Mercor10 дней назад
Research Scientist, APEX Benchmarks
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РЫНОК
16 333 ₽медиана по профессии
Data Scientist · 215 вакансий с указанной зарплатой
5 000половина предложений: 13 167–21 846120 000
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Полная занятостьОфис
Обязанности
- 01Benchmark design: Decide what the next APEX benchmark should measure, based on frontier model performance, saturation of existing evals, and where economically valuable work is still out of reach. Own the task taxonomy, difficulty calibration, contamination controls and statistical design.
- 02Dataset design: Design expert-built datasets and grading rubrics at scale — deciding what makes a task hard, what makes a grade defensible, and how to hold quality while thousands of experts produce work in parallel.
- 03Measurement rigor: Set the standard for how we report results: confidence intervals, inter-rater agreement, human vs. model-as-judge calibration, held-out splits, and the failure analysis that explains why a model scored the way it did.
- 04Partnerships: Work with academic collaborators and industry partners (as we did with Cognition on APEX-SWE) to co-design benchmarks and get them adopted.
- 05External research voice: Publish — arXiv papers, open datasets, blog posts, conference talks, leaderboard releases — and represent Mercor’s research in conversations with frontier labs, customers and the press.
- 06Translate results into narrative: Turn benchmark findings into clear arguments about the ROI of expert-curated data, for technical reports, customer conversations and go-to-market material.
- 07Cross-functional work: Partner with data operations, engineering, product and strategy to take a benchmark from design to production, and to surface research findings that shape the company roadmap.
- 08Stay at the frontier: Track the LLM evaluation literature and bring what’s good into how Mercor builds benchmarks.
Требования
- 01Research background in evaluation: Strong applied or academic research background in LLM evaluation, benchmarking, NLP or a related field, with a track record of rigorous experimental design.
- 02Judgment about what to measure: You can look at a frontier model’s behavior and identify the measurement that would actually be informative, rather than the one that is easiest to build.
- 03Statistical rigor: You reason carefully about sampling, variance, contamination and grader reliability, and you don’t ship a number you can’t defend.
- 04Hands-on: Strong coding skills. You can build an eval harness, run the experiment and analyze the results yourself.
- 05Exceptional communication: You can present complex technical findings clearly to frontier lab researchers and to non-technical audiences, in writing and in person.
- 06Comfort with ambiguity: You’ve operated in fast-moving, cross-functional environments where the problem space is not yet defined.
- 07Interest in the commercial side: Genuine curiosity about GTM strategy, startup dynamics and the business of AI data — this role sits close to all three.
- 08In-person: You are excited to work from our San Francisco office five days a week in a high-intensity, high-ownership environment.
Условия
- 01Work in-person five days a week in our San Francisco, NYC, or London offices.
- 02High-intensity, high-ownership environment.