Sr Manager AI/ML Engineering - Hybrid in MN or DC, remote elsewhere

Role

As a Senior Manager of AI/ML Engineering you will lead teams building and operating scalable ML platforms and production ML systems across the enterprise. You will architect ML and GenAI platforms, productionize models for batch and real-time inference, and establish MLOps/LLMOps pipelines and governance to support experimentation, deployment, monitoring, and lifecycle management.

Key Responsibilities

• Lead and scale AI/ML engineering teams responsible for ML platforms, model pipelines, and AI infrastructure.
• Architect enterprise ML and GenAI platforms for experimentation, training, evaluation, deployment, monitoring, and lifecycle management.
• Productionize machine learning and generative AI models with 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.
• Develop cloud-native ML infrastructure using Docker, Kubernetes, and cloud ML platforms (e.g., SageMaker, Azure ML, Vertex AI).
• Implement model monitoring and lifecycle management to track drift, latency, bias, and data quality and enable automated retraining.
• Ensure governance, security, lineage, auditability, reproducibility, and observability of ML systems.
• Partner with data scientists, data engineers, and software engineers to define production ML standards and scalable AI solutions.

Requirements

• 8+ years experience in machine learning engineering, MLOps, or AI platform engineering building production ML systems and scalable model pipelines.
• 5+ years experience with ML lifecycle platforms such as MLflow, Kubeflow, SageMaker, Azure ML, or GCP Vertex AI.
• 5+ years building cloud-native ML platforms using Docker, Kubernetes, and distributed systems.
• 6+ years programming in Python for ML systems with familiarity with frameworks such as PyTorch, TensorFlow, or scikit-learn.
• 5+ years working with distributed data processing and orchestration tools such as Spark, Ray, Airflow, Dagster, or Prefect.
• 1+ year experience using AI-assisted development or “vibe coding” tools such as Codex, Claude Code, Cursor, Windsurf, or similar.

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.

Location & Work Arrangement

• Remote from anywhere in the U.S.; hires in Minneapolis or Washington, D.C. are required to work in the office a minimum of four days per week (hybrid requirement).
• Telecommuter Policy applies for remote employees.

Compensation & Benefits

• Salary range: $112,700 to $193,200 annually (based on full-time employment).
• Comprehensive benefits package; incentive and recognition programs; equity stock purchase; 401(k) contribution; development and career growth opportunities.

Additional Notes

• Role emphasizes responsible AI, governance, security, and cross-functional collaboration across business units.
• UnitedHealth Group is an Equal Employment Opportunity employer and requires a drug test prior to employment when applicable.