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Catalog

Enriches retailer catalogs for AI shopping

Founding Engineer

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USANo salary listed

About the Job

Requirements

  • Have strong engineering instincts and a track record of building things that work.
  • Be deeply curious about intelligence, how models learn, and what they could become capable of.
  • Enjoy ambiguous problems and be able to turn an idea into something concrete.
  • Move quickly, think independently, and care about the quality of the work.
  • Want high ownership in a small, ambitious team in San Francisco.

Responsibilities

  • Take on open-ended problems at the intersection of AI research and engineering.
  • Build systems that help models learn, improve, and perform more reliably.
  • Move between experiments, prototypes, and production as the work evolves.
  • Help shape the technical approach and the team being built around it.
  • Work across research and engineering to turn ambitious ideas into working systems, help decide which problems matter, explore new approaches, and build the foundations of Catalog.
  • Own meaningful parts of the technical direction, product, and engineering culture while working closely with the founders.

Desired Qualifications

  • Experience with AI agents, machine learning, reinforcement learning, or post-training.
  • Have built early products, research tools, or technical infrastructure.
  • Research, open-source contributions, or independent projects that demonstrate how the candidate thinks.

About the Company

Catalog

Enriches retailer catalogs for AI shopping

Catalog converts retailer product catalogs into AI-ready structured data for shopping agents. It connects to retailers’ data stacks (such as Shopify, PIMs, ERPs) and enriches data by resolving variants, filling missing attributes, and pulling signals from images and reviews. The enriched data is exposed via a Live API for AI shopping agents, agentic commerce platforms, research labs, and retailers. The goal is to enable accurate product discovery, comparison, and checkout in conversational shopping while giving retailers control over where products appear and how performance is measured.

Company size
1-10
Company stage
Seed
Total funding
$3M
Headquarters
San Francisco, CA
Founded
2025

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