Software Engineer

United States·San Francisco,San Franciscofull-timemid

Software EngineerSoftware Engineering

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Quick Summary

Overview

What we do Idler builds reinforcement learning environments that teach AI models to code like 0.01% engineers. Our training environments are based on real-world coding scenarios that frontier models will actually encounter.

Key Responsibilities

Build features and tooling for our agentic systems that create and QA coding environments. You'll work alongside senior engineers and the founding team, learning how to design systems that are both technically sound and philosophically robust.

Technical Tools

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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

~1 min read

As a Software Engineer at idler, you’ll build the systems and infrastructure that our entire company relies on. You will solve open-ended, technical challenges with focus on performance, scale, and simplicity. In the era of AI-coding, systems-level thinking and attention to detail is more important than experience with a particular framework or language.

Responsibilities

~1 min read

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Design and build scaleable systems that generate RL environments
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Create agentic QA systems to validate environment quality and fairness
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Work directly with AI researchers at leading labs to understand what makes training data effective
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Handle petabyte scale ETL and orchestrate millions of concurrent jobs
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Support new product lines as we expand beyond coding environments
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Manage our security posture and compliance requirements