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Recruiting Sourcer

Thinking Machines Lab · San Francisco, California

Location
San Francisco, California
Level
Mid level
Posted
6 months ago

About this role

Thinking Machines Lab's mission is to empower humanity through advancing collaborative general intelligence. We're building a future where everyone has access to the knowledge and tools to make AI work for their unique needs and goals.

We are scientists, engineers, and builders who’ve created some of the most widely used AI products, including ChatGPT and Character.ai, open-weights models like Mistral, as well as popular open source projects like PyTorch, OpenAI Gym, Fairseq, and Segment Anything.

About the Role

We're hiring a Recruiting Sourcer to build the pipeline of exceptional research and engineering talent that will define the next generation of AI. You'll partner closely with recruiters, hiring managers, and our technical leaders to identify, engage, and build relationships with candidates across research, engineering, and infrastructure.

This role is foundational to our growth. You'll need to think creatively about where to find rare technical talent, craft outreach that resonates with researchers and engineers who aren't actively looking, and help us build a sourcing function from the ground up at a fast-moving startup.

What You’ll Do

  • Build and manage a pipeline of candidates across research, engineering, and infrastructure roles, using creative and diverse sourcing channels
  • Partner with recruiters and hiring managers to deeply understand role requirements and translate them into effective sourcing strategies
  • Write and send personalized outreach that engages passive candidates, including senior researchers and engineers
  • Track pipeline metrics and sourcing effectiveness, and iterate on strategy based on what's working
  • Represent Thinking Machines' mission and culture authentically to prospective candidates throughout the sourcing process
  • Help build and refine our sourcing tools, processes, and infrastructure as the team scales

Skills and Qualifications

Minimum qualifications:

  • 3+ years of sourcing or recruiting experience, ideally supporting technical roles in AI labs or tech startups
  • Track record of successfully identifying and engaging passive technical candidates, including researchers and engineers
  • Excellent written communication skills, with the ability to craft compelling, personalized outreach

Preferred qualifications:

  • Familiarity with the AI/ML research landscape, including key labs, conferences, and communities
  • Experience using sourcing tools and platforms (e.g., LinkedIn Recruiter, GitHub, academic search tools)
  • Experience building sourcing processes and infrastructure at an early-stage or fast-scaling company
  • Comfort operating with significant autonomy and adapting quickly as priorities shift

Logistics

  • Location: This role is based in San Francisco, CA.
  • Compensation: Depending on background, skills and experience, the expected annual salary range for this position is $250,000 - $300,000 USD.
  • 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.
  • Benefits: Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.

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.

Thinking Machines Lab will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of the California Fair Chance Act, the San Francisco Fair Chance Ordinance, and any other applicable state or local fair chance ordinance or law.

As published by Thinking Machines Lab. Applications are handled on their site.

Skills this posting mentions

SourcingArtificial IntelligenceRecruiting

About Thinking Machines Lab

Thinking Machines Lab is an artificial intelligence research and product company. We’re building a future where everyone has access to the knowledge and tools to make AI work for their unique needs and goals.

All 36 openings at Thinking Machines Lab

One click, then it is written

Apply to Thinking Machines Lab with a resume written for this role.

Queue Recruiting Sourcer and I read the posting, rewrite your resume against it, draft the cover letter, and score the fit. Then you press send, or press one button and I fill in Thinking Machines Lab’s form for you.

  1. 01Drop your resume

    A PDF or a LinkedIn URL. About a minute, once.

  2. 02I rank the openings

    Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.

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    Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.

  • 25 sent a week, free
  • No card
  • Nothing sent until you say so

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Paste your career in once. Every application after that is written for you.

Drop a resume or a LinkedIn URL. I rank the live openings against it, rewrite the resume and write a cover letter for the best of them, and fill in the employer's form when you press the button. You read, you decide what goes out.

  1. 01Drop your resume

    A PDF or a LinkedIn URL. About a minute, once.

  2. 02I rank the openings

    Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.

  3. 03Each one is written up

    Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.

  • New matches ranked and written before you are up.
  • Every bullet stays inside what your history supports. Nothing invented.
  • Queued, submitted, interviewing, offer: one screen, not a spreadsheet.

500 free credits on sign-up. No card. Nothing is sent until you say so.

Listed from the job board Thinking Machines Lab publishes. Refolk is not the employer and does not handle their hiring. Applications go to Thinking Machines Lab directly.