Senior Machine Learning Engineer

EVOLVE Intelligence accelerates 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 build intelligent, scalable ML solutions that support demand side management, demand flexibility, and transportation electrification programs!

As a Senior Machine Learning Engineer, you will develop and deploy robust machine learning systems that power analytics, optimize energy efficiency, and advance the clean energy transition. You’ll work closely with data scientists, data engineers, analytics engineers, and software developers to take models from experimentation to production, ensuring they are performant, maintainable, and impactful.

Your work will play a vital role in enabling utilities and clean energy programs to make data-driven decisions that reduce emissions, meet goals, and shape a sustainable future.

This role is based at our any DNV office in US, presenting a dynamic hybrid schedule where employees will typically spend three (3) days per week working from either a DNV office or client location/site. Further details regarding role-specific requirements will be shared during the interview process.

What You'll Do:

• Develop & Deploy ML Models: Design, train, and productionize models using structured and unstructured datasets
• Operationalize ML Workflows: Build and maintain ML pipelines using Databricks, Azure ML, MLflow, or similar platforms
• Collaborate with Data & Software Teams: Work closely with data engineers and software developers to integrate models into end-user applications and systems
• Monitor & Improve Model Performance: Implement monitoring, retraining strategies, and evaluation metrics to ensure ongoing model accuracy and stability
• Automate & Scale: Leverage cloud-native tools to deploy scalable ML services and APIs
• Champion Best Practices: Contribute to team-wide ML Ops, version control, testing, and documentation practices
• Mentor & Share Knowledge: Guide junior engineers and in best practices, reviewing code and modeling approaches
• Explore & Innovate: Research and experiment with new modeling techniques that enhance predictive performance and operational impact

• 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**

For California, Washington, New York, Washington, D.C., Illinois, and Maryland: “DNV provides a reasonable range of compensation for this role. The actual compensation is influenced by a wide array of factors, including but not limited to skill set, level of experience, and specific location. For the states of California, Washington, New York, Washington, D.C., Illinois, and Maryland only, the starting pay range for this role is $145,000 - $165,000.

DNV is committed to ensuring equal employment opportunity, including providing reasonable accommodations to individuals with disabilities. US applicants with a physical or mental disability who require reasonable accommodation for any part of the application or hiring process may contact the North America Recruitment Department (hrrecruitment.northamerica@dnv.com). Information received relating to accommodation will be addressed confidentially.

For more information 
https://www.eeoc.gov/know-your-rights-workplace-discrimination-illegal

What is Required:

• Bachelor’s degree
• Minimum of 3 to 5 years’ experience building and deploying machine learning models in production
• Demonstrated ability to manage multiple projects and collaborate across cross-functional teams
• Proficient in:
  • Python (including libraries such as scikit-learn, pandas, numpy, MLflow, etc.)
  • Pyspark (we leverage Databricks)
  • ML Ops tooling and model deployment frameworks
  • SQL (e.g., T-SQL, PostgreSQL)
• Strong written and verbal English communication skills
• We conduct pre-employment drug and background screening

What is Preferred:

• Bachelor’s degree in Computer Science, Machine Learning, Data Science, or a related field (or equivalent experience)
• Experience in the Energy Industry or with clean energy applications
• Familiarity with Azure ML, Azure DevOps, Azure Containers, and ML Ops workflows
• Experience with time-series forecasting, classification, or clustering techniques
• Exposure to distributed computing frameworks such as Apache Spark
• Understanding of model interpretability, fairness, and responsible AI principles
• Experience working within a collaborative DevOps environment

**Immigration-related employment benefits, for example visa sponsorship, are not available for this position** 

About Energy Systems
We help customers navigate the complex transition to a decarbonized and more sustainable energy future. We do this by assuring that energy systems work safely and effectively, using solutions that are increasingly digital. We also help industries and governments to navigate the many complex, interrelated transitions taking place globally and regionally, in the energy industry.