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

Job Title: Lead AI/ML Engineer - Hybrid ML Optimisation ,Gurobi, CPLEX Company: Optum India Job Category: Machine Learning Roles & Responsibilities: 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 solution results, trade\-offs, and business impact to technical and non\-technical stakeholders * Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re\-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so Technical Skills * Optimization: Mathematical optimization , Linear/Non\-linear Programming, Integer and Combinatorial optimization , Stochastic optimization , Robust optimization , Operations Research, Large\-Scale Decision Systems * Optimization Frameworks: Pyomo, OR\-Tools, Gurobi, CPLEX * Quantum and Quantum\-Inspired: Quantum optimization , QAOA, Quantum Annealing, Hybrid Quantum\-Classical Algorithms, Qiskit, Cirq, D\-Wave, Azure Quantum * AI/ML and Analytics: Machine Learning, Deep Learning, Statistical Modelling, Predictive Analytics, Prescriptive Analytics, Experimental Design * Hybrid ML \+ Optimization : Decision\-Focused Learning, Reinforcement Learning, Constrained optimization , Simulation\-Based optimization , Digital Twins * Generative and Agentic AI: Generative AI, LLMs, RAG, Prompt Engineering, Retrieval optimization , Constrained Generation, Agentic AI, Agentic Workflows, Orchestration Frameworks, Tool Integration * Programming and Data Engineering: Python, SQL, Feature Engineering, Data Pipelines, Model Evaluation, Experimentation Frameworks * MLOps and Model Lifecycle: MLOps, MLflow, Kubeflow, CI/CD, Model Monitoring, Observability, Drift Detection, Model Registry, Deployment Automation * Data Platforms: Databricks, Snowflake, BigQuery, Kafka, Lakehouse Architectures * Responsible AI and Governance: Responsible AI, Explainability, Fairness Constraints, AI Governance, Risk Management, SOC 2, HITRUST, HIPAA * Healthcare Analytics: Healthcare Analytics, Claims, Clinical Data, EHR/HL7/FHIR, ICD/CPT, Risk Adjustment, Population Health, Care Management * Leadership and Strategy: Technical Leadership, AI Strategy, optimization Strategy, Innovation, Stakeholder Management, Mentoring, Team Leadership, Cross\-Functional Collaboration Work Location: Bengaluru, Karnataka, India Availability: Full time

Required Qualifications * Bachelor's Degree in computer science , Mathematics, Engineering, Operations Research, Applied Mathematics, or related field; Master's degree preferred * 15\+ years of experience in applied AI/ML or optimization \-focused roles, with demonstrated leadership of enterprise\-scale AI and optimization initiatives * Proven experience leading complex optimization and AI initiatives from ideation through production deployment * Hands\-on experience with optimization frameworks, including Pyomo, OR\-Tools, Gurobi, and/or CPLEX * Hands\-on experience with ML/DL frameworks: PyTorch and/or TensorFlow * Hands\-on experience with Generative AI technologies including LLMs, RAG, prompt engineering, and optimization \-integrated generation frameworks * Experience developing Agentic AI solutions using orchestration frameworks and tool\-enabled workflows * Demonstrated experience with combinatorial optimization and large\-scale decision systems * Proven experience with hybrid ML and optimization approaches * Experience mentoring scientists and leading small technical teams * Solid foundation in mathematical optimization , operations research, and statistics * Solid expertise in machine learning, deep learning, statistical modelling, predictive analytics, and experimentation * Familiarity with quantum computing concepts or quantum\-inspired algorithms for optimization * Solid knowledge of MLOps, model governance, and production AI and optimization systems * Proven solid programming skills in Python, NumPy, pandas, scientific computing, and SQL * Proven solid communication, stakeholder management, and technical leadership skills At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone\-of every race, gender, sexuality, age, location and income\-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes \- an enterprise priority reflected in our mission. Key Skills: Machine Learning, Python, TensorFlow, PyTorch, Pandas, NumPy, Feature Engineering Salary: Not disclosed