AI/ML Lead - IT Operations - Hybrid in MN or Remote

UnitedHealth Group•Minnetonka, MN

2d•Hybrid

About The Position

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. We're seeking a visionary AI/ML Lead to drive innovation in IT Operations through intelligent automation, predictive analytics, and agentic AI. This role will lead the design and deployment of scalable machine learning systems that enhance observability, accelerate incident response, and enable self-healing infrastructure across the enterprise. 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.

Requirements

Graduate degree in Computer Science, Data Science, or a related field
5+ years of experience in AI/ML engineering, with a focus on IT operations or infrastructure
5+ years of hands-on experience with Python, SQL, and Spark for data processing and model development
3+ years of experience with cloud platforms such as Azure, AWS, or GCP
3+ years of experience implementing ML Ops practices, CI/CD pipelines, and containerization using Docker and Kubernetes
3+ years of experience working with IT operations tools and concepts including CMDB, incident management, and observability platforms
2+ years of experience integrating ML models into production environments and supporting model lifecycle management

Nice To Haves

2+ years of experience with NLP, LLM frameworks, and Generative AI techniques
Experience designing and deploying agentic AI systems for autonomous decision-making in operational contexts
Experience leading data science projects and mentoring junior team members
Proven solid technical communication skills and experience with collaborative development using GitHub
Proven ability to work in agile environments and deliver high-impact, scalable solutions

Responsibilities

Data Engineering: Build robust, scalable pipelines to ingest and process structured and unstructured data from tools like Splunk, Dynatrace, ServiceNow, and system logs
Feature Engineering: Create and maintain high-quality features for ML models supporting anomaly detection, predictive alerting, and automated remediation
Model Deployment: Collaborate with Data Scientists to operationalize ML models, ensuring they meet performance, scalability, and maintainability standards
AI-Driven Automation: Integrate ML insights into orchestration platforms (e.g., Jenkins, Interlink) to enable intelligent, self-healing workflows
Agentic AI Systems: Design autonomous agents capable of reasoning, planning, and executing tasks across IT operations-handling incident triage, root cause analysis, and resolution
Data Governance: Uphold data integrity, lineage, and compliance with enterprise security and governance standards
Infrastructure Enablement: Leverage cloud-native and hybrid technologies to support real-time analytics and model inference at scale
Cross-Functional Collaboration: Work closely with engineering, operations, and business teams to define requirements, document solutions, and contribute to knowledge bases for RCA and self-healing patterns
Collaborate with research, engineering, and product teams to translate cutting-edge AI advancements into production-ready capabilities.
Uphold ethical AI principles by embedding fairness, transparency, and accountability throughout the model development lifecycle.