AI Benchmark & Datasets Engineer/Researcher Internship
P
PathwayAI
EU, UK, US, or CanadaInternship
Salary not disclosed
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Job Details
- Languages
- English
Requirements
- Experience with ML/LLM evaluation, data science, or technical product roles, ideally around benchmarks or experimentation.
- Comfortable reading papers, leaderboards, and Github repos, and turning them into clear, repeatable benchmark specs.
- Ability to talk comfortably with both engineers and customers, and translate between technical detail and business value.
- Care about high‑quality data, reproducible experiments, and crisp documentation.
- Respectful of others.
- Fluent in English.
- ICPC World Finalist, or an IOI, IMO, IOAI or IPhO medalist in High School.
- Published a research paper at an A-rated or A*-rated venue (according to ICORE).
- Completed coding projects - ideally with a GitHub repository showcasing previous work.
- Interned at a leading Machine Learning research center (e.g. at: Google Brain / Deepmind, Apple, Meta, Anthropic, Nvidia, MILA).
- Can get a warm recommendation from university faculty member.
Responsibilities
- Proactively identify, prioritize, and curate relevant public and client-driven benchmarks across target use cases and markets.
- Evaluate candidate benchmarks for clarity, data quality, evaluation methodology, and fit with the model roadmap.
- Run benchmarks with baseline models to validate setup, uncover edge cases, and de-risk R&D runs.
- Hand off “benchmark-ready” packages to R&D (specs, data, evaluation scripts, expected metrics, constraints).
- Maintain a shared vocabulary and documentation around benchmarks, datasets, and evaluation formats that GTM and R&D can both use.
- Track and organize benchmark results, model leaderboards, and “what good looks like” for different customers and scenarios.
- Contribute to demos and public‑facing proof points based on benchmark outcomes.
- Play a key role in defining and driving the benchmarking process for AI model evaluation.
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