Application Guide

How to Apply for Software Engineer, Benchmarking

at Epoch AI

🏢 About Epoch AI

Epoch AI is a unique research team dedicated to investigating and forecasting the future of advanced AI, combining rigorous analysis with public-interest research. Working here means contributing to high-impact studies that inform policymakers, researchers, and the public about AI progress and risks.

About This Role

As a Software Engineer on the Benchmarking team, you will build and maintain the infrastructure that evaluates frontier AI models, directly shaping how the community measures AI capabilities. Your work will enable quick, reliable assessments of new models and help develop novel benchmarks that push the field forward.

💡 A Day in the Life

Your day might start by reviewing automated benchmark runs from overnight, troubleshooting any failures, and updating dashboards with results. You'd then collaborate with researchers to design a new evaluation task, implement it in the infrastructure, and run preliminary tests. Afternoons could involve code reviews, refining pipeline documentation, and discussing upcoming model releases to prioritize evaluations.

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Interview Prep

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🎯 Who Epoch AI Is Looking For

  • Experienced in building and maintaining benchmarking pipelines, with a track record of automating evaluations for ML models (e.g., using frameworks like HELM, LM Evaluation Harness, or similar).
  • Familiar with AI model evaluation methodologies, including metrics, dataset curation, and statistical analysis of model performance.
  • Comfortable collaborating with cross-functional teams of researchers, analysts, and engineers, and able to translate research questions into practical engineering solutions.
  • Proactive in identifying infrastructure bottlenecks and proposing improvements to scalability and reliability.

📝 Tips for Applying to Epoch AI

1

In your resume, highlight specific benchmarking projects you've built or contributed to, including the scale (number of models, tasks, compute resources) and impact on research.

2

Showcase your familiarity with Epoch AI's published work (e.g., on AI trends, compute scaling) and mention how your skills can support their ongoing projects.

3

When listing experience with AI models, be specific about which models you've evaluated (e.g., GPT-4, Llama 2, etc.) and the evaluation methodology used.

4

If you have open-source contributions to benchmarking tools (e.g., GitHub repos), include links and describe your role.

5

Tailor your cover letter to address how you would improve the speed and reliability of their existing benchmarking infrastructure, not just generic enthusiasm.

✉️ What to Emphasize in Your Cover Letter

['Emphasize your experience with benchmarking infrastructure at scale, especially for frontier AI models.', "Show understanding of Epoch AI's mission to forecast AI progress and how reliable benchmarks are critical to that mission.", 'Mention any experience developing novel evaluation ideas or benchmarks, as the role includes contributing to new benchmarks.', 'Highlight collaborative skills and ability to work with researchers to implement evaluation ideas.']

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🔍 Research Before Applying

To stand out, make sure you've researched:

  • → Read Epoch AI's recent reports on AI trends, compute scaling, and their methodology for estimating training compute.
  • → Explore their published benchmarks or evaluation frameworks (e.g., if they have open-source tools) and understand their design choices.
  • → Review the company's blog and publications to grasp their perspective on AI safety, forecasting, and the role of benchmarks.
  • → Familiarize yourself with key external benchmarks like MMLU, HumanEval, and HELM, and understand their limitations.
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💬 Prepare for These Interview Topics

Based on this role, you may be asked about:

1 Design a benchmarking pipeline for evaluating a new language model: steps, tools, metrics, and how to ensure reproducibility.
2 How would you handle a benchmark that shows inconsistent results across runs? Discuss debugging and statistical approaches.
3 Explain a time you improved the performance or reliability of an existing evaluation system.
4 Given a research paper proposing a new evaluation metric, how would you implement it in an existing infrastructure?
5 How do you stay updated on AI model releases and evaluation methodologies? What recent benchmark changes do you find important?
Practice Interview Questions →

⚠️ Common Mistakes to Avoid

  • Submitting a generic application that doesn't mention Epoch AI's specific research or your relevant benchmarking experience.
  • Overlooking the importance of reliability and reproducibility in your past work—be ready to discuss how you ensure consistent results.
  • Failing to demonstrate collaboration skills; this role requires working closely with researchers, so provide examples of cross-functional teamwork.

📅 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 Epoch AI!

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