1

Machine Learning Power System Jobs (NOW HIRING)

Our ideal candidate has experience creating a working machine learning-powered project from the ground up, contributes innovative ideas and ingenious implementations to the team, and is capable of ...

Hive also offers turnkey software applications powered by proprietary AI models and datasets ... Machine Learning Role In order to execute our vision, we need to grow our team of best-in-class ...

Machine Learning Engineer

Seattle, WA · On-site

$120K - $180K/yr

Hive also offers turnkey software applications powered by proprietary AI models and datasets ... Machine Learning Role In order to execute our vision, we need to grow our team of best-in-class ...

Machine Learning Engineer

Seattle, WA · On-site

$120K - $180K/yr

Hive also offers turnkey software applications powered by proprietary AI models and datasets ... Machine Learning Role In order to execute our vision, we need to grow our team of best-in-class ...

Hive also offers turnkey software applications powered by proprietary AI models and datasets ... Machine Learning Role In order to execute our vision, we need to grow our team of best-in-class ...

next page

Showing results 1-20

Machine Learning Power System information

See salary details

$15

$27

$42

How much do machine learning power system jobs pay per hour?

As of Jun 4, 2026, the average hourly pay for machine learning power system in the United States is $27.49, according to ZipRecruiter salary data. Most workers in this role earn between $21.39 and $31.97 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Machine Learning Power System Engineer, and why are they important?

To excel as a Machine Learning Power System Engineer, you need a solid background in electrical engineering, power systems, and applied machine learning, often supported by a relevant degree such as electrical engineering or computer science. Familiarity with programming languages like Python, machine learning frameworks (e.g., TensorFlow, PyTorch), and power system simulation tools (e.g., PSS/E, PSCAD) is typically required. Strong analytical thinking, problem-solving skills, and the ability to communicate technical findings clearly are crucial soft skills in this role. These competencies enable effective development and implementation of intelligent solutions for optimizing and securing modern power grids.

How does a Machine Learning Power System engineer typically collaborate with other departments within an energy company?

Machine Learning Power System engineers frequently work closely with electrical engineers, data scientists, and IT teams to develop and implement predictive models for grid management and optimization. They coordinate with operations teams to understand data requirements and with software developers to deploy robust solutions. Effective collaboration ensures that machine learning models are both technically sound and practically applicable, leading to improved reliability and efficiency of power systems. This cross-functional teamwork is essential for integrating advanced analytics into traditional energy infrastructure.

What are machine learning power system engineers?

Machine learning power system engineers are professionals who apply machine learning techniques to improve the efficiency, reliability, and automation of electrical power systems. They develop algorithms to predict power demand, detect faults, optimize grid performance, and integrate renewable energy sources. These engineers often work with large datasets from smart grids, sensors, and meters to create predictive models that support decision-making for utilities and grid operators. Their work helps modernize power infrastructure and supports the transition to smarter, more sustainable energy systems.

What is the difference between Machine Learning Power System vs Power System Engineer?

AspectMachine Learning Power SystemPower System Engineer
Required CredentialsDegree in Electrical Engineering, Data Science, or related fields; knowledge of machine learning and power systemsDegree in Electrical Engineering or Power Engineering; focus on power systems analysis and design
Work EnvironmentResearch labs, utility companies, or tech firms applying AI to power gridsUtilities, consulting firms, or manufacturing plants managing power distribution
Industry UsageDeveloping AI models for grid optimization, fault detection, and predictive maintenanceDesigning, maintaining, and operating power systems and infrastructure

While both roles involve electrical power systems, Machine Learning Power System specialists focus on applying AI and machine learning techniques to optimize and analyze power grids. Power System Engineers primarily design and maintain traditional power infrastructure. The roles often overlap in utility companies but differ in technical focus and skill sets.

Postdoctoral Researcher: Machine Learning/Artificial Intelligence Applications to Power Systems

Postdoctoral Researcher: Machine Learning/Artificial Intelligence Applications to Power Systems

The National Renewable Energy Laboratory (NREL)

Golden, CO • On-site

$76.60K - $126.40K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 18 days ago


Job description

Posting Title
Postdoctoral Researcher: Machine Learning/Artificial Intelligence Applications to Power Systems
Location
CO - Golden
Position Type
Postdoc (Fixed Term)
Hours Per Week
40
Working at NLR
NLR is located at the foothills of the Rocky Mountains in Golden, Colorado is the nation's primary laboratory for energy systems research and development.
Join the National Laboratory of the Rockies (NLR), where world-class scientists, engineers, and experts are accelerating energy innovation through breakthrough research and systems integration. From our mission to our collaborative culture, NLR stands out in the research community for its commitment to an affordable and secure energy future. Spanning foundational science to applied systems engineering and analysis, we focus on solving complex challenges to deliver advanced, secure, reliable, and cost-effective energy solutions. Our work helps strengthen U.S. industries, support job creation, and promote national economic growth.
At NLR, you'll find a mission-driven environment supported by state-of-the-art facilities, multidisciplinary research teams, and strong collaborations with industry, academia, and other national laboratories. We offer robust professional development opportunities, and a competitive benefits package designed to support your career and well-being.
Job Description
The Grid Automation and Controls Group of the Power Systems and Engineering Center (PSEC) at the National Laboratory of the Rockies (NLR) is looking for an exceptional Ph.D. graduate to support research in the operation, control, modeling, and simulation of the power grid, while the power grid is transitioning to a low-carbon and high-renewable grid.
We are looking for a researcher who has solid background on machine learning with enough knowledge about power systems. The candidate will work on research projects that use machine learning (ML)/ artificial intelligence (AI) to solve power system problems, specially with the focus on Generative AI (GenAI) and Large Language Models (LLM). Ideal candidate is expected to have in-depth knowledge and extensive research experience related to GenAI and LLM, and can apply the AI knowledge to solve energy system problems. Ideal candidate should have solid programming skillset. Knowledge and experience about power systems is a plus.
The ideal candidate should be able to conduct research work with limited guidance from senior researchers, and also collaborate with project PI and other power system researchers from the same project team.
Basic Qualifications
Must be a recent PhD graduate within the last three years.
* Must meet educational requirements prior to employment start date.
Additional Required Qualifications
  • Relevant Ph.D. in Electrical Engineering or Computer Science or related fields.
  • Experience in one or more ML/AI techniques
  • Strong programming skill

Preferred Qualifications
  • In-depth knowledge in graph neural networks and reinforcement learning
  • Proven records of research experience related to power systems and power system optimization
  • Experience in natural language learning, generative AI, large language models, foundation models, etc.
  • Have a good fundamental knowledge of neural networks, state-of-the-art learning algorithms, and their applications to complex systems
  • Proficiency in using Python and machine learning/reinforcement learning packages
  • Experience in using high performance computers, Linux systems
  • With strong publication record

Job Application Submission Window
The anticipated closing window for application submission is up to 30 days and may be extended as needed.
Annual Salary Range (based on full-time 40 hours per week)
Job Profile: Postdoctoral Researcher / Annual Salary Range: $76,600 - $126,400
NLR takes into consideration a candidate's education, training, and experience, expected quality and quantity of work, required travel (if any), external market and internal value, including seniority and merit systems, and internal pay alignment when determining the salary level for potential new employees. In compliance with the Colorado Equal Pay for Equal Work Act, a potential new employee's salary history will not be used in compensation decisions.
Benefits Summary
Benefits include medical, dental, and vision insurance; short-term disability insurance*; pension benefits*; 403(b) Employee Savings Plan with employer match*; life and accidental death and dismemberment (AD&D) insurance; personal time off (PTO) and sick leave; and paid holidays. NLR employees may be eligible for, but are not guaranteed, performance-, merit-, and achievement- based awards that include a monetary component. Some positions may be eligible for relocation expense reimbursement.
* Based on eligibility rules
Badging Requirement
NLR is subject to Department of Energy (DOE) access restrictions. All employees must also be able to obtain and maintain a federal Personal Identity Verification (PIV) card as required by Homeland Security Presidential Directive 12 (HSPD-12), which includes a favorable background investigation.
Drug Free Workplace
NLR is committed to maintaining a drug-free workplace in accordance with the federal Drug-Free Workplace Act and complies with federal laws prohibiting the possession and use of illegal drugs. Under federal law, marijuana remains an illegal drug.
If you are offered employment at NLR, you must pass a pre-employment drug test prior to commencing employment. Unless prohibited by state or local law, the pre-employment drug test will include marijuana. If you test positive on the pre-employment drug test, your offer of employment may be withdrawn.
Submission Guidelines
Please note that in order to be considered an applicant for any position at NLR you must submit an application form for each position for which you believe you are qualified. Applications are not kept on file for future positions. Please include a cover letter and resume with each position application.
Equal Opportunity Employer
All qualified applicants will receive consideration for employment without regard basis of age (40 and over), color, disability, gender identity, genetic information, marital status, domestic partner status, military or veteran status, national origin/ancestry, race, religion, creed, sex (including pregnancy, childbirth, breastfeeding), sexual orientation, and any other applicable status protected by federal, state, or local laws.
Reasonable Accommodations
E-Verify www.dhs.gov/E-Verify For information about right to work, click here for English or here for Spanish.
E-Verify is a registered trademark of the U.S. Department of Homeland Security. This business uses E-Verify in its hiring practices to achieve a lawful workforce.