The Role
Leads the architecture, development, and productionization of AI, machine learning, and GenAI solutions for healthcare. Builds data and feature pipelines, LLM applications, RAG systems, and deep learning models while establishing MLOps and LLMOps practices. Ensures monitoring, governance, privacy, fairness, and compliance; translates business needs into technical roadmaps; communicates with stakeholders; and mentors engineers while setting engineering and reliability standards.
Summary Generated by Built In
Requisition Number: 2384091
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're looking for a hands-on technical leader to design, build, and productionize AI/ML and GenAI solutions that improve healthcare operations and patient outcomes. You will own end-to-end delivery-from problem framing and data pipelines to models, MLOps/LLMOps, and ongoing monitoring-while mentoring a small team and partnering with product, data engineering, and clinical/operations stakeholders.
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.
We're looking for a hands-on technical leader to design, build, and productionize AI/ML and GenAI solutions that improve healthcare operations and patient outcomes. You will own end-to-end delivery-from problem framing and data pipelines to models, MLOps/LLMOps, and ongoing monitoring-while mentoring a small team and partnering with product, data engineering, and clinical/operations stakeholders.
Primary Responsibilities:
- Lead architecture and delivery of ML/GenAI solutions (classification, forecasting, NLP, deep learning, LLM apps) at production scale
- Build robust data/feature pipelines over large clinical/claims datasets; write efficient, well-tested Python (pandas/NumPy) and SQL
- Develop and deploy LLM capabilities: prompt design, fine-tuning, RAG pipelines, vector indexing, and evaluation with guardrails
- Establish MLOps/LLMOps best practices: CI/CD, model registry, experiment tracking, monitoring, drift detection, A/B testing, cost/perf optimization
- Ensure data privacy and compliance (HIPAA/PHI handling, access controls, auditability) and champion model governance and Responsible AI
- Translate business problems into technical roadmaps; communicate trade-offs and results to executives and non-technical partners
- Mentor engineers and set engineering standards (code reviews, documentation, reliability, observability)
- 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 degree in Computer Science, Engineering, Math, or related field required; MS/PhD preferred or equivalent experience
- 10+ years of professional experience in software/ML engineering, including 3+ years leading projects or teams
- Hands-on GenAI experience: LLMs, embeddings, RAG, fine-tuning, evaluation; familiarity with Hugging Face and LangChain/LlamaIndex
- Solid foundation in statistics and ML (hypothesis testing, experimental design, feature engineering, supervised/unsupervised methods)
- Deep learning expertise (PyTorch or TensorFlow) and modern NLP (transformers)
- Expert Python and pandas stack; ability to write vectorized, high-performance code; solid testing practices (pytest) and Git
- Solid data engineering skills: SQL; experience with Spark/Dask and workflow orchestration (Airflow/Prefect)
- Cloud proficiency (AWS/Azure/GCP) and containerization/orchestration (Docker/Kubernetes); CI/CD and IaC (Terraform) exposure
- Proven excellent communication and stakeholder management skills
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
- Bachelor’s degree in Computer Science, Engineering, Math, or a related field
- 10+ years of professional experience in software or machine learning engineering
- 3+ years leading projects or teams
- Hands-on experience with LLMs, embeddings, RAG, fine-tuning, and evaluation
- Familiarity with Hugging Face and LangChain or LlamaIndex
- Solid foundation in statistics and machine learning, including hypothesis testing, experimental design, feature engineering, and supervised or unsupervised methods
- Deep learning expertise with PyTorch or TensorFlow
- Modern NLP and transformer experience
- Expert Python and pandas skills, including vectorized high-performance code
- Solid testing practices with pytest and Git
- SQL and data engineering experience
- Experience with Spark or Dask
- Experience with Airflow or Prefect workflow orchestration
- Cloud proficiency in AWS, Azure, or GCP
- Containerization and orchestration experience with Docker and Kubernetes
- CI/CD and Terraform infrastructure-as-code exposure
- Excellent communication and stakeholder management skills
- Master’s degree, PhD, or equivalent experience
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
