Graduate Summer Intern – HPC Operational Analytics
Listed on 2026-06-04
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Software Development
Data Engineer, Data Scientist, Software Engineer
Posting Title
Graduate Summer Intern – HPC Operational Analytics
LocationRemote
Position TypeIntern (Fixed Term)
Hours Per Week40
Working at NLRJoin the National Laboratory of the Rockies (NLR), where world‑class scientists, engineers, and experts are accelerating energy innovation through breakthrough research and systems integration. NLR focuses on foundational science and applied systems engineering to deliver advanced, secure, reliable, and cost‑effective energy solutions that strengthen U.S. industries, support job creation, and promote economic growth.
Job DescriptionThe Advanced Computing program at NLR is looking for a graduate student researcher in High‑Performance Computing (HPC) Operational Analytics. The researcher will assist in building the data foundation and AI‑driven intelligence infrastructure for the facility, focusing on optimizing the operations of the Kestrel supercomputer.
Responsibilities- Develop scalable Python pipelines to ingest and analyze diverse HPC telemetry
- Build and evaluate machine learning models to characterize complex HPC workloads
- Assist in developing automated, agentic AI workflows
- Process and package operational data
- Write robust, test‑driven code and document data schemas within a collaborative Git repository
Minimum cumulative GPA of 3.0.
Undergraduate:
Must be enrolled full‑time in a bachelor’s program at an accredited institution.
Post‑Undergraduate:
Must have earned a bachelor’s degree within the past 12 months; internship up to one year.
Graduate:
Must be enrolled full‑time in a master’s program at an accredited institution.
Post‑Graduate:
Must have earned a master’s degree within the past 12 months; internship up to one year.
Graduate + PhD:
Completed master’s degree and currently enrolled in a PhD program at an accredited institution.
Must meet educational requirements prior to employment start date.
AdditionalRequired Qualifications
- Proficient in Python and the data science/analytics stack
- Comfortable operating in a Linux command‑line environment
- Software engineering fundamentals, including Git and unit testing
- Experience running code on HPC systems or using workload managers (e.g., Slurm)
- Experience handling large‑scale data formats such as time‑series telemetry, system logs, or text data
- Familiarity with integrating Large Language Model APIs into software workflows or building agentic systems
- Basic understanding of supercomputing architecture or facility operations
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)$44,500 – $71,200
Benefits SummaryBenefits include medical, dental, and vision insurance; 403(b) Employee Savings Plan with employer match*; and sick leave as required by law. Internships projected to be less than 20 hours per week are not eligible for medical, dental, or vision benefits.
* Based on eligibility rules.
Badging RequirementAll employees must obtain and maintain a federal Personal Identity Verification (PIV) card as required by Homeland Security Presidential Directive 12. Interns extending beyond six months will be subject to this requirement.
Drug Free WorkplaceNLR is committed to maintaining a drug‑free workplace in accordance with federal law. A pre‑employment drug test will be required; a positive test may result in withdrawal of the employment offer.
Submission GuidelinesPlease include a cover letter and résumé with each application. Applications are not kept on file for future positions.
Equal Opportunity EmployerAll qualified applicants will receive consideration for employment without regard to age, 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, or any other protected status under applicable law.
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