Senior Machine Learning Engineer - Energy
About The Position
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 role‑specific 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.
Requirements
- A bachelor’s degree is required; equivalent experience may be considered for relevance of discipline
- Minimum 5 years of hands-on experience building and deploying machine learning models in production
- Demonstrated Azure cloud experience, including one or more of the following: Azure Machine Learning Azure Databricks or Spark Azure DevOps (CI/CD)
- Strong proficiency in: Python (scikit-learn, pandas, numpy, MLflow, etc.) PySpark (Databricks) ML Ops tooling and model deployment frameworks SQL
- Experience working collaboratively with cross-functional engineering and analytics teams
- Ability to manage multiple concurrent projects
- Excellent written and verbal communication skills in English.
- We conduct pre-employment drug and background screening.
Nice To Haves
- Experience supporting ML solutions in the energy industry, including utilities, grid operations, renewables, demand-side programs, or energy market
- Experience with time-series models, anomaly detection, clustering, or forecasting
- Understanding of interoperability, fairness, model governance, and responsible AI
Benefits
- Generous paid time off (vacation, sick days, company holidays, personal days)
- Multiple Medical and Dental benefit plans to choose from, Vision benefits
- Spending accounts – FSA, Dependent Care, Commuter Benefits, company-seeded HSA
- Employer-paid, therapist-led, virtual care services through Talkspace
- 401(k) with company match
- Company provided life insurance, short-term, and long-term disability benefits
- Education reimbursement program
- Flexible work schedule with hybrid opportunities
- Charitable Matched Giving and Volunteer Rewards through our Impact Program
- Volunteer time off (VTO) paid by the company
- Career advancement opportunities
- Benefits vary based on position, tenure, location, and employee election
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Number of Employees
501-1,000 employees
