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When we released Holo4 on 28 September, we published every trajectory behind its public benchmark scores at trajectories.hcompany.ai. For OSWorld that's 369 desktop tasks, each run 3 times, with the steps, tokens and time of every attempt. This role builds and runs the evaluation framework that produces runs like these.
H builds computer-use agents and the models behind them. Developers use them through a managed API, and our forward deployed engineers take them into enterprise workflows.
What this team owns
The evaluation framework: orchestration, runtimes and observability. Researchers and forward deployed engineers bring the benchmarks, across web apps, desktop applications and the command line. Your job is to make the framework that runs them reliable, fast and cheap, and to make adding a new one quick. Research uses the results to choose checkpoints and decide whether a model ships. Product and the forward deployed engineers use them to measure agents on customer workflows. It carries roughly 50 benchmarks now. That number should be between 100 and 200 soon, and the framework has to keep up.
What you'd be doing
- Integration support for researchers and forward deployed engineers bringing in a benchmark, with a shorter path each time.
- Setting the standard for how a benchmark enters the framework, and building the checks that enforce it.
- Scheduling and observability, so cluster capacity isn't left idle while evaluation jobs queue.
- Reproducible results across trials, so a release decision rests on numbers that hold.
- Whatever stack a benchmark calls for. One week that's cluster tuning; the next it's a browser extension or desktop environments.
- Time with customers, from single developers to large companies, to find out what they want measured, then automating it so the results flow back into our harnesses and models.
The first few months
By 3 months you'll have helped researchers or forward deployed engineers integrate 5 benchmarks, and started fixing what slows the framework down. By 6 months one part of it is yours, for example scaling the runs, observability, or a group of related benchmarks, and a release will have gone out on your numbers. By 12 months you'll know the design and trade-offs of the whole evaluation system, and be the person the rest of H asks about evaluations.
Who you'd work with
Ceiran Chapman, our VP Engineering, is hiring for this role. You'd join the evaluation team. The people relying on your work day to day are H's researchers and forward deployed engineers.
What we think it takes
You do not need a background in machine learning. We'll work that out with you. If you match most of this but not all of it, apply anyway.
How we hire
A 30 minute call with our Talent team, a 60 minute technical challenge, a 60 minute system design interview, and a 30 minute final conversation with Ceiran. About 3.5 hours in total.
Practicalities
Paris posting: Hybrid in Paris. That means 3 office days a week and a London trip about once every 4 to 6 weeks. There is a London posting for the same role. We offer a competitive package.
Если просят выйти из iCloud, прислать код из SMS, запустить или установить что-то, перевести деньги — не соглашайся: это мошенничество.
Спроси Хайрика про вакансию
Сверит с твоим резюме, подскажет вилку и вопросы на собесе.