Sr Manager AI/ML Engineering Unitedhealth Group

Skills / Requirements

• AI Platform Engineering
• Airflow
• Azure ML
• Codex
• Dagster
• Docker
• GCP Vertex AI
• Kubeflow
• Kubernetes
• Machine Learning
• MLflow
• MLOps
• Prefect
• Python
• PyTorch
• Ray
• SageMaker
• scikit-learn
• Spark
• TensorFlow
• Vibe Coding

Why Apply

This role is ideal for someone skilled in MLOps and cloud-based ML platforms, leveraging AI-assisted development tools like Codex and Claude Code. You'll lead teams in building AI infrastructure for real-time and batch inference.

What You'll Be Doing

Lead and scale teams to build and operate machine learning platforms and production systems. Design ML infrastructure, manage model lifecycles, and ensure governance and compliance. Collaborate with cross-functional teams to define AI solutions.

Pay and Career Growth

The role offers a competitive salary range between $148,900 and $255,300. UnitedHealth Group provides a comprehensive benefits package, including stock purchase options and 401k contributions. The company values performance and offers clear career development paths.

Benefits and Perks

• 401k contribution
• Comprehensive Benefits
• equity stock purchase
• incentive programs

Is This Role Right for You?

Original Job Description

Requisition number: 2371824

Job category: Technology

Transform Healthcare Through AI Innovation at Optum

Optum Tech is a global leader in health care innovation. Our teams develop cutting-edge solutions that help people live healthier lives and help make the health system work better for everyone. From advanced data analytics and AI to cybersecurity, we use innovative approaches to solve some of health care’s most complex challenges. Your contributions here have the potential to change lives. Ready to build the next breakthrough? Join us to start Caring. Connecting. Growing together.

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. In addition to transforming the healthcare journey through responsible AI/ML innovation, our charter also includes developing and supporting an enterprise AI/ML development platform.

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.

At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes – an enterprise priority reflected in our mission.

UnitedHealth Group is an Equal Employment Opportunity employer under applicable law and qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations.

UnitedHealth Group is a drug – free workplace. Candidates are required to pass a drug test before beginning employment.

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