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Thinking Machines Lab

Technical Sourcer

Reposted 19 Days Ago
In-Office
San Francisco, CA, USA
250K-300K Annually
Mid level
In-Office
San Francisco, CA, USA
250K-300K Annually
Mid level
Build and manage pipelines for research, engineering, and infrastructure talent. Partner with recruiters and hiring managers, craft personalized outreach to passive candidates, track sourcing metrics, represent company mission, and help develop sourcing tools and processes at a fast-scaling startup.
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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.

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