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.

We are seeking a Senior AI / ML Engineer with solid experience building and operating production‑grade Machine Learning, Generative AI, and Agentic AI systems on Microsoft Azure.

This role focuses on MLOps, scalability, reliability, security, and governance, and works closely with data scientists, data engineers, platform, and application teams to deliver enterprise‑ready AI solutions.

Primary Responsibilities:

• Own the end‑to‑end ML lifecycle, including data ingestion, feature engineering, training, evaluation, deployment, monitoring, retraining, and rollback
• Design, build, and operate production‑grade ML pipelines using Azure‑native services with solid CI/CD and automation practices
• Build scalable data and feature pipelines using Azure Databricks (batch and streaming)
• Use Azure Machine Learning and MLflow for experiment tracking, model registry, and governed promotion across Dev/Test/Prod environments
• Design and deploy Generative AI solutions using Azure OpenAI, embeddings, vector search, and RAG pipelines
• Build Agentic AI workflows with multi‑step reasoning, tool usage, guardrails, observability, reliability, and cost control
• Implement monitoring for data drift, model drift, prediction quality, latency, and system health
• Ensure security, compliance, lineage, and auditability using RBAC, Azure Key Vault, and secure ML practices
• 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:

• Experience: 10+ years
• Bachelor's degree in Computer Science, Engineering, or equivalent practical experience
• 10+ years overall experience in software engineering, data engineering, or ML engineering
• 4+ years hands‑on experience in AI/ML engineering and MLOps
• Proven experience running ML systems in production at scale
• Solid hands‑on experience with Azure Databricks
• Primary Cloud: Microsoft Azure
• AI / ML Technical Skill Sets:
  • Machine Learning & Data
    • Solid understanding of supervised and unsupervised learning, statistical modelling, and model evaluation techniques
    • Experience with classification, regression, anomaly detection, and time‑series use cases
    • Hands‑on experience with feature engineering and strong data engineering fundamentals
• Model Development & ML Frameworks
  • Advanced Python skills with ML frameworks including:
    • Scikit‑learn
    • TensorFlow and/or PyTorch
  • Experience building, tuning, and optimising models for production performance
  • Familiarity with model explainability techniques (e.g. SHAP, feature importance)
• Generative AI & Large Language Models
  • Hands‑on experience with Azure OpenAI and LLM‑based systems.
  • Experience with:
    • Prompt engineering and optimisation
    • Embeddings and vector search
    • Retrieval Augmented Generation (RAG)
    • Frameworks such as LangChain and LangGraph
  • Understanding of LLM risks (hallucination, security, cost) and mitigation strategies
• Agentic AI
  • Experience designing and building agent‑based workflows, including:
    • Tool calling and multi‑step reasoning
    • Memory and state management
    • Guardrails and safety controls
  • Familiarity with emerging standards for agent interoperability, such as Model Context Protocol (MCP) or similar approaches (nice to have)
• MLOps & Productionisation (Core Focus)
  • Build and maintain CI/CD pipelines for ML training, testing, and deployment
  • Containerise ML workloads using Docker and deploy them on Kubernetes (AKS)
  • Manage Kubernetes deployments using Helm, ensuring:
    • Reproducible environments
    • Controlled configuration management
    • Reviewable and auditable infrastructure changes

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.