Manager AI/ML Engineering

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.

• Design, develop, and deploy advanced GenAI and NLP solutions to solve complex business and healthcare problems, using state‑of‑the‑art transformer models, LLMs, and modern ML frameworks
• Lead research, evaluation, and integration of new LLMs (GPT, Claude, Gemini, Anthropic), vector search technologies, prompt‑engineering techniques, and enterprise GenAI platforms
• Build and optimize Retrieval‑Augmented Generation (RAG) systems using vector databases (FAISS, Pinecone, Chroma), improving grounding, retrieval accuracy, and overall system reliability
• Architect and implement agentic AI workflows using frameworks like LangGraph, AutoGen, CrewAI, or Semantic Kernel, enabling single‑agent and multi‑agent systems for reasoning, planning, and tool‑calling
• Drive the development of high‑quality NLP pipelines—including tokenization, embeddings, seq‑to‑seq models, evaluation metrics, and domain adaptation—with a focus on performance, scalability, and robustness
• Perform advanced data analysis, preprocessing, and feature engineering to ensure data quality, reduce noise, and improve model reliability
• Develop and maintain scalable big‑data pipelines for ingestion, processing, and analysis, working with structured and unstructured datasets
• Optimize model inference, latency, and throughput, including integration with LLM gateways, guardrails, filters, and enterprise evaluation frameworks
• Scientist Responsibilities: (manager discretion if AI responsibilities are already present in JD): Collaborate with research, engineering, and product teams to translate cutting-edge AI advancements into production-ready capabilities. Uphold ethical AI principles by embedding fairness, transparency, and accountability throughout the model development lifecycle