Lead AI/ML Engineer Remote Nationwide or Office-Based in MN/DC

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together. The Lead AI/ML Engineer will lead the design, development, deployment, and scaling of enterprise AI/ML solutions that improve clinical outcomes, patient engagement, operational efficiency, and regulatory compliance. This role is responsible for driving engineering best practices, MLOps excellence, and production-scale machine learning solutions while partnering with cross-functional teams to deliver innovative healthcare products leveraging structured and unstructured data. Combining deep technical expertise with technical leadership, this role involves hands-on development, architecture guidance, and mentorship of engineers while enabling enterprise-wide AI adoption. If you are located in MN or DC, you will have the flexibility to work remotely* as you take on some tough challenges. This position follows a office-based schedule with four in-office days per week.

Lead the end-to-end design, development, deployment, and operationalization of production-grade machine learning models and AI-enabled software solutions Build and support scalable, cloud-based AI/ML systems, data pipelines, and feature workflows for both batch and real-time workloads Establish and drive MLOps practices, including model orchestration, CI/CD automation, testing, drift detection, automated retraining, and operational governance Manage, monitor, and optimize production machine learning systems to ensure high reliability, scalability, and performance Apply advanced AI/ML techniques-such as Natural Language Processing (NLP), deep learning, computer vision, foundation models, and modern AI architectures-to address complex healthcare challenges Provide technical leadership, architecture guidance, and mentorship to engineers while driving engineering excellence across cross-functional teams Partner with product management, data science, architecture, and business stakeholders to translate strategic requirements into deliverable AI capabilities and communicate technical approaches to leadership 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 5+ years of software engineering / machine learning engineering experience in lieu of degree 5+ years of software engineering experience across all phases of the Software Development Life Cycle (SDLC) 3+ years of experience designing, developing, and deploying production-grade machine learning solutions in cloud environments (Azure, AWS, or GCP) 3+ years of programming experience with Python and SQL or PySpark 2+ years of experience implementing CI/CD pipelines and automated deployment practices for production software delivery Experience working with large-scale distributed data and computing platforms Preferred Qualifications: Master's degree or PhD in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related quantitative field Experience with enterprise AI/ML platforms such as Databricks, Azure Machine Learning, or Snowflake Experience building and deploying Generative AI, Large Language Models (LLMs), NLP, or advanced analytics solutions Experience working within regulated healthcare, payer, provider, or clinical environments Expertise in MLOps practices