Join Optum, a global leader dedicated to improving health outcomes through innovative technology. We are expanding our team with a Senior AI/ML Engineer who will be instrumental in designing and developing intelligent systems. This position offers the opportunity to work across the entire machine learning project lifecycle, from initial data exploration to model deployment and ongoing maintenance. You will transform complex data into valuable insights and engineer AI-driven solutions that address significant real-world challenges.

Our culture fosters inclusion, collaboration with talented peers, comprehensive benefits, and opportunities for career growth. Contribute to advancing health optimization on a global scale and be a part of our mission to Care, Connect, and Grow together.

As a Senior AI/ML Engineer, your key responsibilities will include researching, designing, and developing sophisticated machine learning and deep learning models. You will build and manage robust data pipelines, ensuring data quality and accessibility for model training. A crucial part of this role involves training, evaluating, and validating models for accuracy and reliability, alongside deploying them into production environments with adherence to MLOps best practices.

You will collaborate closely with cross-functional teams, including data scientists and product managers, to integrate AI/ML solutions. Staying abreast of the latest AI and machine learning advancements is essential. Additionally, you will lead the design, development, and optimization of LLM-powered applications and agentic workflows, focusing on areas like RAG, prompt engineering, and multi-step orchestration. Ensuring the reliability and safety of generative AI systems through robust evaluation frameworks and structured output validation will also be a core function.

To excel in this role, you should possess hands-on experience with ML frameworks such as TensorFlow, PyTorch, Keras, and Scikit-learn. Proficiency in building LLM workflows and agentic applications using LangGraph and LangChain is required, along with experience integrating LLM provider APIs like Anthropic Claude and OpenAI. A deep understanding of machine learning, deep learning, and statistical modeling concepts is essential. Familiarity with cloud platforms (AWS, Google Cloud, Azure) and their ML services, as well as core generative AI concepts like RAG and vector databases, is expected.

Solid programming skills in Python, R, or Java are necessary, complemented by expertise in data handling with SQL, Pandas, and NumPy. Proficiency with Pydantic for data validation is also a must. We are looking for candidates with strong analytical and problem-solving skills, excellent communication abilities to convey complex technical ideas, and a creative, proactive mindset driving continuous improvement. While not strictly required, experience with containerization (Docker, Kubernetes), LLM observability tools, Databricks, and contributions to open-source projects are highly valued.