About the role
You work on knowledge, world models, memory, and the evaluations that keep them honest, in a lab whose partners are Stony Brook, Purdue, and the IITs. Our constraint shapes the research: the model often runs on the person's own hardware under a consent boundary, which closes off the easy answers.
What we need to see
- Research contribution you can point at: publications, or a shipped system whose core idea was yours
- You implement your own work to a standard that could ship
- Rigor about evaluation, especially at telling real gains from better-looking benchmarks
- Depth in knowledge representation, memory, world models, or retrieval
Nice to have
- Personalisation or user-specific models
- Privacy-preserving machine learning
- Open-source or open-weights contributions
What winning looks like
- Benchmark/eval gains that reach the product
- Research shipped to users
- Reproducibility and quality of work
Where and how we work
We work in the office together five days a week, in one of our garages. Remote work is available only by exception, arranged individually around specific circumstances.
Pay
| Location | Annual base range |
|---|---|
| Kirkland, WA | USD 150,000 - 215,000 |
| Dubai, UAE | AED 400,000 - 600,000 |
| Pune, India | INR 28 - 55 LPA |
Indicative annual base for this role's level, in the currency of the garage you join, from our published pay ranges. Full-time roles also get equity and an annual bonus. Your offer depends on level, location and experience, and is confirmed in writing.