Lead AI/ML Engineer - Power & Utilities

EY; Woodbridge Township (NJ); Hybrid; USD 126,000 - 230,000; Full time

Benefits offered by this job

Hybrid work model

Comprehensive compensation package

Extensive time-off policies

Job summary

EY in the United States is seeking a Manager in AI Native Engineering to lead the delivery of innovative AI/ML solutions for Power & Utilities clients. You will design scalable data science platforms, supervise diverse teams, and collaborate with clients to translate analytics into business value.

The role emphasizes cross-functional work, regulatory awareness, and advancing production-grade AI across cloud and on-prem environments, with a hybrid client-facing model.

Qualifications

• Bachelor’s degree required (4-year degree).
• 6–10 years of relevant AI/Data Science experience.
• 2–4 years experience directly managing technical teams.
• Experience designing, building, and maintaining production AI/ML solutions on a major cloud platform.

Responsibilities

• Lead workstream delivery and ensure effective project management.
• Continuously improve processes by researching and analyzing.
• Manage professional staff and supervise teams to deliver complex initiatives.
• Engage with clients and lead workstreams from planning through execution to closure.
• Identify opportunities for additional services and manage engagement economics.
• Design and deliver AI/ML use cases for Power & Utilities, e.g., asset health and outage forecasting.
• Work with utility data sources (SCADA, GIS, EAM, OMS, CIS, historians) and integrate into analytics platforms.
• Support utilities in moving AI solutions from pilots to production with governance and cybersecurity considerations.

Skills

Python

Client engagement

Team leadership

Data science

CI/CD

Education

Bachelor’s degree

Tools

Git

Azure DevOps

Jira

Job description

EY in the United States is seeking a Manager in AI Native Engineering to lead the delivery of innovative AI/ML solutions for Power & Utilities clients. You will design scalable data science platforms, supervise diverse teams, and collaborate with clients to translate analytics into business value.

The role emphasizes cross-functional work, regulatory awareness, and advancing production-grade AI across cloud and on-prem environments, with a hybrid client-facing model.