ML Optimization Engineer

Optum; Dadri, Hyderabad, Bengaluru; Hybrid; INR 4,000,000 - 7,000,000; Full time

Job summary

Optum is seeking a senior AI/optimization leader to drive enterprise-scale AI and optimization initiatives across health care domains. You will ideate, design, and deploy solutions that blend ML, optimization, and data analytics to improve outcomes

You will mentor scientists and manage small teams, collaborate with engineering and product partners, and uphold governance and responsible AI practices while delivering measurable impact at scale.

Qualifications

• 10+ years in applied AI/ML or optimization roles with enterprise-scale leadership.
• Proven experience delivering AI/optimization from ideation through production.
• Strong foundation in mathematical optimization, operations research, and statistics.
• Experience with hybrid ML and optimization approaches.
• Mentoring scientists and leading small technical teams.
• Familiarity with quantum computing concepts or quantum-inspired algorithms for optimization.
• Solid knowledge of MLOps, model governance, and production AI/optimization systems.

Responsibilities

• Lead enterprise-scale AI and optimization initiatives.
• Mentor scientists and small teams.
• Collaborate with engineering and product partners for deployment.
• Develop and evaluate advanced optimization models and experiments.
• Ensure governance and responsible AI practices.

Skills

Leadership

Communication

Mentoring

Stakeholder mgmt

Team leadership

Cross-functional

Technical leadership

Problem solving

Tools

Pyomo

OR-Tools

Gurobi

CPLEX

PyTorch

TensorFlow

Qiskit

Cirq

D-Wave

Azure Quantum

Databricks

Snowflake

BigQuery

Kafka

MLflow

Sagemaker

Vertex AI

Job description

Required Qualifications:

• 10+ 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

Preferred Qualifications:

• Experience with quantum frameworks such as Qiskit, Cirq, D-Wave, or Azure Quantum
• Experience with reinforcement learning for decision optimization
• Experience with simulation-based optimization and digital twins
• Healthcare domain expertise including claims, EHR/HL7/FHIR, care pathways, resource planning, ICD/CPT coding, risk adjustment, quality measures, and de-identification
• Experience with publications or patents in optimization, ML, or quantum computing; contributions to internal frameworks, accelerators, or enterprise AI innovation initiatives
• Experience integrating optimization into production systems in collaboration with engineering teams
• Experience establishing Responsible AI, governance, risk management, and compliance frameworks for constrained optimization and decision-making systems
• Experience building enterprise-scale Generative AI solutions integrated with optimization pipelines
• Experience with Big data platforms including Databricks, Snowflake, BigQuery, and Kafka; lakehouse patterns
• Experience with MLOps stack including MLflow, Sagemaker, Azure ML, or Vertex AI; model monitoring, observability, automated retraining, and deployment automation
• Experience designing enterprise AI platforms, optimization solver services, and reusable ML frameworks
• Experience mentoring teams and driving AI and optimization capability development across optimization
• Knowledge of security and compliance frameworks including SOC 2, HITRUST, and HIPAA

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