Sr. AI/ML Engineer - Remote

UnitedHealth Group•Schaumburg, IL

1d•$120,100 - $214,500•Remote

About The Position

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. As a Sr AI/ML Engineer within Optum Rx, you will contribute to the design, development, and scaling of advanced machine learning systems and artificial intelligence solutions that directly impact pharmacy benefits, patient care, and clinical workflows. You will serve as a senior technical engineer for complex AI/ML initiatives, designing conversational virtual assistants and driving modern engineering practices across cross-functional teams. This role collaborates with enterprise architecture, capability teams, and vendors to architect robust, secure, and scalable solutions for our core conversational chatbot platform utilized by both internal and external stakeholders. 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.

Requirements

Bachelor’s degree or equivalent experience; 4+ years of software engineering experience may substitute for a degree
4+ years of professional software engineering experience using Python, Java, Scala, or similar programming languages
2+ years of experience designing, training, and deploying machine learning or deep learning models into production systems
2+ years of experience building and managing MLOps frameworks, continuous integration/continuous deployment (CI/CD) pipelines, and containerized deployments (e.g., Docker, Kubernetes)
2+ years of experience writing SQL and working with relational or non-relational database systems (such as MongoDB)

Nice To Haves

Master’s or PhD degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field
Experience architecting, designing, and maintaining solution/network architecture diagrams for conversational chatbot solutions, virtual assistants, or natural language processing (NLP) applications
Experience collaborating with enterprise architecture teams and participating in technical design discussions with cloud and platform vendors (e.g., Microsoft, Palantir, MongoDB)
Experience with Large Language Models (LLMs), prompt engineering, fine-tuning, and retrieval-augmented generation (RAG)
Proven understanding of data privacy, model governance, and ethical AI practices within the healthcare sector
Excellent communication and collaborative problem-solving skills, with a proven ability to support technical initiatives and mentor team members

Responsibilities

Contribute to the design, development, and production deployment of AI/ML solutions, translating models and algorithms into scalable, secure, and reliable software used in enterprise systems
Serve as a senior technical engineer for complex AI/ML initiatives, owning end-to-end implementation from design through deployment and operational support
Leverage enterprise-approved AI tools to streamline workflows, automate tasks, and drive continuous improvement across teams
Apply advanced knowledge of machine learning, deep learning, statistics, and experimental methodologies to build high-quality, data-driven solutions
Partner closely with product, business, and engineering stakeholders to identify high-value use cases and deliver AI solutions that solve real Optum Rx business problems
Collaborate on AI solution architecture and design with Enterprise Architecture, core capability teams, and major platform vendors (including Microsoft, Palantir, and MongoDB) for core conversational chatbot platforms
Maintain solution architecture and network architecture diagrams for conversational chatbot platforms utilized by internal and external stakeholders
Drive modern engineering practices across teams, including automation-first development, code reuse, observability, and CI/CD adoption for AI systems
Champion MLOps best practices, ensuring models and pipelines are production-ready, monitored, and continuously improved
Evaluate emerging trends to inform solution design, optimize architecture, and drive strategic enterprise innovation