Sr Manager AI/ML Engineering

About the role

Optum AI is UnitedHealth Group's enterprise AI team. We are AI/ML scientists and engineers with deep expertise in AI/ML engineering for healthcare. We develop AI/ML solutions for the highest impact opportunities across UnitedHealth Group businesses including UnitedHealthcare, Optum Financial, Optum Health, Optum Insight, and Optum Rx.

Primary Responsibilities

• Lead and scale AI/ML engineering teams responsible for building ML platforms, model pipelines, and scalable AI infrastructure
• Architect enterprise ML and GenAI platforms supporting experimentation, model training, evaluation, deployment, monitoring, and lifecycle management
• Productionize machine learning and generative AI models using batch and real-time inference architectures
• Build and operate MLOps and LLMOps pipelines including CI/CT/CD workflows for model testing, validation, versioning, and promotion across environments
• Implement scalable cloud-native ML infrastructure using Docker, Kubernetes, and cloud ML platforms such as AWS SageMaker, Azure ML, or GCP Vertex AI
• Implement model monitoring and lifecycle management systems to track drift, latency, bias, and data quality while enabling automated retraining
• Ensure governance, security, and compliance of ML systems including lineage, auditability, reproducibility, and observability
• Partner with data scientists, data engineers, and software engineers to define production ML standards and scalable AI solutions

Required Qualifications

• 8+ years of experience in machine learning engineering, MLOps, or AI platform engineering building production ML systems and scalable model pipelines
• 6+ years of experience programming in Python for ML systems with familiarity with frameworks such as PyTorch, TensorFlow, or scikit-learn
• 5+ years of experience working with ML lifecycle platforms such as MLflow, Kubeflow, SageMaker, Azure ML, or GCP Vertex AI
• 5+ years of experience building cloud-native ML platforms using Docker, Kubernetes, and distributed systems
• 5+ years of experience working with distributed data processing and orchestration tools such as Spark, Ray, Airflow, Dagster, or Prefect
• 1+ year of experience using AI-assisted development or 'vibe coding' tools such as Codex, Claude Code, Cursor, Windsurf, or similar tools
• 1+ year of experience in Healthcare
• Must be authorized to work in the United States without the need for current or future employer-sponsored visa sponsorship (e.g., H-1B, TN, F-1/OPT, CPT, or other employment-based visa status)

Preferred Qualifications

• Master's degree in Computer Science, Engineering, Data Science, or related discipline
• Experience building low-latency inference systems and online feature serving architectures
• Experience implementing Responsible AI practices including bias detection and model explainability
• Experience operating multi-cloud or hybrid ML platforms
• Contributions to open-source ML or MLOps tooling