Senior AI/ML Engineer - Onsite in Minnesota
About The Position
Optum Tech is seeking a Senior AI/ML Engineer to join a technology team developing and scaling artificial intelligence and machine learning solutions across the enterprise. The engineer will design, develop, and deploy production-ready AI models and automations to turn complex healthcare workflows and data into actionable insights, collaborating with data scientists, software engineers, and domain leaders to build secure, high-performing systems on modern cloud infrastructure. The role is embedded with Behavioral Health business and operations teams and focuses on hands-on engineering and delivery of user-facing features. The engineer will work directly with business partners, operations leaders, clinicians, care advocates, and other users to understand workflows, prototype capabilities, validate requirements, and refine AI solutions. Under the architecture and technical direction of the Lead AI Engineer, this person will own complex AI components and serve as the day-to-day engineering connection between users and the broader development team. The emphasis is on complex feature ownership and user-facing delivery rather than portfolio architecture or overall team leadership. The engineer will build, train, optimize, and maintain machine learning models and data pipelines; integrate solutions into enterprise applications; and apply responsible AI practices. The role also includes using approved AI tools to streamline workflows, evaluating emerging trends, and advancing coding standards, code reviews, and architecture best practices.
Requirements
- Bachelor’s degree in Computer Science, Data Science, Software Engineering, or a related technical field.
- At least 5 years of software engineering or machine learning engineering experience in an enterprise technology environment.
- At least 2 years independently owning complex AI capabilities and user-facing features, working directly with business stakeholders and operations users to design, build, test, deploy, and optimize production AI solutions.
- At least 2 years of hands-on experience designing, building, and deploying AI/ML, generative AI, or advanced analytics solutions.
- At least 2 years of experience writing production-grade code in Python and working with RESTful APIs or microservices architectures.
- At least 2 years of experience with MLOps, CI/CD pipelines, and deployment on AWS, Azure, or GCP.
- Experience with PyTorch, TensorFlow, scikit-learn, Hugging Face, or comparable frameworks.
- Ability to engage directly with nontechnical users, clinicians, and business stakeholders to clarify problems and validate solutions.
- Ability to pass a drug test before beginning employment.
Nice To Haves
- Master’s degree in Computer Science, Data Science, Software Engineering, or a related technical field.
- Experience with generative AI architectures, large language models (LLMs), retrieval-augmented generation (RAG), and prompt or fine-tuning pipelines.
- Experience in healthcare IT, behavioral health, utilization management, prior authorization, clinical review, provider portals, or provider operations.
- Familiarity with enterprise AI governance frameworks, security standards, and ethical AI deployment.
- Familiarity with sensitive healthcare data, regulated workflows, or responsible AI controls.
Responsibilities
- Serve as a senior hands-on AI/ML engineer embedded with Behavioral Health business and operations teams.
- Work with business partners, operations leaders, clinicians, care advocates, and users to prototype, develop, test, and refine AI capabilities.
- Own complex AI components and features under the architecture and technical direction of the Lead AI Engineer.
- Act as the daily engineering connection between users and the broader development team.
- Design, develop, and deploy AI-powered solutions for complex business challenges, emphasizing responsible AI use.
- Meet with business users, operations leaders, clinicians, and subject-matter experts to understand workflows and validate requirements.
- Translate user needs into prototypes, technical designs, user stories, acceptance criteria, evaluation scenarios, and engineering tasks.
- Use enterprise-approved AI tools to streamline workflows, automate tasks, and drive continuous improvement across software systems.
- Evaluate emerging trends to inform solution design and strategic innovation.
- Build, train, optimize, and maintain scalable machine learning models and end-to-end data pipelines.
- Collaborate with cross-functional technical teams to integrate machine learning solutions into enterprise application ecosystems.
- Establish coding standards, perform code reviews, and promote architecture best practices for AI software engineering.
Benefits
- Comprehensive benefits package, subject to eligibility requirements.
- Incentive and recognition programs, subject to eligibility requirements.
- Equity stock purchase plan, subject to eligibility requirements.
- 401(k) contribution, subject to eligibility requirements.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
