Join a leading health services organization as a Senior AI/ML Engineer, focusing on Optimization and Operations Research. This senior technical leadership role is pivotal in driving innovation in advanced AI/ML solutions, encompassing mathematical programming, quantum-inspired methods, hybrid ML and optimization, and Generative AI.

You will be instrumental in solving complex healthcare business challenges, architecting scalable solutions, and accelerating the transition of these solutions from experimentation to production. This position requires a deep, hands-on engagement with critical business problems while owning the optimization strategy, architecture decisions, enterprise standards, and capability development.

This is an opportunity to shape the future of AI and optimization within a company dedicated to improving the health system for everyone.

Spearhead the optimization and AI solution strategy for high-impact healthcare challenges. Lead technical design, solution architecture, and technology selection. Establish reusable optimization patterns, solver frameworks, and best practices. Mentor AI/ML Engineers and cross-functional teams. Evaluate emerging technologies and influence enterprise strategy.

Define modelling strategies for complex business problems, including advanced AI/ML and optimization model development. Own the formulation strategy for complex optimization problems, leading the development of new paradigms combining ML and optimization, and driving Generative AI integration. Architect scalable frameworks that integrate solvers with AI/ML systems and champion quantum-inspired optimization methods.

Possess a Bachelor's degree in a relevant technical field; a Master's degree is preferred. Bring 9+ years of experience in applied AI/ML or optimization roles, with a proven track record of leading enterprise-scale initiatives from ideation to production. A strong foundation in mathematical optimization, operations research, statistics, and machine learning is essential.

Demonstrate hands-on expertise with optimization frameworks (Pyomo, OR-Tools, Gurobi, CPLEX) and ML/DL frameworks (PyTorch, TensorFlow). Experience with Generative AI technologies (LLMs, RAG, prompt engineering) and Agentic AI solutions is required. Proficiency in Python, NumPy, pandas, scientific computing, and SQL, along with strong knowledge of MLOps, model governance, and production AI systems, is crucial. Excellent communication, stakeholder management, and technical leadership skills are expected. Experience mentoring scientists and leading small technical teams is also a key requirement.