Application Guide

How to Apply for HPC User Support Engineer

at Argonne National Laboratory

🏢 About Argonne National Laboratory

Argonne National Laboratory is a premier U.S. Department of Energy research lab driving breakthroughs in climate solutions and sustainable technologies. Working here means contributing to cutting-edge science that addresses global challenges, with access to world-class facilities like the Aurora supercomputer. The lab's collaborative culture and commitment to innovation make it an inspiring place for engineers passionate about high-impact research.

About This Role

As an HPC User Support Engineer at the Argonne Leadership Computing Facility (ALCF), you'll be the bridge between researchers and one of the most powerful supercomputers in the world. Your work will directly enable breakthroughs in climate science, materials discovery, and AI by helping scientists debug, optimize, and scale their applications. This role combines deep technical troubleshooting with user education, making it ideal for someone who enjoys both solving complex problems and empowering others.

💡 A Day in the Life

Your day might start by triaging user tickets: a climate scientist struggling with MPI scaling, a materials researcher needing help with a Python library install. You'll debug application crashes, optimize I/O patterns, and then shift to updating documentation or leading a virtual training session on GPU programming. Afternoons often involve collaborating with system administrators to address user-reported issues or testing new software stacks for compatibility.

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Interview Prep

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🎯 Who Argonne National Laboratory Is Looking For

  • A problem-solver with hands-on experience in HPC environments, including job schedulers (Slurm), parallel file systems, and MPI/OpenMP programming.
  • Proficient in Python, C/C++, and shell scripting, with a track record of debugging and optimizing large-scale scientific applications.
  • Comfortable communicating with researchers from diverse backgrounds, translating technical concepts into clear guidance, and creating user-friendly documentation.
  • Familiar with AI/ML frameworks (TensorFlow, PyTorch) and their deployment on HPC systems, as the role explicitly supports AI workflows.

📝 Tips for Applying to Argonne National Laboratory

1

Tailor your resume to highlight specific HPC systems you've supported (e.g., Cray, IBM, or clusters with GPUs) and quantify impact (e.g., 'Reduced job failure rate by 20% through improved documentation').

2

In your cover letter, mention your experience with user support ticketing systems (e.g., ServiceNow, Jira) and give an example of a complex user issue you resolved.

3

Showcase any experience with containerization (Docker, Singularity) and version control (Git), as these are key for reproducible research on HPC.

4

If you have experience with AI/ML on HPC, explicitly describe how you helped users optimize training or inference on GPU clusters.

5

Research Argonne's current projects (e.g., Exascale Computing Project) and mention one in your application to demonstrate genuine interest.

✉️ What to Emphasize in Your Cover Letter

['Emphasize your ability to diagnose and resolve complex technical issues under time pressure, especially with large-scale parallel applications.', 'Highlight your experience creating documentation and training materials that non-experts find accessible.', "Mention any familiarity with Argonne's ALCF systems (e.g., Theta, Polaris, Aurora) or similar DOE HPC facilities.", 'Stress your collaborative mindset and enthusiasm for supporting a diverse user community with varying skill levels.']

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🔍 Research Before Applying

To stand out, make sure you've researched:

  • → Familiarize yourself with ALCF's current supercomputers: Theta (Intel Xeon Phi), Polaris (NVIDIA A100), and the upcoming Aurora (Intel Xe GPUs).
  • → Read about Argonne's Exascale Computing Project (ECP) and how ALCF supports climate, biology, and materials science.
  • → Look into the ALCF's AI Testbed and their work on integrating machine learning with traditional simulation.
  • → Review recent ALCF user success stories or case studies to understand the types of research you'd support.

💬 Prepare for These Interview Topics

Based on this role, you may be asked about:

1 Describe a time you helped a user debug a parallel application that was crashing or performing poorly. What steps did you take?
2 How would you approach onboarding a new user who has never used an HPC system? Walk us through your process.
3 Explain how you would optimize a Python-based AI workflow that is I/O bound on a Lustre file system.
4 How do you stay current with HPC technologies and AI frameworks? Give an example of a new tool you learned recently.
5 Tell us about a time you had to communicate a complex technical concept to a non-technical stakeholder.
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⚠️ Common Mistakes to Avoid

  • Don't focus solely on your own research or coding projects without showing how you've helped others (user support is a service role).
  • Avoid generic statements like 'I love HPC' without demonstrating specific knowledge of schedulers, parallel debugging, or user training.
  • Don't overlook the AI aspect; even if you're not an expert, show willingness to learn and any relevant experience with ML frameworks.

📅 Application Timeline

This position is open until filled. However, we recommend applying as soon as possible as roles at mission-driven organizations tend to fill quickly.

Typical hiring timeline:

1

Application Review

1-2 weeks

2

Initial Screening

Phone call or written assessment

3

Interviews

1-2 rounds, usually virtual

✓

Offer

Congratulations!

Ready to Apply?

Good luck with your application to Argonne National Laboratory!

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