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Graduate Summer Intern – AI/ML Software Developer

Posting Title

Graduate Summer Intern – AI/ML Software Developer

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Location

CO - Golden

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Position Type

Intern (Fixed Term)

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Hours Per Week

40

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Working at NREL

The National Renewable Energy Laboratory (NREL), located at the foothills of the Rocky Mountains in Golden, Colorado is the nation's primary laboratory for research and development of renewable energy and energy efficiency technologies.

Join a team of world-class scientists, engineers, and visionaries dedicated to shaping the world’s energy future through cutting-edge research and innovation. From our vision to our NREL community, we are unique in the research community. We are focused on impact. From our work in basic sciences to systems engineering, analysis, demonstration, and deployment, we are focused on solving market-relevant problems that result in advanced, secure, reliable, and affordable energy systems. We are trusted clean energy leaders, developing cost-saving solutions that make U.S. industries more competitive, and support job creation and economic growth across rural and urban communities.

At NREL, we offer a unique, mission-driven work environment with cutting-edge facilities and multidisciplinary research teams. NREL's environment offers strong partnerships with industry, academia, and other national laboratories, as well as professional development opportunities and a competitive benefits package for employees.

Learn about NREL’s critical objectives: NREL's Mission and Vision.

Job Description

The graduate intern will be part of a larger team developing sensor placement and optimization software tools for modern distribution power systems integrated with clean energy resources such as Photovoltaics, batteries, EV Charging Stations, and electric vehicles. The intern will contribute to the development of deep learning models such as Bayesian neural networks, graph neural networks, probabilistic semantic graphs, and Generative AI to detect anomalies such as missing data, bad data, and communications failure in sensor data. Development of data driven forecasting and disaggregation models and validation of both centralized and distributed state estimation algorithms.

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Basic Qualifications

Minimum of a 3.0 cumulative grade point average.

Undergraduate: Must be enrolled as a full-time student in a bachelor’s degree program from an accredited institution.
Post Undergraduate: Earned a bachelor’s degree within the past 12 months. Eligible for an internship period of up to one year.

Graduate: Must be enrolled as a full-time student in a master’s degree program from an accredited institution.
Post Graduate: Earned a master’s degree within the past 12 months. Eligible for an internship period of up to one year.
Graduate + PhD: Completed master’s degree and enrolled as PhD student from an accredited institution.

Please Note:
• Applicants are responsible for uploading official or unofficial school transcripts, as part of the application process.
• If selected for position, a letter of recommendation will be required as part of the hiring process.
• Must meet educational requirements prior to employment start date.

* Must meet educational requirements prior to employment start date.

Additional Required Qualifications

Preferred Qualifications

  • Experience in deep learning models, Bayesian neural networks, graph neural network models, and probabilistic semantic graphs.
  • Experience in the formulation of mixed-integer optimization problems and open-source solvers for sensor placement in distribution systems.
  • Demonstrated experience in programming languages such as Python and MATLAB.
  • Experience with open-source, collaborative software development and use of tools such as GitHub or GitLab for project management and version control.

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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: / Annual Salary Range: $43,700 - $69,900

NREL 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; 403(b) Employee Savings Plan with employer match*; and sick leave (where required by law). NREL 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. Internships projected to be less than 20 hours per week are not eligible for medical, dental, or vision benefits.

* Based on eligibility rules

Badging Requirement

NREL 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. Intern assignments extending beyond six months will be subject to this requirement.

Drug Free Workplace

NREL 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 NREL, 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 NREL 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.

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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. 

Average salary estimate

$56800 / YEARLY (est.)
min
max
$43700K
$69900K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Graduate Summer Intern – AI/ML Software Developer, National Renewable Energy Lab

If you're a passionate graduate looking to kickstart your career in AI and Machine Learning, the Graduate Summer Intern – AI/ML Software Developer position at the National Renewable Energy Laboratory (NREL) in Golden, CO is tailored for you! Imagine working at the foothills of the magnificent Rocky Mountains alongside world-class scientists and engineers who are committed to creating a sustainable energy future. In this role, you'll dive into developing cutting-edge software tools for sensor placement within modern power systems. Your contributions will involve incorporating clean energy resources like solar panels and electric vehicles, thereby directly impacting how energy is consumed and optimized. As a key player on our team, you will help implement advanced deep learning models such as Bayesian and graph neural networks to detect issues within sensor data. This isn’t just about coding; it’s about solving market-relevant problems in energy systems that affect real communities. To thrive as a Graduate Summer Intern, you'll benefit from a flexible and supportive work environment that offers fantastic mentorship opportunities, access to pioneering research, and the chance to make your mark in the world of renewable energy. At NREL, we believe in the synergy of science and innovation—so, if you’re ready to take your first step into the professional realm while contributing to a greater cause, this is the internship for you!

Frequently Asked Questions (FAQs) for Graduate Summer Intern – AI/ML Software Developer Role at National Renewable Energy Lab
What are the key responsibilities of the Graduate Summer Intern – AI/ML Software Developer at NREL?

As a Graduate Summer Intern – AI/ML Software Developer at the National Renewable Energy Laboratory, your responsibilities will include developing sensor placement and optimization software tools tailored for modern distribution power systems. You'll work on applying advanced deep learning models to analyze and enhance data integrity, while also focusing on forecasting and state estimation algorithms.

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What qualifications are required for the Graduate Summer Intern position at NREL?

To qualify for the Graduate Summer Intern – AI/ML Software Developer role at NREL, applicants must be enrolled as full-time students in relevant master's or PhD programs, or have recently completed such degrees. A minimum GPA of 3.0 is essential, and you should ideally have experience with deep learning models, programming languages like Python or MATLAB, and collaborative software development practices.

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What kind of projects can I expect to work on as a Graduate Summer Intern at NREL?

During your internship as a Graduate Summer Intern – AI/ML Software Developer at NREL, you will engage in projects that involve implementing deep learning models to manage sensor data for energy efficiencies. This could include exploring algorithms for anomaly detection and data forecasting, critical for modern energy systems relying on renewable resources.

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What software development tools and languages should I be proficient in for this internship at NREL?

For the Graduate Summer Intern – AI/ML Software Developer position, proficiency in programming languages such as Python and MATLAB is highly preferred. Experience with open-source software development tools like GitHub or GitLab for version control and project management will also be advantageous for your success in this internship.

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What professional development opportunities are available for Graduate Summer Interns at NREL?

At NREL, the Graduate Summer Intern – AI/ML Software Developer will experience a unique environment focused on professional development. This includes exposure to cutting-edge projects, mentorship from experienced researchers, and potential networking opportunities that can lead to future career paths in renewable energy and technology.

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Common Interview Questions for Graduate Summer Intern – AI/ML Software Developer
Can you explain a deep learning project you've worked on?

In your response, outline the project objectives, your specific contributions, and the technologies you employed. Highlight key challenges you faced and how you overcame them, demonstrating both your technical skills and problem-solving capabilities.

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What attracted you to apply for the Graduate Summer Intern – AI/ML Software Developer role at NREL?

Focus on your passion for renewable energy and AI/ML technologies. Discuss how NREL's mission aligns with your personal and professional goals, and how you see yourself contributing towards innovative solutions in energy systems.

Join Rise to see the full answer
How do you approach learning new programming languages or technologies?

Discuss your learning strategies, such as utilizing documentation, online courses, and hands-on practice. Provide examples of how this approach helped you quickly become proficient in a new language or tool required for a project.

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Describe your experience with collaborative software development.

Share your involvement in team projects where you used tools like GitHub for version control. Highlight your ability to communicate effectively with peers and navigate through project iterations smoothly.

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What is your understanding of Bayesian neural networks?

Explain the concept, emphasizing how Bayesian approaches differ from traditional neural networks by incorporating uncertainty into their predictions. Discuss any relevant experiences you have had in applying this method.

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Can you give an example of optimizing sensor placement in a power system?

Provide a specific scenario where you used optimization techniques to improve sensor placements. Talk about the impact it had on system efficiency and reliability, showcasing your analytical skills.

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How do you handle setbacks or challenges during a project?

Demonstrate resilience and problem-solving skills by sharing a specific instance where a challenge arose, how you approached valid alternatives, and what you learned from the experience.

Join Rise to see the full answer
What do you think is the biggest challenge facing clean energy systems today?

Share your insight into current trends and issues in the clean energy sector, such as integration of renewable sources or grid stability. Discuss potential solutions and how your background can contribute to addressing these challenges.

Join Rise to see the full answer
Explain the importance of data validation in AI models.

Discuss how data validation ensures the integrity and accuracy of model training. Connect this to your past experiences and emphasize your understanding of maintaining high-quality data standards.

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How would you approach understanding the requirements for a new software tool?

Discuss your method of gathering requirements from stakeholders, including conducting interviews or surveys. Highlight how you translate their needs into technical specifications and ensure alignment before development.

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Full-time, on-site
DATE POSTED
March 29, 2025

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