Join Optum, a global leader in health technology, and contribute to improving health outcomes for millions. We foster an inclusive culture with opportunities for professional growth and collaboration. Your work will directly impact health optimization worldwide.

Our team is dedicated to leveraging cutting-edge AI and ML to connect people with the care, resources, and pharmacy benefits they need. We emphasize collaboration, innovation, and making a real difference in the communities we serve.

This role is ideal for individuals passionate about advancing health through technology and eager to be part of a dynamic, mission-driven organization.

Experiment with novel ML and Generative AI architectures, and create/maintain robust embedding models. Support Retrieval Augmented Generation (RAG) solutions, integrating semantic search, vector databases, and LLMs.

Design and implement AI-powered enterprise applications, analyzing large datasets for actionable insights. Enhance existing models for improved accuracy and performance.

Optimize AI pipelines for scalability, performance, and cost-efficiency. Integrate AI/ML solutions into enterprise systems by collaborating closely with data engineering and product teams.

Communicate complex technical concepts clearly to cross-functional teams and stakeholders. Contribute to the skill development of engineers and interns in AI/LLM techniques.

A graduate degree or equivalent experience is required, preferably in Computer Science, Engineering, Mathematics, or Statistics. Possess 4+ years of relevant experience, with a strong background in ML model development.

Demonstrate hands-on expertise in Databricks, Spark, Python, Scala, and SQL. Proficiency in LLM & GenAI skills, including custom embedding models, RAG pipelines, vector databases, semantic search, and LangChain for agentic workflows.

Experience with OpenAI/Azure OpenAI APIs and Azure cloud for compute, security, and resource management is essential. Familiarity with CI/CD tools like Git, GitHub Actions, Jenkins, and Terraform is expected.

Exhibit a solid ability to build ML models end-to-end, from data preparation to evaluation. Proven excellent communication and partnership skills are critical for success in this role.