---
title: 'Research Scientist at Idler'
canonical: 'https://feeny.ai/job/research-scientist-idler-san-francisco-1tr3n99m2wt8'
type: 'job'
last_seen: '2026-09-04'
---

# Research Scientist at Idler

- **Company:** Idler
- **Location:** San Francisco, CA
- **Compensation:** $200k–$500k
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-08-26
- **Last confirmed live:** 2026-09-04
- **Apply:** https://jobs.ashbyhq.com/idler/3a8b02ec-c567-4f75-bf73-ec763e06d6eb

## Job description

## About idler

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.

After raising a $9m seed round led by Paradigm, we spent the last year developing coding evals for top coding models you know and love. At the same time, we've expanded into other domains besides coding: RSI & Auto-Research, Law, Enterprise Business, Cybersecurity, and others. Now, we are facing more lab demand for our data than we can serve, and are rapidly scaling the team to grow the business.

Our approach to creating training data scales using technology, and all of our data products are built on a unified self-reinforcing platform that learns through experience.

You would be joining a close-knit team that has reached product market fit, and your work would directly help to multiply our revenue.

You can see some of our work here: https://idler.ai/collections

## About the role

As a Research Scientist at idler, you'll own measuring and improving how models learn from our tasks. The job is to maximize learning signal we produce per unit time. You'll draw on your own experience and collaborate with researchers at the frontier 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.

Examples of what you’ll do

- 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
- Identify opportunities to take advantage of self-reinforcing exponential feedback loops
- Create agents to analyze thousands of environments and millions of trajectories
- Help curate and specify task distributions for new corpora
- Work with procurement to ensure external data we acquire is suitable for refinement
- Create scaleable systems for ingesting & evaluating data we are considering buying
- Develop new techniques for mining data for signal

## What we’re looking for

- 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

Tech stack

Typescript, React, NodeJS, Postgres, Redis, Vercel, Cursor/Claude Code/Codex, Tinker, Modal, AWS, Daytona, GRPO

Details

- In-person in San Francisco
- Competitive salary + meaningful equity
- Free meals in office
- Healthcare, 401(k), 15 days of PTO per year
- Relocation assistance
- Small, ambitious team

This is an in-person role in San Francisco. We're a tight-knit founding team and we play to win. Join us if you like to win too.

## About Idler

## Company Overview
- **One-liner**: Idler builds reinforcement learning environments that teach AI models to code at expert human levels, using real-world coding scenarios to prepare them for production challenges.
- **Entity Type**: Private (Pre-Seed, YC Summer 2025)
- **Headquarters**: San Francisco, California, United States
- **Founded**: 2025
- **Founders**: Nalu Concepcion, Ivan Chub, Tony Goss

## Core Business
- **Primary industry**: Artificial Intelligence / Reinforcement Learning
- **Target customers**: Frontier AI labs, research organizations, and enterprises developing large language models (B2B, Enterprise)
- **Mission**: To create the training data layer for frontier AI by building environments that teach models to code like the top 0.01% of engineers.

## Products & Services
- **Reinforcement Learning Training Environments**: A platform that generates synthetic coding challenges and real-world scenarios for training AI models via reinforcement learning. These environments are designed to teach models complex, production-level coding skills.

## Market Standing
- **Valuation**: Not disclosed
- **Key Metrics**:
  - **Total Funding**: $500,000 (Pre-Seed round led by Y Combinator, October 2025)
  - **Annual Revenue**: Estimated at $22.5M (LinkedIn estimate; likely a projection or early revenue figure for a 2025 startup)
- **Notable Investors/Partners**: Y Combinator (lead investor), Harj Taggar (primary partner)
- **Growth Signals**:
  - Secured a multimillion-dollar contract with a leading foundation lab (largest they have issued to date)
  - Rapidly scaling team (currently 13-14 employees) to meet demand that outpaces delivery capacity
  - Active hiring for Software Engineers, Staff Software Engineer, and Special Projects Operator roles

## Competitive Advantages
- **Focus on Real-World Scenarios**: Unlike generic coding datasets, Idler’s environments simulate the complex, messy challenges models face in production, making trained models more capable and reliable.
- **Early Frontier Lab Contracts**: Already landed multimillion-dollar deals with top AI labs, validating demand and providing real-world feedback loops.
- **Y Combinator Backing**: Part of the prestigious Summer 2025 batch, providing network, credibility, and early-stage support.

## Strategic Focus
- **Scale Training Data Production**: Rapidly expand capacity to build environments for frontier AI models, aiming to become the default training data layer for reinforcement learning in coding.
- **Hire Top Engineering Talent**: Grow the team (currently ~13) with senior engineers and operators who can move fast and think deeply about training data quality.
- **Maintain In-Office Culture**: All employees work in person at the Dogpatch office in San Francisco to foster tight collaboration and rapid iteration.

## Why Work Here
- **Culture**: Tight-knit founding team that moves quickly, thinks deeply about data, and “plays to win.” Emphasis on high agency and ownership.
- **Work Environment**: 100% in-office at the Dogpatch neighborhood in San Francisco. No remote/hybrid option.
- **Perks & Benefits**:
  - Competitive salary ($140K–$400K depending on role) plus equity (0.05%–1.0%)
  - Free daily meals, snacks, and drinks
  - Health insurance, 401(K), generous PTO, paid holidays
  - Wellness initiatives and company-sponsored outings
  - Office perks including on-site workspace
- **Engineering Culture**: Uses modern stack (Next.js, React, TypeScript, PostgreSQL, Redis, Honeycomb, GitHub). Emphasis on building high-quality training data infrastructure.

## Sources
1. [ycombinator.com](https://www.ycombinator.com/companies/idler)
2. [linkedin.com](https://www.linkedin.com/company/idler)
3. [builtin.com](https://builtin.com/company/idlersai)
4. [ycombinator.com/jobs](https://www.ycombinator.com/companies/idler/jobs)
5. [builtinsf.com](https://www.builtinsf.com/company/idlersai)

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