- Platform & Data:- Experience with cloud platforms (Azure preferred) and containerized deployments (Docker/Kubernetes)
- Familiarity with data engineering fundamentals - ETL/ELT, SQL, data modeling, streaming pipelines
- Basic understanding of CI/CD pipelines covering both model and front-end deployment
- Experience building UIs that consume streaming APIs (e.g., SSE/WebSockets for LLM token streaming)
- Working knowledge of TypeScript, HTML5, CSS3, and modern build tooling (Vite, Webpack)
- Familiarity with REST/GraphQL API integration and basic UX principles for AI-driven interfaces
- Solid Python programming experience (NumPy, Pandas, Scikit-Learn, PyTorch/TensorFlow)
- Knowledge of MLOps tools (Azure ML, AWS Sagemaker, MLflow, Databricks, KubeFlow, Feature Stores)
- Exposure to agentic AI patterns, automated workflows, and API-based integrations
- Practical experience with AI development tools such as Copilot Studio, GitHub Copilot, or M365 Copilot integrations
- Experience with vector databases/embedding stores (e.g., Pinecone, FAISS, Chroma, Azure AI Search)
- Solid Python programming experience (NumPy, Pandas, Scikit-Learn, PyTorch/TensorFlow)
- Exposure to design systems/component libraries (e.g., Material UI, Tailwind, shadcn/ui)
- Platform & Data:- Experience with cloud platforms (Azure preferred) and containerized deployments (Docker/Kubernetes)
- Familiarity with data engineering fundamentals - ETL/ELT, SQL, data modeling, streaming pipelines
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 an experienced AI/ML Builder for the AIFWD team, with a solid foundation in Analytics (5+ years), Machine Learning (3+ years), hands-on AI development (2+ years), and front-end engineering, particularly React (2+ years). The ideal candidate is passionate about building scalable, full-stack AI/ML solutions - from model and agent logic through to the user-facing interface - and is committed to ongoing support, optimization, and enhancement of deployed use cases.
This role spans the full lifecycle - from problem discovery to deployment, UI delivery, and operational support - across multiple high-impact AIFWD initiatives.
- Collaborate with cross-functional teams across engineering, product, and data teams to operationalize AI workloads efficiently
- UI/Frontend- Build responsive, production-grade UIs (primarily in React) that expose AI/ML and LLM capabilities to end users
- Integrate front-end applications with AI/ML backends, APIs, and streaming LLM responses (e.g., token streaming, chat UX, status/progress states)
- 2+ years in hands-on AI/LLM development (prompt engineering, RAG, agent workflows, embeddings, vector stores, generative models)
- 2+ years in front-end development, primarily React (component architecture, state management, API integration)
- Technical Skills:- AI/ML & Gen AI- Experience with LLM-based development, including instruction tuning, prompt engineering, retrieval-augmented generation (RAG), or evaluation frameworks
- Understanding of model evaluation, guardrails, and hallucination mitigation techniques for Gen AI applications
- Front-End / UI:- Solid hands-on experience with React (hooks, component design, state management - Redux/Context/Zustand)
- Experience building UIs that consume streaming APIs (e.g., SSE/WebSockets for LLM token streaming)
- Experience supporting multiple simultaneous AI/ML use cases, including user-facing AI products
- Experience as a full-stack AI engineer, bridging ML/LLM backend work with React front-end delivery
- Understanding of Responsible AI principles and enterprise AI safety guidelines
Complete your application on careers.unitedhealthgroup.com. The employer’s form will show what is required.
Applying through Radancy (TalentBrew)
Radancy (TalentBrew) runs the employer’s careers site, but the application itself usually runs on another system, often Workday or Taleo. The advice for that system applies once you click Apply.
Yes. We’ve followed 9 other Lead AI/ML Engineer jobs there since April 2026. 4 came down, usually after about 12 days. 5 are still up.
HyderabadCame down after 0 days, first seen Jun 11
HyderabadCame down after 15 days, first seen Aug 18
GurugramCame down after 9 days, first seen Aug 18
Eden PrairieStill up after 36 days, first seen Oct 8
Eden PrairieStill up after 36 days, first seen Oct 8
Eden PrairieStill up after 16 days, first seen Oct 28
GurugramStill up after 15 days, first seen Oct 30
BengaluruStill up after 9 days, first seen Nov 4
This jobUp 2 days so far, first seen Nov 12
Jun 11Today
If this one keeps the same pace, it may come down around November 24.
Large employers often post one title for several teams, so these can be separate openings.
About UnitedHealth Group
People
About 390,000 in 2025, down 2% from the year before.Annual report (SEC Form 10-K)
Company
Listed as UNH.
H-1B visas
11 approved for new hires in fiscal 2025.US Citizenship and Immigration Services
Demand for ML Engineer roles
New ML Engineer postings at the employers we follow are up 10% over the last 6 weeks compared with the 6 before.
August 17Last week
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
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 an experienced AI/ML Builder for the AIFWD team, with a solid foundation in Analytics (5+ years), Machine Learning (3+ years), hands-on AI development (2+ years), and front-end engineering, particularly React (2+ years). The ideal candidate is passionate about building scalable, full-stack AI/ML solutions - from model and agent logic through to the user-facing interface - and is committed to ongoing support, optimization, and enhancement of deployed use cases.
This role spans the full lifecycle - from problem discovery to deployment, UI delivery, and operational support - across multiple high-impact AIFWD initiatives.
Primary Responsibilities:
AI Builder
Design, develop, and deploy AI-powered solutions to solve complex business challenges, with an emphasis on responsible AI use
Streamline workflows and automate tasks using enterprise-approved AI tools and ML/LLM frameworks
Evaluate emerging AI/ML trends to inform solution design and drive continuous improvement
Support the end-to-end lifecycle of AI/ML use cases - data preparation, feature engineering, modeling, deployment, monitoring, MLOps, and post-production enhancements
Design and build Gen AI/LLM-powered features such as chat interfaces, copilots, RAG-based search, and agentic workflows
Collaborate with cross-functional teams across engineering, product, and data teams to operationalize AI workloads efficiently
UI/Frontend
Build responsive, production-grade UIs (primarily in React) that expose AI/ML and LLM capabilities to end users
Integrate front-end applications with AI/ML backends, APIs, and streaming LLM responses (e.g., token streaming, chat UX, status/progress states)
Collaborate with design/product teams to ensure AI-driven features are explainable, trustworthy, and user-friendly
Contribute to component libraries/design systems used across AIFWD AI products
Development & Support
Build production-ready ML pipelines and services (batch/real-time)
Provide L2/L3 support for deployed AI/ML systems, ensuring reliability, model drift management, and performance optimization
Conduct root-cause analysis for production incidents involving model performance, data changes, or UI/integration issues
Maintain documentation, versioning, and traceability of models, training datasets, and front-end codebases
Comply with all applicable Company policies, procedures, and business directives, changes including those relating to work location, team assignments, work schedules, and flexible work arrangements
Required Qualifications:
Experience:
5+ years in Data Analytics, statistical modeling, or data-driven problem solving
3+ years in Machine Learning model development (supervised, unsupervised, NLP, forecasting, optimization, etc.)
2+ years in hands-on AI/LLM development (prompt engineering, RAG, agent workflows, embeddings, vector stores, generative models)
2+ years in front-end development, primarily React (component architecture, state management, API integration)
Technical Skills:
AI/ML & Gen AI
Experience with LLM-based development, including instruction tuning, prompt engineering, retrieval-augmented generation (RAG), or evaluation frameworks
Practical experience with AI development tools such as Copilot Studio, GitHub Copilot, or M365 Copilot integrations
Experience with vector databases/embedding stores (e.g., Pinecone, FAISS, Chroma, Azure AI Search)
Exposure to agentic AI patterns, automated workflows, and API-based integrations
Familiarity with LLM orchestration frameworks (e.g., LangChain, LlamaIndex, Semantic Kernel)
Understanding of model evaluation, guardrails, and hallucination mitigation techniques for Gen AI applications
Front-End / UI:
Solid hands-on experience with React (hooks, component design, state management - Redux/Context/Zustand)
Experience building UIs that consume streaming APIs (e.g., SSE/WebSockets for LLM token streaming)
Working knowledge of TypeScript, HTML5, CSS3, and modern build tooling (Vite, Webpack)
Familiarity with REST/GraphQL API integration and basic UX principles for AI-driven interfaces
Exposure to design systems/component libraries (e.g., Material UI, Tailwind, shadcn/ui)
Platform & Data:
Experience with cloud platforms (Azure preferred) and containerized deployments (Docker/Kubernetes)
Familiarity with data engineering fundamentals - ETL/ELT, SQL, data modeling, streaming pipelines
Basic understanding of CI/CD pipelines covering both model and front-end deployment
Preferred Qualifications:
Experience supporting multiple simultaneous AI/ML use cases, including user-facing AI products
Experience as a full-stack AI engineer, bridging ML/LLM backend work with React front-end delivery
Understanding of Responsible AI principles and enterprise AI safety guidelines
Solid problem-solving orientation and ability to convert ambiguous business problems into well-structured, end-to-end AI solutions (model + UI)
Ability to coach teams on using AI tools and contribute to AI adoption across the organization
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.