Senior AI/ML Engineer Office Based

UnitedHealth Group•Eden Prairie, MN

12d•$120,100 - $214,500•Onsite

About The Position

As a Senior AI/ML Engineer within Optum Technology, you will drive enterprise-scale artificial intelligence and machine learning innovations. You will collaborate with data scientists, data engineers, and software architects to design, build, and optimize AI/ML solutions and Generative AI capabilities. Using modern cloud environments, Databricks, large language models, and MLOps practices, you will translate complex business challenges into scalable, reliable, production-ready AI systems that advance healthcare quality and operational excellence. The role emphasizes responsible AI and enterprise engineering practices.

Requirements

Bachelor’s degree or equivalent experience.
7+ years of software engineering or data engineering experience.
3+ years focused specifically on AI/ML solution engineering and operational deployment.
3+ years of experience with Python, SQL, data structures, algorithms, and enterprise software engineering practices.
3+ years of hands-on experience with ML frameworks such as scikit-learn, PyTorch, or TensorFlow.
3+ years of experience building scalable data processing solutions using Databricks, Spark, or PySpark on cloud platforms such as Azure, AWS, or GCP.
3+ years of hands-on MLOps experience, including model versioning, CI/CD pipelines, automated testing, production monitoring, drift management, and observability.
3+ years of experience building and deploying APIs, microservices, and containerized applications using Docker and Kubernetes, and using Git version control practices.
2+ years of hands-on experience developing Generative AI and LLM solutions, including RAG, embeddings, vector search, prompt engineering, and agentic workflows.

Nice To Haves

Master’s degree in Computer Science, Data Science, AI/ML, Engineering, Statistics, Mathematics, or a related field.
Demonstrated experience taking ML/AI solutions from prototype through production deployment and operational support at enterprise scale.
Experience establishing reusable engineering patterns and development standards across cross-functional technology teams.
Proven ability to evaluate technical trade-offs involving model quality, scalability, cost, security, and maintainability in cloud-native environments.

Responsibilities

Design, develop, and deploy AI-powered solutions for complex business challenges, emphasizing responsible AI use.
Use enterprise-approved AI tools and software engineering best practices to streamline workflows, automate tasks, and drive continuous improvement.
Evaluate emerging technology trends to inform solution design, architectural strategy, and innovation across enterprise platforms.
Independently design end-to-end AI/ML architectures and translate ambiguous business problems into scalable, production-ready AI use cases.
Implement MLOps practices, CI/CD pipelines, and automated testing for model versioning, deployment, monitoring, drift management, and observability.
Establish reusable engineering patterns, architectural standards, and development workflows to accelerate enterprise-scale AI adoption.
Make technical trade-offs involving model quality, scalability, performance, cost, security, and maintainability across cloud and containerized environments.
Lead technical design reviews and mentor engineers while partnering with data scientists, data engineers, product teams, security, and operations.