AI/ML Engineer

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.

The AI/ML Engineer with ML/AI, Python, Databricks, Snowflake, Spark, Scala – AI & Platform Enablement is a hands‑on technical leader responsible for building, modernizing, and scaling enterprise‑grade data assets/products while enabling advanced ML/AI capabilities. This role focuses primarily on designing and operating robust cloud‑native data pipelines and platforms, while also contributing to the development, deployment, and integration of AI/ML and Generative AI solutions into production systems.

The role requires solid ownership across data engineering, cloud infrastructure, and AI enablement, along with the ability to collaborate closely with Data & AI/ML engineers, mentor other engineers, and translate complex technical solutions into business value.

Primary Responsibilities:

• Design, build, and maintain scalable, secure, and high‑performance batch and streaming data pipelines using modern data engineering practices
• Lead the modernization and migration of on‑premise data platforms to cloud‑native architectures, owning infrastructure, networking, security, and deployment pipelines
• Develop and maintain core data platform components that support reliable ingestion, transformation, enrichment, and consumption of enterprise data assets
• Collaborate with data domain experts across Operations, Product, Finance, Value Analytics, and other domains to understand data sources and design efficient, connected data models
• Ensure data accuracy, quality, relevance, and governance by implementing validation, monitoring, documentation, and security controls
• Analyze large datasets to identify trends, patterns, and actionable insights; perform data analysis  to support analytics, AI use cases, and business strategy
• Enable reporting and analytics by making curated, trusted datasets available to BI and downstream consumers
• Partner with AI/ML Engineers and Leads to design, build, and improve machine learning models from scratch or enhance existing models
• Contribute to experimentation with novel ML and Generative AI architectures
• Help design and implement AI‑powered enterprise applications
• Support Retrieval‑Augmented Generation (RAG) solutions, including semantic search, vector databases, and LLM integration
• Optimize data and AI pipelines for scalability, performance, reliability, and cost efficiency in production environments
• Integrate AI/ML solutions into enterprise systems by partnering closely with data engineering, product, and platform teams
• Mentor and guide engineers and interns, contributing to skill development in data engineering, cloud infrastructure, Spark, and AI/ML
• Collaborate effectively with cross‑functional teams and stakeholders, communicating complex technical concepts in a clear and practical manner
• Comply with company policies, procedures, and directives related to employment, work arrangements, and evolving business needs
• 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 regard 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 or Master’s degree in Computer Science, Engineering, Data Engineering, Mathematics/Statistics, or a related field
• 4+ years of experience in software development with a solid focus on data engineering
• 1+ years of experience delivering solutions that include AI/ML or Generative AI components
• Proven experience building and maintaining data pipelines, data models, and data integration workflows
• Solid SQL skills for querying, transformation, and performance optimization
• Advanced proficiency in Python and experience with Scala for data and AI workloads
• Hands‑on experience with Apache Spark (batch and streaming), Databricks, Spark SQL, and cloud data platforms
• Experience with Azure cloud services, cloud infrastructure, monitoring, and deployment automation
• Working experience with Generative AI solutions using OpenAI‑compatible APIs
• Experience with CI/CD, version control, and DevOps practices (Git, GitHub Actions, Jenkins)
• Solid communication skills and ability to work effectively with technical and non‑technical stakeholders
• Data Engineering & Cloud Platforms: Spark, Azure, Snowflake, Databricks
• Programming & Infrastructure: Scala, Python, Terraform
• Machine Learning & AI: Good knowledge with a willingness to advance
• Version Control & Collaboration: GitHub
• AI Builder Expertise: Ability to design and deploy AI models

Preferred Qualifications:

• Experience with Databricks, Snowflake, modern data warehousing
• Hands‑on experience with Docker, Kubernetes, and Terraform
• Experience with Azure OpenAI, LLM Gateway, Agentic AI frameworks, AI Foundry, or LangFuse
• Exposure to NLP, enterprise search, speech AI, vision AI, and supervised/unsupervised ML techniques
• Experience working in Agile / Scrum environments
• Domain experience in US Healthcare or large‑scale regulated data environments

Professional Attributes:

• Solid analytical and problem‑solving skills with a platform‑first mindset
• Demonstrated technical leadership and ownership across complex initiatives
• Ability to balance hands‑on engineering with mentorship and collaboration
• Continuous learner with a solid interest in emerging data and AI technologies
• Positive, collaborative team player who contributes to a culture of excellence and shared accountability

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.