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Composite

AI-powered browser autopilot for task automation

Founding Machine Learning Engineer

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USA$150k - $220k /yrIn-person

About the Job

Requirements

  • Strong machine learning fundamentals and hands-on experience training and deploying models in production.
  • Experience optimizing inference pipelines for very low latency to end users.
  • Strong attention to data quality and the ability to build tooling that ensures it.
  • Experience with large language models, transformer architectures, or sequence prediction problems.
  • Ability to work across a system spanning a Chrome extension, Electron app, Cloudflare Workers edge proxy, and inference providers.
  • Curiosity, humility, strong communication, and willingness to challenge assumptions and accept being wrong.
  • Ability to work intensely on difficult problems and ambitious goals.
  • Ability to understand complex systems quickly and solve novel, ambiguous problems with self-guidance.

Responsibilities

  • Improve the accuracy and latency of core models across diverse web applications to predict users' intended next actions and execute them faster than manual input.
  • Design and optimize large language model inference pipelines, including token caching strategies, streaming architectures, and network-level optimizations between client and server.
  • Build evaluation frameworks and data pipelines to measure and improve model quality at scale.
  • Experiment with retrieval-augmented approaches using vector databases for contextual memory.
  • Develop synthetic data generation pipelines for browser interaction training data.
  • Work with document object model states, accessibility trees, and user interaction data to improve browser understanding.
  • Ship end-to-end features directly to users.

Desired Qualifications

  • Experience with browser automation, Chrome extensions, or web scraping at scale.
  • Familiarity with accessibility tree or document object model parsing for page understanding.
  • Background in reinforcement learning or online learning from user interaction data.
  • Experience with vector databases such as Turbopuffer or Pinecone and hybrid search.
  • Full-stack development experience with TypeScript, Node.js, and React.

About the Company

Composite

AI-powered browser autopilot for task automation

Composite provides an AI-powered autopilot for web browsers that automates repetitive digital tasks inside the user’s existing browser. It runs locally in the browser, learns from the user’s actions, and proactively suggests and executes workflows in real time without requiring any setup or changes to the browser. It works across any website and can handle tasks like data entry, job searches, and expense submissions by turning user actions into automated routines. Its goal is to make professional browsing more productive by turning ordinary web tasks into automated, efficient workflows while keeping everything local and easy to use.

Company size
1-10
Company stage
Seed
Total funding
$5.6M
Headquarters
San Francisco, CA
Founded
2024

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