The Role
Develop and productionize advanced AI/ML solutions, including LLM training and fine-tuning, GraphRAG, embeddings, semantic retrieval, distributed multi-GPU training, and reinforcement learning alignment. Build hybrid NLP systems, optimize model architectures and retrieval pipelines, and collaborate cross-functionally to deploy AI solutions. The role requires deep expertise in machine learning, deep learning, NLP, transformer and state-space architectures, cloud ML platforms, data preparation, and production-grade model development.
Summary Generated by Built In
Requisition Number: 2386678
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 Responsibilities:
Required Qualifications:
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.
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 Responsibilities:
- Develop end-to-end training and fine-tuning of Large Language Models (LLMs), including both open-source (e.g., Qwen, LLaMA, Mistral) and closed-source (e.g., OpenAI, Gemini, Anthropic) ecosystems
- Architect and implement GraphRAG pipelines, including knowledge graph representation and retrieval for enhanced contextual grounding
- Design, train, and optimize semantic and dense vector embeddings for document understanding, search, and retrieval
- Develop semantic retrieval systems with advanced document segmentation and indexing strategies
- Build and scale distributed training environments using NCCL and InfiniBand for multi-GPU and multi-node training
- Apply reinforcement learning techniques (e.g., RLHF, RLAIF) to align model behavior with human preferences and domain-specific goals
- Collaborate with cross-functional teams to translate business needs into AI-driven solutions and deploy them in production environments
- 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:
- Graduate degree or equivalent experience
- PhD or Master's degree in computer science, Machine Learning, or related field
- 10+ years of experience in applied AI/ML with statistics, with a Solid track record of delivering production-grade models
- Experience with Hybrid NLP solutions that combine symbolic and machine learning approaches
- Experience with PyTorch
- Deep knowledge and extensive experience with Machine/Deep Learning frameworks including transformer architectures, state space models, large language models, and agentic approaches
- Knowledge of algorithms and techniques within a computational domain with emphasis on text processing
- Proven deep expertise in: NLP, Fundamental machine learning, deep learning, transformer, state space-based architecture
Azure ML and/or AWS - Proven solid in Python coding, SQL and database queries, data preparation, and analysis
- Exploratory Data Analysis (EDA)
- LLM training and fine-tuning (e.g., GPT, LLaMA, Mistral, Qwen)
- Graph-based retrieval systems (GraphRAG, knowledge graphs)
- Embedding models (e.g., BGE, E5, SimCSE)
- Semantic search and vector databases (e.g., FAISS, Weaviate, Milvus)
- Document segmentation and preprocessing (OCR, layout parsing)
- Model fusion and ensemble techniques (stacking, boosting, gating)
- Optimization algorithms (Bayesian, Particle Swarm, Genetic Algorithms)
- Reinforcement learning (e.g., RLHF, PPO, DPO, GRPO), Supervised Fine Tuning (SFT), LoRA, QLoRA, axolotl
- Prompt optimization framework (AutoPrompt, GreaterPrompt, DSPy), GEPA
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.
Skills Required
- Graduate degree or equivalent experience
- PhD or Master's degree in computer science, machine learning, or a related field
- 10+ years of experience in applied AI/ML with statistics and a track record of delivering production-grade models
- Experience with hybrid NLP solutions combining symbolic and machine learning approaches
- Experience with PyTorch
- Deep knowledge of machine learning and deep learning frameworks, transformer architectures, state space models, large language models, and agentic approaches
- Knowledge of algorithms and techniques for text processing
- Expertise in NLP, fundamental machine learning, deep learning, transformers, and state-space architectures
- Experience with Azure ML and/or AWS
- Strong Python coding, SQL, database query, data preparation, and analysis skills
- Experience with exploratory data analysis
- Experience training and fine-tuning LLMs such as GPT, LLaMA, Mistral, and Qwen
- Experience with graph-based retrieval systems, GraphRAG, and knowledge graphs
- Experience with embedding models such as BGE, E5, and SimCSE
- Experience with semantic search and vector databases such as FAISS, Weaviate, and Milvus
- Experience with document segmentation and preprocessing, including OCR and layout parsing
- Experience with model fusion and ensemble techniques, including stacking, boosting, and gating
- Experience with Bayesian, particle swarm, and genetic optimization algorithms
- Experience with reinforcement learning, RLHF, PPO, DPO, GRPO, supervised fine-tuning, LoRA, QLoRA, and axolotl
- Experience with prompt optimization frameworks including AutoPrompt, GreaterPrompt, DSPy, and GEPA
Optum Compensation & Benefits Highlights
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Parental & Family Support — Paid parental leave (six weeks), paid caregiver leave (up to two weeks), Bright Horizons back-up care, and adoption assistance up to $10,000 are prominently included. Feedback suggests these family supports meaningfully aid work-life balance and are often highlighted as strengths.
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Retirement Support — A 401(k) with company match is available to all employees, including part-time staff, alongside other financial protections like disability and life insurance. Feedback suggests broad access and matching make retirement support a core pillar of the package.
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Equity Value & Accessibility — An Employee Stock Purchase Plan offers discounted company stock, with some roles also eligible for sign-on or performance bonuses. Feedback suggests the ESPP is a standout financial perk that helps employees build ownership over time.
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The Company
What We Do
Optum, part of the UnitedHealth Group family of businesses, 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. At Optum, we support your well-being with an understanding team, extensive benefits and rewarding opportunities. By joining us, you’ll have the resources to drive system transformation while we help you take care of your future. We recognize the power of connection to drive change, improve efficiency and make a difference in health care. Join a team where your skills and ideas can make an impact and where collaboration is key to creating technology that produces healthier outcomes.
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Optum Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
Optum has three workplace models that balance the needs of the business and the responsibilities of each role. These models, core on‑site (5 days/week), hybrid (4 days/week) and telecommute or fully remote, vary by country, role and location.
Typical time on-site:
Not Specified
