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.
AIML Engineer
We are seeking an AI/ML Engineer to design, build, and deploy AI driven and machine learning powered solutions that solve real business problems at scale.
This role focuses on applied machine learning, GenAI, and intelligent automation, working closely with product, engineering, and platform teams to move AI concepts from idea to production. You will contribute across the AIML lifecycle - from data preparation and model development to deployment, integration, and ongoing optimization - while applying modern engineering and DevOps practices.
Primary Responsibilities:
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Design and deploy generative AI and NLP solutions using transformer-based architectures for enterprise use cases such as search, summarization, extraction, conversational AI, and decision support
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Develop and fine-tune large language model (LLM) applications using commercial and open-source models such as OpenAI, Anthropic/Claude, Gemini, LLaMA, or Mistral
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Design and implement retrieval augmented generation (RAG) pipelines including document ingestion, chunking strategies, embedding generation, and vector database integration
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Build agentic AI systems including single agent and multi agent workflows capable of tool use, reasoning, planning, and autonomous task execution
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Implement evaluation and monitoring frameworks for generative AI systems including hallucination detection, bias monitoring, and human in the loop evaluation
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Develop safety and governance controls for AI systems including prompt hardening, policy enforcement, and responsible AI guardrails
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Productionize AI/ML pipelines using CI/CD, testing, monitoring, and observability best practices in cloud native environments
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Collaborate with product, platform, and data science teams to translate requirements into scalable AI solutions
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Influences the team designs and solutions
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Prioritizing and tech stack selection for implementation for AI/ML solution
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Helps decompose complex problems into straightforward solutions; is customer focused
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Understands the problem space and the "why" behind the solution; identifies opportunities to improve the AI solution
Focus on AI capability performance metrics (quality, latency, cost, reliability, and adoption/impact)
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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
Builder Responsibilities:
Design, develop, and deploy AI-powered solutions using no-code, low-code, and advanced platforms, translating business needs into scalable applications that enhance products, workflows, and decision-making.
Required Qualifications:
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Bachelor's degree or equivalent experience
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Core AI/ML Engineering
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Hands-on experience applying Statistical Models, Machine Learning Models, Deep Learning Models, and GenAI Models
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Exposure to RAG, LangChain, and VectorDBs (or equivalent frameworks/tools)
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Foundational understanding of Machine Learning concepts
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Proven ability to quantize and optimize GenAI models (latency/cost/performance tradeoffs)
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Proven ability to run medium to complex proof-of-concepts in a healthcare business context involving model training, evaluation, and baselining against production systems
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Platform, Scale, and Delivery
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Experience working on large-scale training and inference of ML models
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Experience scaling via Databricks and PySpark (or equivalent distributed compute)
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Experience with GitHub and modern engineering practices (code reviews, pair programming)
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Familiarity with cloud platforms such as Azure and/or AWS
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Familiarity with evaluation metrics and model performance measurement
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Understanding of AI platform tech stack and how models move from experimentation to production
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Collaboration & Leadership Behaviors
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Proven excellent communication, writing, and presentation skills within the team
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Proven ability to mentor junior AI/ML engineers; collaborative, positive attitude
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Team player- Proven ability to take feedback and "disagree and commit" to the team's direction
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Proven ability to foster a culture of safety, quality, and trust
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Responsible AI
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Demonstrated commitment to building, testing, and deploying AI responsibly in a way that meets enterprise governance expectations (e.g., model development/testing requirements aligned to the Optum Machine Learning Review Board)
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Hands-on AI/ML engineering expert that will tackle intrinsically hard problems, acquiring expertise as needed
Preferred Qualifications:
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Experience improving GenAI systems across quality, hallucination reduction, cost, and latency through experimentation and evaluation frameworks
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Experience productionizing AI/ML with CI/CD, observability, monitoring, and operational readiness in regulated environments
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Experience delivering AI/ML in healthcare
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.
