[{"@context":"https://schema.org","@type":"JobPosting","title":"Founding Machine Learning Engineer","description":"

About the Role

We're looking for founding Machine Learning Engineers (MLEs) to own and improve our core action models end-to-end - the intelligence that powers Composite's proactive automation platform.

You'll work at the intersection of LLM inference, browser understanding, and low-latency systems, shipping models that need to feel instant while reasoning over complex page state and user context.

Unlike hosted browser solutions that introduce latency and auth barriers, or consumer-focused \"AI browsers,\" we run AI directly through professionals' existing browsers via a Chrome extension, creating instant response times with zero migration or IT friction. This architecture creates unique ML challenges.

This is a high-ownership role on our small, exceptional team where your work ships directly to users and has the potential to tangibly improve the work lives of hundreds of millions of people.

About Composite

College-educated professionals spend 85% of their day as digital factory workers in Chrome, clicking through repetitive browser tasks.

Composite is building the proactive layer for productivity so professionals around the world can focus on meaningful, high-leverage work. We're training action prediction models that run in real time, anticipating what you'll do next based on page context and prior interactions.

We've raised $5.6M in seed funding led by Nat Friedman and Daniel Gross, with participation from Menlo Ventures, Anthropic's Anthology Fund, SVAngel, and other incredible investors.

What You'll Work On

Improve the accuracy and laten","datePosted":"2025-10-22","employmentType":"FULL_TIME","hiringOrganization":{"@type":"Organization","name":"Composite","sameAs":"https://composite.com"},"url":"https://jobs.ashbyhq.com/composite/03e445d5-f7c9-41f3-8994-ed136dc1e64d","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}}}]

Composite

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