Optum, a global leader in health optimization, is seeking a Senior AI/ML Engineer to drive innovation in healthcare delivery. This role is pivotal in transforming pharmacy benefit operations and patient care through advanced AI and machine learning solutions.

Our team is dedicated to enhancing health outcomes by connecting individuals with the care and resources they need. We foster an inclusive culture with opportunities for professional growth and comprehensive benefits. Join us in advancing health optimization on a global scale.

As a Sr AI/ML Engineer, you will architect, develop, and deploy cutting-edge AI/ML solutions. You will leverage predictive modeling, NLP, and scalable AI platforms to improve medication adherence and ensure accessible healthcare for millions. This is an opportunity to tackle complex healthcare challenges using modern cloud architectures and enterprise ML pipelines.

Design and deploy scalable AI solutions, including generative AI applications for tasks like summarization and knowledge retrieval. Develop and optimize LLMs using advanced techniques such as prompt engineering and fine-tuning. Build and automate end-to-end MLOps pipelines for seamless model deployment and lifecycle management. Integrate AI/ML capabilities into enterprise applications and workflows using cloud platforms. Implement vector search and agentic AI solutions for context-aware user experiences. Establish robust AI governance, evaluation, and quality assurance practices. Monitor and optimize AI systems for performance, scalability, and cost efficiency. Evaluate emerging AI technologies to drive innovation and strategic technology adoption. Collaborate with stakeholders to translate requirements into scalable, secure AI solutions.

Possess an advanced degree in Computer Science, Data Science, Engineering, or a related quantitative field. Have 7+ years of experience in software or machine learning engineering, developing and deploying production-grade AI/ML systems. Demonstrate hands-on experience with generative AI applications, LLMs, or RAG architectures. Proficient in Python and SQL, with practical experience in core ML frameworks. Experience with containerization, orchestration, and CI/CD tools (e.g., Docker, Kubernetes). Proven ability to build end-to-end ML pipelines and MLOps workflows in cloud environments. Familiarity with healthcare data, clinical workflows, or pharmacy benefit management systems is beneficial. Apply responsible AI principles, data governance, and rigorous model evaluation techniques.