Senior AI/ML Engineer - MLOps & Production AI Systems - Remote or Hybrid in MN/DC

About the role

Join us to start Caring. Connecting. Growing together. As part of Optum AI, UnitedHealth Group's enterprise AI organization, you will build and scale production-grade machine learning and generative AI systems that directly impact patient outcomes, clinical efficiency, and enterprise automation.

Primary Responsibilities

• Design, build, and maintain end-to-end ML platforms and pipelines (training, validation, deployment, and monitoring)
• Productionize ML models using batch and real-time inference architectures (APIs, streaming, event-driven systems)
• Develop and manage ML lifecycle workflows using tools such as MLflow, Kubeflow, SageMaker, or Azure ML
• Build and maintain CI/CD pipelines for ML (CI/CT/CD), including automated testing, validation, and model promotion
• Containerize and deploy ML workloads using Docker and Kubernetes, ensuring scalability and reliability
• Implement infrastructure-as-code (Terraform or equivalent) for reproducible and secure ML environments
• Develop monitoring and observability solutions for model performance, drift, latency, and data quality
• Automate retraining and redeployment workflows based on performance degradation or new data availability
• Partner with cross-functional teams to define and enforce ML engineering standards and best practices
• Ensure compliance with enterprise governance, security, and Responsible AI requirements

Required Qualifications

• Bachelor's degree in Computer Science, Engineering, or related field OR 4+ years of equivalent experience
• 5+ years of experience in ML Engineering / MLOps with production deployment of machine learning systems
• 3+ years of experience with ML lifecycle tools (MLflow, Kubeflow, SageMaker, Azure ML, or similar)
• 3+ years of experience with Docker and Kubernetes in production environments
• 3+ years of experience building CI/CD pipelines for ML using Git-based workflows and automation tools
• 2+ years of experience with cloud platforms (AWS, Azure, or GCP) for ML workloads
• Experience with real-time and batch inference systems (e.g., Kafka, Kinesis, Event Hubs)
• Solid programming experience in Python (5+ years) with ML frameworks (PyTorch, TensorFlow, or scikit-learn)

Preferred Qualifications

• 7+ years of experience in ML engineering or distributed systems
• Hands-on experience with distributed data processing frameworks (Spark, Ray)
• Experience with workflow orchestration tools (Airflow, Dagster, Prefect)
• Experience with multi-cloud or hybrid cloud ML deployments
• Knowledge of Responsible AI, bias detection, and model explainability techniques
• Familiarity with observability tools (Prometheus, Grafana, OpenTelemetry)
• Proven contributions to open-source ML or MLOps projects

Pay and Benefits

Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements).

The salary for this role will range from $91,700 to $163,700 annually based on full-time employment. We comply with all minimum wage laws as applicable.