Data Engineering Scientist with AI/ML - Remote

UnitedHealth Group is 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.

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

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
• 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
• All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy