Optum AI is looking to solve business problems focused on improving patient engagement, predicting progression of disease, supporting novel designs of clinical trials using both structured and unstructured (text) data, and optimizing claims processing by designing, implementing, and scaling AI systems for health applications.
Requirements
- Experience using in cloud platforms and services (Azure, AWS, GCP, etc.)
- Proficiency in AI/ML engineering development with Python
- Demonstrated experience leading and implementing AI/ML projects from ideation to evaluation, delivery, and monitoring
- Experience with AI Cloud services like Azure ML, Databricks, Azure OpenAI, or similar services in GCP / AWS
- Expertise in Large Language Modeling and Transformer Architectures with experience in prompt engineering, evaluation, and LLM optimization
- Proven working knowledge of software development tools and practices including DevOps and CI/CD tools (Git, Docker, Kubernetes, etc.)
- Experience implementing agent architectures that can plan, call tools/APIs, interact with retrieval systems, and handle multistep clinical workflows
Responsibilities
- Process and transform source data to be used in machine learning pipelines, leveraging distributed computing environments and parallel processing approaches.
- Build robust training and evaluation pipelines using Python, PyTorch/TensorFlow, and modern ML tooling
- Follow best practices for software development (tests, packaging, GitHub, code review)
- Stay up-to-date with latest AI/ML technologies and research
- Publish findings in top tier AI and ML venues (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, CHIL, etc.) and present internally to Optum AI and business leaders
- Develop evaluation protocols, diagnostics, and documentation to support model governance and regulatory requirements
- Establish best practices for end-to-end machine learning, deep learning and GenAI development cycles to ensure rigor in process and quality in outcome
Other
- Collaborate with cross-functional teams to determine applicability of AI to business problems
- Communicate clearly with cross functional teams and stakeholders through written documents, technical talks, and presentations
- Closely collaborate with the Responsible Use of AI (RUAI) team to ensure that the delivered solutions are compliant with the company policies and standards.
- Mentorship and leadership of project team members
- Proven exceptional verbal and written communication skills to lead/mentor project teams, as well as to communicate technical content and analytical insights/complex findings in a clear and concise manner to multiple audiences, including senior management
