Join Optum, a global leader in healthcare technology, and drive the future of health optimization. This role offers the opportunity to shape AI/ML and optimization strategies, impacting millions. You'll work within an inclusive culture alongside talented peers, with comprehensive benefits and ample career development.

As a Lead AI/ML Engineer, you will spearhead the discovery, design, and implementation of advanced optimization and AI/ML solutions. Your expertise will be crucial in areas like mathematical programming, quantum-inspired methods, hybrid ML + optimization, and Generative AI.

This senior technical leadership position involves innovating optimization approaches, tackling complex healthcare challenges, and architecting scalable solutions. You will accelerate the transition of these solutions from concept to production, ensuring their enterprise-wide impact.

You will own the optimization strategy, making key architecture decisions and setting enterprise standards. This includes developing reusable frameworks and leading small teams while remaining hands-on with complex business challenges. Your responsibilities will span driving optimization and AI solution strategies for high-impact healthcare problems, leading technical design and architecture, and establishing best practices.

Define modeling strategies for complex business issues, encompassing mathematical optimization and AI/ML solution design. Lead the development of advanced models, including predictive, prescriptive, deep learning, and GenAI systems. You will also formulate complex optimization problems and drive the strategy for integrating GenAI with optimization frameworks.

Design and develop proofs of concept (POCs), prototypes, and reference implementations. Build reusable assets such as solver configurations and optimization workflows. Lead the end-to-end lifecycle, from problem formulation to continuous improvement, and ensure successful transition of validated solutions into production by partnering with engineering teams.

A Bachelor's Degree in a relevant field such as Computer Science, Mathematics, or Engineering is required, with a Master's degree being preferred. You should possess at least 15 years of experience in applied AI/ML or optimization roles, with a proven track record of leading enterprise-scale initiatives.

Demonstrated experience in leading complex optimization and AI projects from inception to deployment is essential. Hands-on experience with optimization frameworks like Pyomo, Gurobi, or CPLEX, and ML/DL frameworks such as PyTorch or TensorFlow is critical. Familiarity with Generative AI technologies, including LLMs and RAG, is also expected.

Solid programming skills in Python, NumPy, pandas, and scientific computing are necessary, alongside strong communication and stakeholder management abilities. A firm understanding of mathematical optimization, operations research, and machine learning fundamentals is a must. Familiarity with MLOps, model governance, and production AI/optimization systems is also required.