Principal AI/ML Engineer - Remote Nationwide or Hybrid in MN/DC

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. We are looking for a Principal AI/ML Engineer to lead the architecture, design, and end-to-end development of production-grade AI/ML systems. This is a hands-on technical leadership role - you'll set engineering standards, drive adoption of modern ML and agentic AI approaches, and translate research into scalable, enterprise-ready solutions used across the business. 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.

Lead architecture, design, and end-to-end delivery of production AI/ML systems - training, deployment, and monitoring pipelines Drive adoption of deep learning and agentic AI approaches across use cases such as NLP/NLU, intent classification, semantic understanding, and ASR Translate research and experimental findings into scalable, enterprise-ready solutions Define and enforce engineering best practices across the ML lifecycle - versioning, CI/CD, drift detection, performance optimization, model governance Design and evaluate agentic workflows (multi-step reasoning, tool-use, orchestration) and establish standards for evaluating and monitoring them safely in production Partner with data scientists and applied researchers to bridge the gap between prototypes, platform and production Work with large-scale computing frameworks and distributed data systems to process high-volume datasets Present model performance, architectural decisions, and technical tradeoffs to leadership and cross-functional stakeholders Mentor senior and mid-level engineers; set the technical bar across the AI/ML engineering function Evaluate and introduce emerging AI/ML tools, frameworks, and platformsMentor and guide senior and mid-level engineers, setting technical standards across the AI/ML engineering function Evaluate and introduce emerging AI/ML tools, frameworks, and platforms to continuously improve engineering capabilities Apply knowledge of statistics, probability theory, optimization, and experimental methodologies to build robust, reliable ML systems You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.

Bachelor's degree or 4+ years of equivalent software engineering or AI/ML experience in lieu of a degree 12+ years of total software/ML engineering experience 8+ years building and deploying production systems 3+ years of experience in a technical leadership, architecture, or staff/principal-level engineering capacity 3+ years solid Python skills with hands-on depth in at least one major deep learning framework (PyTorch or TensorFlow) 3+ years of proven experience architecting end-to-end ML pipelines: data ingestion, training, serving, and monitoring 3+ years of working experience with at least one cloud ML platform (AWS SageMaker, Azure ML, or GCP Vertex AI) 3+ years of solid grounding in statistics, probability theory, optimization, and experimental design 3+ years of MLOps experience: CI/CD for models, versioning, drift detection, automated retraining, performance observability, and governance 2+ years of practical, hands-on experience building or deploying LLM-based or agentic systems - orchestration, tool-use/function