A national energy research laboratoryHiring

Graduate Intern, Power Data Analysis for AI Data Centers

  • Remote, United States
  • Internship
  • Entry-level
  • Posted 6 days ago
In one line

Graduate Intern, Power Data Analysis for AI Data Centers is an entry-level internship remote role in the United States at a national energy research laboratory.

About the role

A small digital twins and scalable workflows group runs the project on a supercomputer, measuring rack power during training, inference and agentic runs so models can predict behavior for workloads not yet measured.

At a glance

Pay
Not stated in the posting
Remote scope
Remote, United States
Seniority
Entry-level
Employment
Internship
Skills
Data analysis, GPU telemetry, Profiling, Visualization
Posted
29 Oct 2026
Last checked
3 Nov 2026

What you will do

  • Go through power readings from each AI experiment and spot anomalies and data quality problems in a visualization workbench.
  • Hand-label power ramps, load steps and other key events under a written labeling protocol.
  • Trace unexplained behavior by tying power data to GPU telemetry, profiling data, job logs and system config.
  • Design, build and test an automated detector for ramps and anomalies, trained on your labeled data.
  • Share results in technical reports, papers and conference talks.

What they look for

  • Enrolled full time in a relevant degree program with a cumulative GPA of at least 3.0.
  • Strong data analysis skills and real curiosity about energy, computing and the grid.
  • Careful, detail-minded approach to reviewing measurements.

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Questions about this job

Is this job fully remote, and from where?

Yes, it is listed as remote, aimed at candidates in the United States.

What does this job pay?

No pay range is stated in the posting.

What experience is needed?

It is an entry-level role. The posting asks for: enrolled full time in a relevant degree program with a cumulative GPA of at least 3.0; strong data analysis skills and real curiosity about energy, computing and the grid; careful, detail-minded approach to reviewing measurements. Skills it names include Data analysis, GPU telemetry, Profiling, Visualization.

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