AI Benchmark & Datasets Engineer – Internship

Role Overview

• Proactively identify, prioritize, and curate relevant public and client-driven benchmarks across our target use cases and markets.
• Evaluate candidate benchmarks for clarity, data quality, evaluation methodology, and fit with our 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.

Requirements

• Cover letter
• You were an ICPC World Finalist, or an IOI, IMO, IOAI or IPhO medalist in High School.
• You have published a research paper at an A-rated o A*-rated venue (according to ICORE).
• You have completed coding projects
• ideally with a GitHub repository showcasing previous work.
• You were an intern at a leading Machine Learning research center (e.g. at: Google Brain / Deepmind, Apple, Meta, Anthropic, Nvidia, MILA).
• You can get a warm recommendation from you university faculty member.
• Have experience with ML/LLM evaluation, data science, or technical product roles, ideally around benchmarks or experimentation.
• Are comfortable reading papers, leaderboards, and Github repos, and turning them into clear, repeatable benchmark specs.
• Can 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.
• Are respectful of others.
• Are fluent in English.

Benefits

• Join an intellectually stimulating work environment.
• During your internship, you will collaborate on a cutting edge research project.
• Be a pioneer: you get to work with a new type of "Live AI" challenges.
• Be part of one of an early-stage AI startup that believes in impactful research and foundational changes.