Lead AI/ML Engineer-Remote Nationwide or Hybrid in MN/DC

Role overview

Lead AI/ML Engineer (Hands-on technical leadership) for Optum’s Value Connect AI-first platform supporting value-based care. You will design and build scalable, production-ready AI/ML and GenAI solutions that turn complex healthcare data into actionable workflows for care, quality, finance, and provider enablement teams.

Responsibilities

• Lead the design, architecture, and end-to-end implementation of AI/ML, GenAI, RAG-based, and agentic solutions
• Apply machine learning, deep learning, statistical, and Generative AI techniques to solve clinical, operational, and financial business problems
• Build and optimize models including fine-tuning, quantization, performance tuning, and cost optimization
• Develop and maintain production-grade APIs (e.g., FastAPI/REST) to expose AI capabilities at scale
• Own MLOps practices: model versioning, lifecycle management, CI/CD, monitoring/logging, drift detection, and reliability
• Deploy and operate AI workloads on cloud platforms (Azure/AWS) using containerization and modern data platforms such as Databricks and PySpark
• Establish engineering best practices across quality, testing, security, responsible AI, design reviews, and code reviews
• Partner with product, data science, clinical, and business stakeholders, and mentor engineers while evaluating emerging AI technologies
• Use enterprise-approved AI tools to streamline developer workflows and automate tasks

Requirements

• Degree: 6+ years (Bachelor’s) or 4+ years (Master’s) or 3+ years (PhD) in AI/ML engineering or related fields
• 3+ years hands-on ML/DL/GenAI model building, validation, tuning, and evaluation
• 3+ years writing production-grade Python code using modern ML/AI libraries
• 2+ years building/deploying AI systems with RAG using vector databases and/or orchestration libraries (e.g., LangChain, LangGraph)
• Experience deploying/operating MLOps workloads on Azure/AWS with containerization
• Core software engineering practices: GitHub/version control, code reviews, and CI/CD

Nice to have

• Experience in healthcare technology, clinical data processing, or value-based care platforms
• Distributed computing experience (e.g., Spark, Databricks)
• Model optimization techniques such as quantization