Data Engineering Scientist with AI/ML - Remote

Optum is a global leader in health care innovation, seeking a highly skilled and motivated AI/ML Engineer to lead innovation in claims adjudication through advanced Generative AI solutions. This role emphasizes designing and deploying secure, scalable AI systems while collaborating across teams to deliver measurable impact.

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