Join Optum, a global leader in healthcare technology, and contribute to improving health outcomes for millions. Our team is dedicated to connecting individuals with the care, pharmacy benefits, and resources they need to thrive. You'll find an inclusive culture, collaborate with talented peers, and benefit from comprehensive development opportunities. Make a tangible impact as we advance health optimization worldwide. Start your journey with us in Caring, Connecting, and Growing together.

This role focuses on leveraging cutting-edge AI/ML to drive innovation within the healthcare sector. We are committed to equitable care and mitigating environmental impact, aligning with our core mission.

Key responsibilities include designing, developing, and deploying scalable AI/ML solutions tailored for the healthcare domain. This involves selecting and optimizing algorithms for various tasks like classification, regression, and anomaly detection. You will be instrumental in adopting and promoting standard AI development approaches, including deep learning, NLP, and computer vision models. Furthermore, you will build advanced solutions such as retrieval-augmented generation and agentic AI, integrating them with enterprise systems and ensuring human-in-the-loop controls for high-impact AI workflows. Developing robust data pipelines, MLOps/LLMOps, and secure cloud-based services using Python and containerization will be crucial. Effective communication of AI/ML strategies and results to diverse stakeholders is also a core expectation.

We are seeking candidates with a graduate degree or equivalent experience, holding a Bachelor's degree in a relevant field like Computer Science, Engineering, Data Science, or Statistics. A minimum of 4 years in software engineering or data science is required, with at least 2 years specifically in AI/ML engineering. Proficiency in Python, PySpark, and libraries such as Scikit-learn, TensorFlow, PyTorch, Pandas, and NumPy is essential. Experience with deep learning architectures, NLP, computer vision, and generative AI is a must. Hands-on experience with frameworks like LangGraph, LangChain, or AutoGen for agentic AI solutions, coupled with a strong understanding of MLOps/LLMOps practices, is vital. Familiarity with cloud platforms (Azure, AWS, GCP) and deploying production services using FastAPI, Docker, and Kubernetes is also necessary. Excellent analytical and problem-solving skills are paramount.