Data Engineering Scientist with AI/ML - Remote

UnitedHealth Group•Minnetonka, MN

1d•Remote

About The Position

Optum Tech is a global leader in health care innovation. Our teams develop cutting-edge solutions that help people live healthier lives and help make the health system work better for everyone. From advanced data analytics and AI to cybersecurity, we use innovative approaches to solve some of health care’s most complex challenges. Your contributions here have the potential to change lives. Ready to build the next breakthrough? Join us to start Caring. Connecting. Growing together. UHC Technology is focused on driving change, modernization, and ensuring reliable and stable systems so that we can help to transform health care - making it easier, more affordable, and more effective for those we serve. We are passionate about technology and the role it plays to create distinctive experiences to our constituents. While we are always focused on how technology can help us deliver faster and with improved quality, we are far more enthusiastic about the ways technology can reinvent how we deliver on our mission in partnership with the UHC lines of business and Optum Technology. We are seeking a highly skilled and motivated AI/ML Engineer to lead innovation in claims adjudication through advanced Generative AI solutions. This role emphasizes Large Language Models (LLMs), agentic frameworks, and prompt engineering to automate complex workflows. You will design and deploy secure, scalable, and responsible AI systems while collaborating across teams to deliver measurable impact. You’ll enjoy the flexibility to work remotely from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week.

Requirements

5+ years of hands-on experience in AI/ML techniques like Prompt Engineering , RAG (Retrieval Augmented Generation) and Agentic AI
Solid expertise in Python, PySpark, T-SQL, SQL, and big data technologies (Hadoop, Spark)
Proven deep knowledge of statistics, data modeling, and simulation
Hands-on experience with Generative AI frameworks/architectures (LangChain, HuggingFace, OpenAI APIs)
Proficiency in cloud technologies: Azure (Databricks, ML Studio), AWS Bedrock, Azure Foundry, Kafka, and cloud-native AI services
Demonstrated familiarity with CI/CD pipelines, GitHub Actions, and containerization tools
Proven excellent problem-solving skills and ability to handle ambiguity
Proven solid understanding of LLM security, prompt engineering, and responsible AI practices

Nice To Haves

Experience with LLMs (GPT, Gemini, LLaMA) and prompt-based learning
Knowledge of Kafka, TensorFlow, and advanced deep learning architectures (CNNs, Autoencoders)
Solid understanding of Agile methodologies and DevOps practices
Internal Data management and Big data handling experience

Responsibilities

Design, develop, and deploy AI/ML and Generative AI models for predictive, prescriptive, and generative analytics across healthcare datasets
Implement advanced architectures including LLMs (GPT, Gemini, LLaMA), Retrieval-Augmented Generation (RAG), and Agentic Frameworks
Build and optimize end-to-end pipelines using Python (Sci-kit Learn, Pandas, Flask, LangChain), PySpark, T-SQL and SQL
Develop and fine-tune multiple GenAI models for NLP, summarization, prompt engineering, and conversational AI
Apply MLOps best practices: model versioning, drift analysis, quantization, MLFlow, containerization with Docker, and CI/CD pipelines
Work with cloud platforms: Azure (Databricks, ML Studio, Data Factory, Data Lake, Delta Tables), AWS, and GCP for scalable deployments
Integrate data warehousing solutions like Snowflake and manage large-scale data pipelines.
Collaborate in an Agile environment, participate in sprint planning, and maintain code repositories using GitHub/Git
Ensure compliance with security and governance standards for healthcare data
Coach and mentor junior team members