Senior AI or ML Applied Scientist

Optum India; Bengaluru; On-site; INR 2,500,000 - 5,000,000; Full time

Job summary

UnitedHealth Group, via Optum, seeks an experienced ML Engineer/Scientist to own end-to-end model development for CPT/HCPCS prediction and patient navigation initiatives. You will design, train, evaluate, and deploy models using healthcare data, while applying deep learning and generative AI where appropriate.

The role emphasizes production-grade Python, collaboration with cross-functional teams, and responsible AI practices, with opportunities to influence governance and model deployment in

Qualifications

• Bachelor's, Master's, or PhD in CS/AI/ML/DS/Statistics or related quantitative field.
• 5+ years of applied ML experience delivering real business outcomes.
• Hands-on experience with generative AI or LLMs.
• Practical experience with PyTorch or TensorFlow.
• Production deployment experience for models via APIs.
• Strong Python programming and production-grade code.
• Solid ML fundamentals: tree-based and gradient-boosted methods.
• Ability to communicate modeling decisions clearly.

Responsibilities

• Design, build, and evaluate ML models using healthcare data.
• Own components of the model lifecycle end-to-end.
• Write production-quality Python for data processing and inference.
• Apply deep learning and transformer methods where beneficial.
• Build generative AI and LLM-based components.
• Deploy models as production services or APIs with MLOps teams.
• Design experiments with metrics, baselines, validation, and communicate results.
• Collaborate with product managers and data engineers to translate requirements.
• Contribute to model documentation, responsible AI practices, governance readiness.
• Collaborate with research and engineering to translate AI advances into production.
• Uphold ethical AI by embedding fairness, transparency, and accountability.

Skills

Applied machine learning

Python

Deep learning

PyTorch

Model deployment

Communication

Education

Bachelor's/Master's/PhD in CS/AI/ML/DS/Statistics

Tools

PyTorch

TensorFlow

Job description

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.

This role supports the Optum Real Pre-Care CPT Predictor and Digital Front Door (DFD) initiatives, which deliver AI-driven capabilities for CPT/HCPCS prediction, healthcare intent understanding, and patient navigation. citeturn1search1 The work directly supports business objectives of improving patient estimate accuracy, streamlining prior authorization workflows, and reducing downstream claim denials. citeturn1search1

You will own meaningful pieces of the model lifecycle end to end: framing the problem with stakeholders, exploring and engineering features from healthcare data, training and evaluating models, and carrying them through to a deployed, monitored production service. This is a hands‑on applied science role for someone who writes solid Python, is grounded in classical machine learning, has practical exposure to deep learning and generative AI, and has seen their own work run in production rather than stop at a notebook.

Primary Responsibilities

• Design, build, and evaluate machine learning models for prediction and classification problems using healthcare claims, clinical, and registration data
• Own assigned components of the model lifecycle end to end, from data exploration and feature engineering through training, evaluation, deployment, and post-production monitoring
• Write production-quality Python for data processing, model training, and inference, following sound software engineering practices including version control, testing, and code review
• Apply deep learning and transformer‑based approaches where they outperform classical methods, and justify model selection with rigorous experimentation
• Build and evaluate generative AI and LLM‑based components, including prompting, fine‑tuning, and retrieval‑augmented approaches, for applicable use cases
• Deploy models as production services or APIs in partnership with MLOps and engineering teams, and support them post‑release
• Design and run experiments with clear evaluation metrics, baselines, and validation strategy, and communicate results and trade‑offs clearly to technical and non‑technical audiences
• Partner with product managers, data engineers, and business stakeholders to translate requirements into well‑scoped modeling problems
• Contribute to model documentation, responsible AI practices, and AIRB and governance readiness for production deployment
• Scientist Responsibilities:
  • 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
• 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, Master's, or PhD in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Statistics, or a related quantitative field
• 5+ years of applied machine learning experience building models that solve real business problems
• Hands‑on exposure to generative AI or LLMs, including prompting, fine‑tuning, or embedding and retrieval‑based approaches
• Practical experience with deep learning frameworks such as PyTorch or TensorFlow
• Demonstrated experience taking at least one model or system into production as a deployed service or API, and supporting it thereafter
• Solid Python programming skills, including experience writing maintainable, production‑grade code rather than exploratory scripts alone
• Solid foundation in classical machine learning, including tree‑based and gradient‑boosted methods, with sound understanding of feature engineering, model evaluation, and validation methodology
• Proven ability to communicate modeling decisions, assumptions, and results clearly to cross‑functional partners

Preferred Qualifications

• Experience with healthcare data such as claims, HL7, EHR, or medical coding systems including CPT, HCPCS, or ICD
• Experience with multilabel or large‑label‑space classification problems
• Experience with MLOps tooling and practices, including experiment tracking, model registries, containerization, and CI/CD
• Experience delivering AI/ML solutions in a regulated or compliance‑sensitive environment
• Familiarity with Azure and cloud‑based AI/ML platforms
• Exposure to model monitoring, drift detection, and retraining workflows

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.

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