As a Senior Manager of AI/ML Engineering, you will lead teams responsible for building and operating scalable machine learning platforms and production ML systems across the enterprise. You will drive the design and implementation of ML infrastructure, model lifecycle management systems, and MLOps platforms that enable reliable experimentation, deployment, monitoring, and governance of machine learning and generative AI models. This role requires solid technical leadership, deep experience in MLOps and cloud-based ML platforms, and the ability to collaborate closely with data science, engineering, and platform teams.
You'll enjoy the flexibility to work remotely * from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week.
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
- Develop 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
You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.
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
*All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy.
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). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $148,900 to $255,300 annually based on full-time employment. We comply with all minimum wage laws as applicable.
Application Deadline: This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants.
