Sr AI/ML Engineer Remote Nationwide or Office-Based in MN/DC

UnitedHealth Group•Minnetonka, MN

12d•$120,100 - $214,500•Hybrid

About The Position

As a Senior AI/ML Engineer within the Optum Tech UHC Technology team supporting UHC Medicare & Retirement, you will play a key role in designing, building, and scaling artificial intelligence and machine learning solutions that transform the healthcare experience for millions of Medicare-eligible individuals. You will collaborate with cross-functional teams to engineer innovative AI models, automate complex workflows, and deploy robust MLOps pipelines. By leveraging modern machine learning frameworks and cloud platforms, you will tackle high-impact business challenges and directly contribute to advancing health equity and operational excellence. You’ll enjoy the flexibility to work remotely from anywhere within the U.S. as you take on some tough challenges. This position follows a Office-Based schedule with four in-office days per week.

Requirements

5+ years of professional experience in software engineering, data science, or AI/ML engineering
3+ years of experience designing, training, and deploying machine learning models into production environments
3+ years of hands-on experience programming in Python and utilizing standard ML libraries/frameworks (e.g., TensorFlow, PyTorch, scikit-learn, XGBoost)
2+ years of experience with MLOps practices, automated model deployment, and monitoring
2+ years of experience working with cloud infrastructure (e.g., AWS, Azure, GCP) for scalable machine learning workflows
2+ years of experience with relational or non-relational database management and SQL

Nice To Haves

Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related technical field
Experience with Large Language Models (LLMs), generative AI architectures, prompt engineering, or model fine-tuning
Experience building AI/ML solutions within healthcare, health insurance, or Medicare & Retirement domain applications
Experience with containerization technologies (e.g., Docker, Kubernetes) and CI/CD tools
Familiarity with enterprise AI governance, model fairness, and healthcare data security standards (e.g., HIPAA)

Responsibilities

Design, develop, and deploy AI-powered solutions to address complex business challenges with emphasis on responsible use of AI
Use enterprise-approved AI tools to streamline workflows, automate tasks, and drive continuous improvement
Evaluate emerging trends and technologies in artificial intelligence and machine learning to inform solution design and strategic innovation
Build, train, tune, and operationalize end-to-end machine learning models and AI services for enterprise-scale healthcare applications
Establish scalable MLOps frameworks, automated deployment pipelines, and continuous model monitoring practices
Collaborate with cross-functional teams including software engineers, data scientists, and business partners to integrate AI capabilities into production applications
Ensure AI/ML models meet performance, scalability, security, and ethical governance standards