You decide what "better" means.Models, agents, and product features all ship behind one question: did this actually get better? Without a strong evals function, the lab ships vibes. With one, every training run, every prompt change, every agent capability moves a number we trust - and the team makes decisions on real signal, not the loudest opinion in the room.
You'll build the eval harness for AGI - across model capability, agentic behavior, on-device performance, and end-user experience. You'll set the bar for what counts as "shipped" and protect it from the gravity of product deadlines.
🤩 Tasks you will own- The eval suites that gate every model and agent release - capability, behavior, regressions, and human-rated rubrics that catch what automated evals miss
- The dashboards and tooling that make researcher experiment loops fast and leadership decisions easy
- The bar - what counts as ready to ship, and how we know
🤚 Areas where you will assist- Research, by making sure what we measure is what we want
- Product engineers, by instrumenting real-user behavior on real devices
- Partnerships, by translating "did it get better" into language an OEM partner can hold us to
Skills you'll be expected to teach- How to measure non-deterministic systems - agent eval, tool use, long-horizon tasks, multilingual behavior
- How to push back on a metric that's being gamed without breaking the team
Skills you'll be expected to learn- On-device perf trade-offs and how they show up in real-user evals
- What QA-ing AI at OEM scale actually looks like
- The realities of shipping consumer agents to production partners
Timeline of successAfter 30 days - You've audited every eval we run today and produced a sharp doc on what's good, what's noise, and what's missing. You've fixed the most embarrassing gap.
After 60 days - You've stood up a new eval surface - agentic, on-device, or behavioral - and the team is making real decisions on its output. Researchers come to you before launching a run, not after.
After 90 days - Releases now ship against your eval bar, not a vibe-check. You've caught a regression that would have shipped, and cleared a launch the team was nervous about. You're shaping the research roadmap by surfacing where we're flat, where we're climbing, and where we're lying to ourselves.
CompensationCompetitive cash and meaningful equity. Top-tier relocation and immigration support. SF, in person.
How to applySend a link to an eval, benchmark, or measurement system you built - and one paragraph on what decision it changed. Plus your resume or LinkedIn. Every exceptional candidate hears back within 48 hours.
