Senior AI/ML Engineer

Requisition Number: 2391432

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.

Primary Responsibility

• 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

Required

Qualifications

• Bachelor's degree in Computer Science, Mathematics, Engineering, Operations Research, Applied Mathematics, or related field
• 10+ years of experience in applied AI/ML or optimization-focused roles, with solid ownership of enterprise-scale AI and optimization initiatives
• Proven experience translating business challenges into effective optimization and AI/ML solution strategies and production-ready solution architectures
• 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
• Experience with combinatorial optimization and large-scale decision systems
• Demonstrated experience with hybrid ML and optimization approaches
• Solid foundation in:
• Mathematical optimization, operations research, and statistics
• Machine learning, deep learning, and experimental design
• Demonstrated experience designing, developing, validating, and delivering successful optimization and AI proof-of-concepts that progressed into large-scale production environments
• Familiarity with quantum computing concepts or quantum-inspired algorithms for optimization
• Familiarity with MLOps practices including experiment tracking, benchmarking, model versioning, and deployment automation
• Proven ability to translate theoretical models into impactful, real-world solutions
• Proven ability to collaborate effectively with engineering organizations to enable successful production adoption of AI and optimization solutions
• Proven ability to collaborate effectively across business, product, engineering, and leadership teams
• Proven solid programming skills in Python (NumPy, pandas, scientific computing) and SQL
• Proven solid analytical, problem-solving, communication, solution design, and stakeholder management skills

Preferred

Qualifications

• MS/PhD
• 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
• Experience integrating optimization into production systems in collaboration with engineering teams
• Experience building enterprise-scale Generative AI solutions integrated with optimization pipelines
• Experience mentoring teams and driving AI capability development across organizations
• Experience with Big data platforms (Databricks, Snowflake, BigQuery) and streaming (Kafka); lakehouse patterns
• Experience with MLOps stack: MLflow, SageMaker, Azure ML, or Vertex AI; model monitoring, observability, automated retraining, and deployment automation
• Experience with Publications or patents in optimization, ML, or quantum computing; contributions to internal frameworks, accelerators, or enterprise AI innovation initiatives
• Healthcare domain expertise including claims, EHR/HL7/FHIR, care pathways, resource planning, ICD/CPT coding, risk adjustment, quality measures, and de-identification
• Knowledge of Responsible AI in constrained decision-making systems
• Knowledge of security and compliance frameworks (SOC 2, HITRUST, HIPAA)

Technical Skills

• Optimization - Mathematical Optimization, Linear/Non-linear Programming, Integer and Combinatorial Optimisation, Stochastic Optimization, Robust Optimization, Operations Research, Large-Scale Decision Systems
• Optimization Frameworks - Pyomo, OR-Tools, Gurobi, CPLEX
• Quantum and Quantum-Inspired - Quantum Optimisation, 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 + Optimisation - Decision-Focused Learning, Reinforcement Learning, Constrained Optimisation, Simulation-Based Optimisation, Digital Twins
• Generative and Agentic AI - Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Prompt Engineering, Retrieval Optimisation, Constrained Generation
• AI Frameworks - PyTorch, TensorFlow
• Programming and Data Engineering - Python (NumPy, pandas, SciPy), 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, Po