Drimva

Thinking Machines Lab

Research Engineer, Web Crawling

$350K–$475K

San Francisco +1 · On-site · Full-time · Posted Sep 24, 2026

Location
San Francisco
New York
Experience
8+ years; no alternatives stated.
Visa sponsorship
Visa sponsorship is offered; success is not guaranteed for every candidate or role.

About the job

Build and operate internet-scale web-crawling and data-ingestion systems that collect, process, and prepare data for pretraining.

What you'll do

  • Design and scale crawling and ingestion infrastructure, including specialized crawlers for difficult or high-value sources.
  • Build extraction, deduplication, and data-quality filtering pipelines; improve reliability and efficiency at petabyte scale.
  • Work with the pretraining team to assess how crawled data affects model performance and help set technical direction.

What they ask for

  • 8+ years designing, building, and scaling web crawlers, scrapers, or large-scale distributed data-acquisition systems.
  • Track record of owning crawler or data-acquisition infrastructure at internet scale.
  • Strong software engineering skills in a language such as Python, Go, or Rust, with real experience in distributed systems.
  • Working knowledge of practical and legal considerations of large-scale web data collection, including robots.txt, rate limiting, and licensing.

Nice to have

  • Experience applying machine learning to crawl selection, extraction, or data-quality classification at internet scale.
  • Experience setting technical direction for relevant infrastructure teams; petabyte-scale systems experience, open-source contributions, or search-engine/frontier-AI data-acquisition background.

Pay

$350,000-$475,000 USD (base salary)

Tools

Python, Go, Rust, robots.txt

AI focus

The job prepares Inkling's pretraining data and works with the pretraining team to understand how crawled data affects model performance. Preferred experience includes applying machine learning to crawl selection, extraction, or data-quality classification.

Model-written summary · the original posting is authoritative

First seen Oct 10, 2026 · Last verified Nov 5, 2026 (UTC)