Lead AI/ML Engineer

Caring. Connecting. Growing Together.

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.

Primary Responsibilities:

• Lead architecture and delivery of ML/GenAI solutions (classification, forecasting, NLP, deep learning, LLM apps) at production scale
• Build robust data/feature pipelines over large clinical/claims datasets; write efficient, well-tested Python (pandas/NumPy) and SQL
• Develop and deploy LLM capabilities: prompt design, fine-tuning, RAG pipelines, vector indexing, and evaluation with guardrails
• Establish MLOps/LLMOps best practices: CI/CD, model registry, experiment tracking, monitoring, drift detection, A/B testing, cost/perf optimization
• Ensure data privacy and compliance (HIPAA/PHI handling, access controls, auditability) and champion model governance and Responsible AI
• Translate business problems into technical roadmaps; communicate trade-offs and results to executives and non-technical partners
• Mentor engineers and set engineering standards (code reviews, documentation, reliability, observability)

Required Qualifications:

• Bachelors in Computer Science, Engineering, Math, or related field required; MS/PhD preferred or equivalent experience
• 10+ years of professional experience in software/ML engineering, including 3+ years leading projects or teams
• Hands-on GenAI experience: LLMs, embeddings, RAG, fine-tuning, evaluation; familiarity with Hugging Face and LangChain/LlamaIndex
• Solid foundation in statistics and ML (hypothesis testing, experimental design, feature engineering, supervised/unsupervised methods)
• Deep learning expertise (PyTorch or TensorFlow) and modern NLP (transformers)
• Expert Python and pandas stack; ability to write vectorized, high-performance code; solid testing practices (pytest) and Git
• Solid data engineering skills: SQL; experience with Spark/Dask and workflow orchestration (Airflow/Prefect)
• Cloud proficiency (AWS/Azure/GCP) and containerization/orchestration (Docker/Kubernetes); CI/CD and IaC (Terraform) exposure
• Proven excellent communication and stakeholder management skills

Preferred Qualifications:

• Healthcare domain experience: claims, EHR/HL7/FHIR, coding (ICD/CPT), risk adjustment, quality measures, de-identification
• Big data platforms (Databricks, Snowflake, BigQuery) and streaming (Kafka); lakehouse patterns
• MLOps stack: MLflow/SageMaker/Azure ML/Vertex; model monitoring/observability
• Vector databases (FAISS, Pinecone, pgvector), knowledge graphs (Neo4j), and ontologies (UMLS/SNOMED)
• Security/compliance frameworks (SOC 2, HITRUST)
• Additional languages for performance or integration (Scala/Java/Go)