Senior Machine Learning Engineer - Energy

Energy Management's Analytics & Data Science team works to accelerate the transition toward a carbon-free future through software and analytics. We are looking for a Senior Machine Learning Engineer to help us accomplish this mission.

Working with the Analytics & Data Science team in DNV - Energy Management's Technology group is more than just a job; it's an opportunity to be part of a collaborative community where you can learn, grow, and thrive. Join a dynamic and diverse technology team that values innovation, impact, and sustainability. Help us bridge the gap between advanced analytics systems and user-facing web applications that support demand side management, demand flexibility, and transportation electrification programs!

This role is based at our DNV offices in Albuquerque, NM; Arlington, VA; Austin, TX; Columbus, OH; Dallas, TX; Des Moines, IA; Jersey City, NJ; Helena, MT; Houston, TX; Irvine, CA; Lansing, MI; Las Vegas, NV; Medford, MA; Miami, FL; Madison, WI; New York - Broadway, NY; Oakland, CA; Portland, OR; Phoenix, AZ; Portland, ME; Oak Brook, IL; San Diego, CA; Santa Clara, CA; Seattle, WA; Troy, NY; Middletown, CT; and North Andover, MA, presenting a dynamic hybrid schedule where employees will typically spend three (3) days per week working from a DNV office. Further details regarding rolespecific requirements will be shared during the interview process.

Other DNV offices may also be considered.

What You'll Do:

• As a Senior Machine Learning Engineer, Energy Systems, you will build and deploy scalable machine learning solutions that support utilities, renewable developers, grid operators, and clean energy programs.
• You will partner with data scientists, data engineers, analytics engineers, and software developers from the US and internationally to take models from experimentation to production, ensuring they are performant, reliable, and impactful in the energy domain. This position will coordinate and collaborate across multiple time zones.
• Your work will directly enable data-driven decisions that improve grid reliability, increase energy efficiency, accelerate decarbonization, and support the clean energy transition.
• Applications must clearly demonstrate relevant, hands-on experience in both ML engineering.
• Direct experience working with energy systems, utilities, grid operations, renewable energy, energy efficiency programs, or energy-market data is strongly preferred.