LLM Modeling and Scaling Researcher
Ricursive Intelligence · Palo Alto, California
- Location
- Palo Alto, California, United States
- Employment
- Full time
- Level
- Mid level
- Posted
- 19 January
About this role
Ricursive Intelligence is a frontier AI lab building self-improving systems, starting with chip design. We are reinventing chip development and closing the loop between AI and the hardware that fuels it, recursively accelerating the path to artificial superintelligence. Backed by $335M from Sequoia, Lightspeed, DST, and NVIDIA Ventures, we are a growing, fast-paced team where every hire shapes the work.
The company has unmatched talent density, including IMO, IPHO, and IOAA gold medalists, pioneers who made prior breakthroughs in chip design: AlphaChip (Nature 2021), ePlace (DAC Best Paper Nominee 2014), RL-CCD (DAC Best Paper 2023), INSTA (DAC Best Paper 2025), and C3PO (ASP-DAC Best Paper 2026), chip leads for Apple Silicon (multiple generations of iPhone and iPad) and Google (TPU, OpenTitan), and top researchers and engineers from Anthropic, Google DeepMind, Stanford, and MIT.
We are hiring best-in-class researchers to conduct novel AI research, work on a variety of challenges related to LLM modeling, training, data, evaluation, and more. As a startup, everyone is hands-on - our researchers design and run experiments at scale, and build/deploy models in production.
As published by Ricursive Intelligence. Applications are handled on their site.
Skills this posting mentions
About Ricursive Intelligence
A frontier AI lab enabling a recursive self-improvement loop between AI and the chips that fuel it.
All 14 openings at Ricursive IntelligenceOne click, then it is written
Apply to Ricursive Intelligence with a resume written for this role.
Queue LLM Modeling and Scaling Researcher and I read the posting, rewrite your resume against it, draft the cover letter, and score the fit. Then you press send, or press one button and I fill in Ricursive Intelligence’s form for you.
01Drop your resume
A PDF or a LinkedIn URL. About a minute, once.
02I rank the openings
Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.
03Each one is written up
Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.
- 25 sent a week, free
- No card
- Nothing sent until you say so
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Put this to work
Paste your career in once. Every application after that is written for you.
Drop a resume or a LinkedIn URL. I rank the live openings against it, rewrite the resume and write a cover letter for the best of them, and fill in the employer's form when you press the button. You read, you decide what goes out.
01Drop your resume
A PDF or a LinkedIn URL. About a minute, once.
02I rank the openings
Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.
03Each one is written up
Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.
- New matches ranked and written before you are up.
- Every bullet stays inside what your history supports. Nothing invented.
- Queued, submitted, interviewing, offer: one screen, not a spreadsheet.
Free, no card. Up to 25 applications sent a week, and nothing is sent until you say so.
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