San Francisco, California, United States · On-site
$180k–$280k/yr
We want to build agents that autonomously validate code changes. Today that looks like AI that reviews pull requests in GitHub, catching bugs and enforcing standards. We’re reviewing close to 1B lines of code a month now…
Skills: Machine Learning, Large Language Models, AI Agents, Programming, Product Intuition
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Experiment with and apply recent advancements in agents and LLMs to improve product performance. This includes prototyping multi-agent workflows and integrating them into production systems.
Requires a BS in Computer Science or equivalent with strong programming skills and product intuition. Candidates should have research experience, specifically with ML, LLMs, or AI agents.
We want to build agents that autonomously validate code changes. Today that looks like AI that reviews pull requests in GitHub, catching bugs and enforcing standards. We’re reviewing close to 1B lines of code a month now for over 3,000 companies.
Coding standards can be idiosyncratic and are often poorly documented; can we build agents that learn them through osmosis like a new hire might?
Can we identify for each customer what types of PR feedback they do and don’t care about, perhaps using some sample efficient RL, in order to increase signal-to-noise ratio?
Some bugs are best caught by running the code, potentially against discerning AI-generated E2E tests. Can we autonomously deploy feature branches and use agents to parallel try to break the application to detect bugs?
7,000+ customers
Raised $30M from Benchmark, YC, Paul Graham, Initialized
We have assembled a small, talent dense team who have scaled critical functions at companies like Stripe, Google, Figma, LinkedIn, etc.
BS in Computer Science or equivalent
Some research experience, ideally with ML/LMs/Agents
Strong programming skills and good product intuition
Experiment with and apply recent advancements in agents/LMs etc. to improve the performance and capabilities of our products
Example: you might study multi-agent architectures, prototype and evaluate a multi-agent code review workflow, and then work with a team to integrate successful prototypes into production systems
Stay current with the latest research in LLMs, information retrieval, and developer tooling
The AI Code Reviewer
Building the universal code validation layer, starting with AI agents that review pull requests with full codebase context.
Offices: 407 Sansome St, 300, San Francisco, California 94111, US
The AI Code Reviewer
Building the universal code validation layer, starting with AI agents that review pull requests with full codebase context.
Offices: 407 Sansome St, 300, San Francisco, California 94111, US
