Lead AI/ML Engineer - Hybrid ML Optimisation ,Gurobi, CPLEX

Requisition Number: 2393142

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.

We are seeking a highly experienced Lead AI/ML Engineer to lead the discovery, design, and adoption of advanced optimization and AI/ML solutions across mathematical programming, quantum-inspired methods, hybrid ML + optimization, and Generative AI domains.

This role serves as a senior technical leader responsible for driving optimization innovation, solving complex healthcare business problems, defining scalable solution strategies, and accelerating the transition of optimization solutions from experimentation to production.

Owns optimization strategy, architecture decisions, enterprise standards, reusable frameworks, capability development, and leadership of small teams while remaining deeply hands-on in solving critical business challenges.

Primary

Responsibilities

• Optimization Strategy and Technical Leadership
• Drive optimization and AI solution strategy for complex, high-impact healthcare business problems
• Lead technical design, solution architecture, and optimization technology selection decisions
• Establish reusable optimization patterns, solver frameworks, standards, and best practices across the organization
• Provide technical leadership and mentorship to AI/ML Engineers and cross-functional teams
• Evaluate emerging optimization , quantum, and AI technologies and recommend enterprise adoption approaches
• Influence enterprise AI and optimization strategy, architecture standards, and capability development
• Optimization and AI/ML Modelling
• Define the modelling strategy for complex business problems, setting the approach for mathematical optimization and AI/ML solution design across the enterprise
• Set strategic direction for advanced AI/ML and optimization model development across predictive, prescriptive, deep learning, and GenAI systems
• Own the formulation strategy for complex optimization problems, including linear and non-linear programming, integer and combinatorial optimization , and stochastic and robust optimization
• Lead the development of new modelling paradigms combining ML and optimization , including decision-focused learning, reinforcement learning, and constrained optimization
• Drive the enterprise strategy for GenAI and optimization integration, including retrieval optimization , prompt optimization , and constrained generation frameworks
• Architect scalable modelling frameworks that integrate optimization solvers with ML/AI systems for enterprise-wide deployment
• Champion quantum and quantum-inspired optimization methods, including QAOA, annealing approaches, and hybrid quantum-classical algorithms
• Applied Solution Development
• Design and develop POCs, prototypes, and reference implementations for optimization-driven use cases
• Build reusable assets including solver configurations, optimization workflows, evaluation frameworks, and implementation accelerators
• Define production-ready solution blueprints to support engineering adoption of optimization solutions
• Lead end-to-end lifecycle activities including problem formulation, modelling, solver selection, validation, deployment, monitoring, and continuous improvement
• Production Readiness and MLOps
• Drive successful transition of validated optimization solutions into production by partnering with engineering teams to ensure scalability, maintainability, and security
• Apply MLOps best practices including experiment tracking, solver versioning, CI/CD integration, performance monitoring, and observability
• Ensure operational readiness, model governance, and alignment with enterprise architecture standards
• Develop implementation-ready artefacts including reusable code, optimization pipelines, solver integration patterns, and technical documentation
• Research and Innovation
• Define the research agenda in optimization , operations research, and quantum computing, directing investigation into high-impact healthcare applications
• Lead evaluation and enterprise adoption decisions for emerging AI and optimization frameworks and technology stacks
• Lead and sponsor publication of research artefacts including white papers, patents, and internal frameworks
• Drive adoption of optimization accelerators, reusable frameworks, and best practices across teams
• Responsible AI and Compliance
• Establish evaluation, guardrail, and governance frameworks for optimization and AI solutions
• Ensure explain ability of optimization decisions, fairness constraints, and regulatory alignment with HIPAA/PHI, SOC 2, and HITRUST
• Apply responsible AI principles, bias mitigation, and AI governance frameworks throughout the solution lifecycle
• Collaborate with research, engineering, and product teams to translate cutting-edge AI advancements into production-ready capabilities Uphold ethical AI principles by embedding fairness, transparency, and accountability throughout the model development lifecycle
• Team and Organizational Impact
• Lead a small team of AI/ML Engineers while remaining deeply hands-on in optimization and AI solution development
• Mentor team members on optimization methodologies, mathematical modelling, experimentation practices, and technical excellence
• Promote knowledge sharing, innovation, and adoption of reusable optimization and AI capabilities
• Collaborate with business, product, architecture, and engineering teams to align solutions with measurable business outcomes
• Communicate s