As a Lead AI/ML Engineer within Optum Technology, you will define and execute the AI/ML engineering roadmap aligned with key business objectives. You will provide technical leadership for Machine Learning, Generative AI, Agentic AI, NLP, and Predictive Analytics initiatives, leading architectural reviews and technology selection decisions. Working alongside a collaborative team of engineers and data scientists, you will design, build, and deploy production-ready AI systems, establish end-to-end MLOps pipelines, and champion responsible AI practices to deliver scalable solutions that transform healthcare technology.
You'll enjoy the flexibility to work remotely * from anywhere within the U.S. as you take on some tough challenges.
Primary Responsibilities:- Define and execute the AI/ML engineering roadmap aligned with business objectives
- Provide technical leadership for AI, Machine Learning, Generative AI, Agentic AI, NLP, and Predictive Analytics initiatives
- Lead AI solution architecture reviews and technology selection decisions while mentoring and developing AI/ML engineers and data scientists
- Design, build, train, evaluate, and deploy production-ready machine learning and deep learning models
- Lead implementation of LLM-based applications, RAG architectures, AI agents, and conversational AI platforms
- Establish model performance benchmarks, validation frameworks, responsible AI, explainability, bias mitigation, and model governance practices
- Design and implement end-to-end MLOps pipelines, CI/CD standards, model monitoring, drift detection, and observability on cloud platforms (e.g., Azure or GCP)
- Collaborate with data engineering teams to develop reliable data pipelines and feature stores while ensuring compliance with security and regulatory standards
- Partner with business leaders and domain experts to translate complex business problems into scalable AI solutions and communicate technical outcomes to executive audiences
- Strategically leverage enterprise AI capabilities to streamline workflows, optimize inference performance, solve complex challenges, and drive continuous engineering excellence
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.
Required Qualifications:- 5+ years of software engineering or data engineering experience
- 2+ years of hands-on Machine Learning engineering experience
- Experience building and deploying production-ready ML/DL models into live environments
- Experience designing or implementing cloud-native infrastructure or MLOps pipelines (e.g., Azure or GCP)
- Demonstrated track record of delivering AI solutions that drive measurable business impact
Preferred Qualifications:- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, Mathematics, or a related field
- Experience delivering Large Language Model (LLM) applications, Retrieval-Augmented Generation (RAG) architectures, and AI agents
- Hands-on experience with responsible AI frameworks, explainability tools, bias mitigation, and model governance
- Proven solid leadership and communication skills with experience presenting technical concepts to executive stakeholders
*All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy
Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $145,500 - $249,500 annually based on full-time employment. We comply with all minimum wage laws as applicable.
Application Deadline: This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants.
