Senior AI/ML Engineering Manager — Power & Utilities

EY; Lansing (MI); Hybrid; USD 126,000 - 230,000; Full time

Benefits offered by this job

Hybrid work model

Total rewards package

Job summary

EY is seeking a Manager in AI Native Engineering to deliver innovative AI/ML solutions for Power & Utilities clients. You will guide teams, collaborate with IT and business leaders, and translate analytics into actionable insights while ensuring governance and regulatory compliance.

You will work across cloud and on‑prem environments, advancing production deployments, data pipelines, and model monitoring for utility operations.

Qualifications

• Bachelor’s degree required.
• 6–10 years of full‑time experience in AI, Data Science, and/or Machine Learning.
• 2–4 years of experience directly managing technical teams.
• Strong skills in Python and ML frameworks.
• Experience designing, building, and maintaining production AI/ML solutions on a major cloud platform.
• Familiarity with regulatory, governance, and risk management considerations.

Responsibilities

• Lead workstreams delivering AI/DS projects for Power & Utilities clients.
• Manage teams and supervise complex technical initiatives with accountability for results.
• Engage actively with clients and lead sessions from planning to closure.
• Identify opportunities for additional services and manage engagement economics.
• Design and deliver AI/ML use cases such as asset health, outage prediction, and regulatory analytics.

Skills

Python

Generative AI

ML pipelines

Team leadership

Client engagement

Education

Bachelor’s degree

Master’s degree (preferred)

Tools

Git

Azure DevOps

Jira

CI/CD

Job description

EY is seeking a Manager in AI Native Engineering to deliver innovative AI/ML solutions for Power & Utilities clients. You will guide teams, collaborate with IT and business leaders, and translate analytics into actionable insights while ensuring governance and regulatory compliance.

You will work across cloud and on‑prem environments, advancing production deployments, data pipelines, and model monitoring for utility operations.