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About the Role
As a Research Scientist at idler, you'll own measuring and improving how models learn from our tasks. You'll draw on your own experience and collaborate with frontier researchers to validate our data quality, identify where improvements are needed, and create new datasets. To succeed, you'll need to have extensive experience doing this work in production at a frontier lab.
Responsibilities
- Work with our customers — researchers at frontier labs — to design novel post-training recipes and data quality measurement techniques
- Design and run our in-house post-training stack to measure model lift on our tasks
- Develop new data products based on datasets and experts available to us
- Work with procurement to ensure external data we acquire is suitable for refinement
- Create scaleable systems for ingesting & evaluating data we are considering buying
Requirements
- 1+ years of experience doing RL in production at a frontier lab
- Track record of post-training an LLM end to end
- Desire to drive the research roadmap and implementation on a fast-moving team
- Deep curiosity about how machines learn from data and how to extract the maximum learning signal from our tasks
Skills
- Typescript
- React
- NodeJS
- Postgres
- Redis
- Vercel
- Cursor
Location
- San Francisco
Work Type
- In-person
Experience Level
- 1+ years of experience
Salary/Compensations
- Competitive salary
Benefits
- Meaningful equity
- Free meals in office
- Healthcare
- 401(k)
- 15 days of PTO per year
- Relocation assistance
About the Company
- idler is a frontier data research lab.
- We build the evals and environments that the world's leading frontier labs use to measure and train their models.
- We closed on a multimillion-dollar contract with a top lab and raised a $9m seed round led by Paradigm.
- We are now facing more lab demand for our data than we can currently serve.
- Teaching AI superhuman capabilities is a responsibility we take very seriously.
- Our training data comes from work that is rigorous, ethically produced, and grounded in real expertise.
- Small, ambitious team
- We're a tight-knit founding team and we play to win. Join us if you like to win too.