Thinking Machines Lab

Thinking Machines Lab

Research Engineer, Web Crawling

San Francisco · Senior

H1B sponsorship available$350k-$475kDetected 22 days ago
PythonGoDistributed SystemsMachine LearningLogisticsResearch

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odds of building a lasting career here

59Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role80
Entry-level history0
PERM / green-card track0
Lottery odds (Level IV)94
Fits your clock70

Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.

Lottery odds assume a STEM candidate.

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Employer immigration record

from this employer's Department of Labor filings

Files H-1B transfers

16 transfer filings in the last year, covering 16 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.

Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.

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About the role

  • The ideal candidate has built and scaled a web crawler or large-scale data-acquisition systems.
  • You'll work closely with our pretraining and data teams to understand what's actually moving model quality, but this is fundamentally an engineering role, not a research one.

Responsibilities

  • Design and scale the web crawler and ingestion infrastructure that sources Inkling's pretraining data
  • Build pipelines for large-scale extraction, deduplication, and data quality filtering
  • Build specialized crawlers for high-value or hard-to-reach data sources
  • 8+ years designing, building, and scaling web crawlers, scrapers, or large-scale distributed data-acquisition systems
  • We believe the future worth building is human, and we're hiring people who want to build it.

Requirements

  • A 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 the practical and legal considerations of large-scale web data collection (robots.txt, rate limiting, licensing)

Nice to have

  • Experience setting technical direction for a crawling, data acquisition, or search infrastructure team, whether or not that was your formal title
  • Experience designing systems for petabyte-scale storage and processing
  • Track record of open-source contributions to crawling, scraping, or data infrastructure tools
  • Background at a search engine (crawling, indexing) or a frontier AI lab's data acquisition team
  • Visa sponsorship: We sponsor visas.
  • While we can't guarantee success for every candidate or role, if you're the right fit, we're committed to working through the visa process together.
  • As set forth in Thinking Machines' Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.

Compensation

  • Depending on background, skills and experience, the expected annual salary range for this position is $350,000-$475,000 USD.

Benefits

  • Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.
  • Experience applying machine learning to crawl selection, extraction, or data quality classification at internet scale

Company info

  • The mission of Thinking Machines is to build AI that extends human will and judgment.
  • We are training frontier models with Inkling, developing Tinker to let people make models their own, and crafting interfaces that broaden human-AI communication.

Visa & Work Authorization

  • We sponsor visas.
  • While we can't guarantee success for every candidate or role, if you're the right fit, we're committed to working through the visa process together.
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This listing is sourced directly from Thinking Machines Lab's careers page and normalized into a canonical job model.