyTorch, TensorFlow, Keras for model and workflow development
• Architect scalable retrieval pipelines (chunking, embedding strategy, vector search, caching, routing) and integrate tool/function calling for agent workflows
• Build reproducible ML pipelines (data ingestion, feature engineering, training, evaluation, deployment) using tools like Azure ML, MLflow, Airflow, Kubeflow
• Implement CI/CD for ML (GitHub Actions/Azure DevOps), automated testing, and model registries with versioning and rollbacks
• Containerize services with Docker and deploy to Kubernetes (AKS preferred)
• Deploy on cloud platforms (preferably Azure) with robust observability (latency, cost, drift, safety, hallucinations)
• Implement A/B tests, canary releases, and performance optimization (throughput, memory, token usage, cache hit rates)
• Own cost governance and capacity planning (e.g., model selection, token budgeting, vector index sizing)
• Conduct rigorous evaluation using offline metrics + human‑in‑the‑loop (prompt tests, regression suites)
• Use or integrate evaluation/observability frameworks (e.g., Ragas/TruLens/DeepEval, custom eval harnesses)
• Implement guardrails and content safety checks (prompt injection defenses, PII redaction, policy enforcement)
• Collaborate with data engineering to operationalize data on
• Databricks/Spark/Snowflake/Delta Lake
• Design and manage vector databases/search (e.g., Azure Cognitive Search, Pinecone, Milvus, FAISS/Chroma) and feature stores (Feast/Tecton)
• Partner with stakeholders to preprocess, analyze, and interpret large-scale datasets to drive product outcomes
• Ensure code quality and security (static analysis, secrets management, least-privilege IAM, KMS)
• Adhere to data governance, model review, and compliance requirements; integrate with internal processes (e.g., UAIS, MLRB, or equivalent governance boards)
• Champion Responsible AI practices (fairness, transparency, safety, auditability)
• Lead technical design reviews, guide trade‑off decisions, and mentor engineers and data scientists
• Communicate complex findings clearly to technical and non‑technical audiences
• Stay current with GenAI/ML advancements and turn research into production‑ready solutions
• Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regard to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so

Required Qualifications:

• Bachelor's degree in Computer Science, Data Science, or related field; or equivalent practical experience
• 7+ years of professional experience in AI/ML or Data Science with track record of production deployments
• 4+ years hands‑on Python (typing, testing, packaging) and Git/GitHub workflows
• 4+ years with deep learning frameworks (PyTorch and/or TensorFlow/Keras)
• 3+ years deploying AI/ML solutions in production (APIs, batch, or streaming), preferably on Azure
• Proven experience with containers (Docker), CI/CD (GitHub Actions/Azure DevOps), and Kubernetes (AKS)
• Experience designing cloud solution architectures for AI/ML (networking, security, scalability, cost)
• Demonstrated capability in LLM/RAG system design, including vector search, prompt engineering, tool/function calling, and evaluation & guardrails

At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone - of every race, gender, sexuality, age, location and income - deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.