AI Researcher

Tasks you will own

• One or more model capabilities end-to-end — from data mixture and training objective through eval and shipping into a production on-device runtime
• The experiment design and writeups that compound across the team — kill what doesn't move the metric, double down on what does
• A training workstream with a clear success metric and a checkpoint that ships

Areas where you will assist

• Infra and product engineers, by turning research wins into shipped capabilities
• Partnerships, by telling them honestly what's possible at the next device refresh and what's not
• Other researchers, by reading their code and making theirs easier to read

Skills you'll be expected to teach

• The training techniques that matter most for our regime — distillation from frontier teachers, MoE at small scale, speculative decoding, KV cache compression
• How to design experiments that move a number you actually care about

Skills you'll be expected to learn

• What production model deployment looks like under hardware deadlines from OEM partners
• On-device tool use and agentic post-training at consumer scale
• The full stack from training run to phone

Timeline of success

• After 30 days — You've reproduced one of our recent training runs end-to-end. You've named the three highest-leverage research bets for the next quarter and have a take on which two to run.
• After 60 days — You're leading a training workstream with a clear metric. You've shipped a checkpoint that beats the previous best on the eval that matters. People trust your read on what's working.
• After 90 days — Your work has shipped into a partner build. You've made one non-obvious bet that paid off and one that didn't, and the team has learned from both. You're shaping the next training cycle.

Compensation

• Competitive cash and meaningful equity
• Top-tier relocation and immigration support
• Permission to publish what's safe to publish
• SF, in person

How to apply

Send a link to your most interesting result — paper, blog, model card, GitHub — with one paragraph on why it matters. Plus your resume, Google Scholar, or LinkedIn. Every exceptional candidate hears back within 48 hours.