ML and Optimization Engineer

National Renewable Energy Laboratory; Golden (CO); On-site; USD 100,000 - 181,000; Full time

Job summary

The National Laboratory of the Rockies (NLR) in Golden, CO seeks an ML and Optimization Engineer to design, develop, and test software supporting energy research and high-performance computing. You will work across AI/ML and optimization to build production-ready systems that operate in real‑world, constrained environments.

You should have strong software skills, experience with PyTorch/TensorFlow, and the ability to communicate complex ideas across teams.

Qualifications

• Bachelor's degree with 5+ years of experience or equivalent relevant education/experience.
• Master's degree with 3+ years of experience or equivalent relevant education/experience.
• PhD or equivalent relevant education/experience.

Responsibilities

• Design, develop, and rigorously test software applications and components using best practices and modern technologies.
• Evaluate AI models and translate findings into production‑ready systems.
• Collaborate across teams to ensure robust, scalable solutions in constrained environments.

Skills

pytorch

tensorflow

Python

JavaScript/TypeScript

C/C++

Education

Bachelor's degree

Master's degree

PhD

Job description

ML and Optimization Engineer . Location CO - Golden . Position Type Limited Term (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.

Job Description

The National Laboratory of the Rockies (NLR) is seeking an accomplished full-time software engineer with experience in AI, optimization, applied mathematics, and high-performance computing within the Computational Science Center (CSC) with a focus on advancing energy innovation by supporting world class research and leadership in computational science. In the CSC, we integrate discovery science, engineering, and mission delivery to translate breakthrough research into operational capabilities, with core strengths in high‑performance computing, AI/ML, modeling and simulation, and visualization. We steward state‑of‑the‑art supercomputing and data facilities, secure research environments (including classified spaces), and specialized testbeds that enable end‑to‑end development and red‑team evaluation. NLR collaborates across DOE program offices and with the defense and intelligence communities, other federal agencies, universities, and industry through public–private partnerships and technology transition pathways, while fostering a culture of scientific excellence, operational rigor, and responsible research. In this position you will design, develop, and rigorously test software applications and components, utilizing best practices and cutting‑edge technologies to pave the way for innovative, collaborative, and hybrid computing solutions supporting NLR’s mission critical research projects. Candidates will work across the full research-to-implementation stack including designing and evaluating AI models, translating findings into production‑ready systems, and occasionally diving into the quantitative underpinnings that make intelligent systems behave reliably in constrained, real‑world settings. This isn't a role where AI and optimization live in separate silos. Candidates are expected to reason across both. Strong software engineering fundamentals are the foundation. Beyond that, candidates should have meaningful experience with modern AI/ML such as deep learning, probabilistic modeling, large-scale inference, foundation models, and applied AI in a specific domain. Candidates understand the difference between a benchmark result and a deployed system, and know how to close that gap. On the optimization side, candidates are expected to be comfortable with formulating and reasoning about constrained optimization problems. Candidates should possess a willingness to go deep when the work demands it. Candidates should have a strong technical background, good work ethic, experience in leadership and mentorship, and be comfortable to quickly learn and apply new technologies, as the role will include self‑starting and performing technical tasks independently. The role also requires collaboration and effective communication with peers, mentors, and team members. The successful candidate will not shy away from tackling challenges, but rather, demonstrate eagerness to engineer creative solutions. In this vein, the candidate should have a high degree of curiosity, excitement to work on a team, and ability to adapt to needs of different projects and challenges by gaining and utilizing new skills in support of research goals.

Basic Qualifications

• Professional Level III - Relevant Bachelor's Degree and 5 or more years of experience or equivalent relevant education/experience.
• Or, relevant Master's Degree and 3 or more years of experience or equivalent relevant education/experience.
• Or, relevant PhD or equivalent relevant education/experience.
• Professional Level II - Relevant Bachelor's Degree and 2 or more years of experience or equivalent relevant education/experience.
• Or, relevant Master's Degree or equivalent relevant education/experience.
• * Must meet educational requirements prior to employment start date.

Additional Required Qualifications

• Demonstrated experience with pytorch and tensorflow.
• Demonstrated experience writing clean, efficient, and maintainable code, adhering to coding standards and guidelines.
• Demonstrated experience designing, developing, and testing software applications and components using best practices and modern technologies.
• Demonstrated knowledge in Python and at least one other major programming language, such as JavaScript/TypeScript,, Java, or C/C++.
• Ability to communicate complex technical documentation of software architecture, design decisions, and technical specifications with precision and clarity, providing valuable insights for team collaboration and future reference.
• Effective communication skills to participate in code reviews, provide constructive feedback to ensure code quality and consistency across the team.
• Openness to alternative methods and willingness to adjust plans as circumstances evolve.
• Works effectively with others toward a common goal, valuing differing perspectives and contributions.
• Demonstrated experience in a research lab environment including technical publication experience, experience in writing proposals, ability to context shift and be able to support multiple projects at once, experience supporting junior‑level researchers and developers.

Preferred Qualifications

• First-author publication(s)
• Open-source software release(s)
• Ability to obtain a clearance .

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: IT Professional III / Annual Salary Range: $100,400 - $180,700

Job Profile: IT Professional II / Annual Salary Range: $83,600 - $150,500

Benefits Summary

• Benefits include medical, dental, and vision insurance; pension benefits*; 403(b) Employee Savings Plan with employer match*; and sick leave (where required by law).
• 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.

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.

About the Laboratory

The National Laboratory of the Rockies (NLR) is the U.S. Department of Energy's primary national laboratory for critical minerals, energy innovation, and energy security. With locations in Golden and Boulder, Colorado, Fairbanks, Alaska, and a satellite office in Washington, D.C., NLR bridges foundational research with practical applications to develop and bring to scale new energy materials and technologies that lower energy costs, drive economic growth, and deliver abundant and reliable energy.