Join Optum, a global leader in health optimization, and leverage cutting-edge technology to make a significant impact on millions of lives. Our mission is to connect individuals with the care, resources, and data they need to thrive.

At Optum, you'll find an inclusive culture with talented colleagues, comprehensive benefits, and ample opportunities for career growth. Become part of a team dedicated to advancing health globally and fostering a healthier future for all communities.

We are committed to equitable care, addressing health disparities, and mitigating our environmental impact, reflecting our core mission to help people live healthier lives and improve the health system for everyone.

As an AI/ML Engineer, you will be instrumental in developing and implementing advanced AI and Machine Learning solutions. This includes designing and deploying enterprise-level agentic solutions and integrating generative AI capabilities like LLMs and RAG architectures.

You will be responsible for implementing real-world projects involving fine-tuning LLMs and utilizing vector databases for efficient data handling. The role also involves creating structured outputs from Document AI and OCR solutions, ensuring seamless data extraction and processing.

Your contributions will extend to exploring and implementing various machine learning techniques, staying abreast of NLP advancements, and leveraging cloud environments like Azure, AWS, and GCP for development and deployment. Familiarity with UI tools and API development is key to presenting and integrating these solutions effectively.

We are seeking a highly skilled AI/ML Engineer with a Bachelor's degree or higher in Computer Science or Engineering and a minimum of 5 years of experience in AI/ML roles.

Essential expertise includes implementing Gen AI, fine-tuning LLMs, and applying RAG. Proficiency in building enterprise agentic solutions using frameworks like Langgraph, Google ADK, or CrewAI is required.

Candidates must possess experience with vector databases/embeddings, Document AI/OCR, and structured output creation. A strong understanding of both open-source and OpenAI LLMs, along with RAG architecture, is crucial.

Demonstrated experience with machine learning techniques (supervised, unsupervised, reinforcement learning, deep learning, NLP) and familiarity with NLP literature are expected. Proficiency in Python, PyTorch, SQL, FAST APIs, REST APIs, and Docker, coupled with experience in cloud environments (Azure, AWS, GCP), is mandatory. Excellent analytical and problem-solving skills are essential for success in this role.