Full-Time

Recruiting Coordination and Operations Specialist

Posted on 3/18/2026

Thinking Machines Lab

Thinking Machines Lab

51-200 employees

Develops customizable multimodal AI systems

Compensation Overview

$140k - $200k/yr

H1B Sponsorship Available

San Francisco, CA, USA

In Person

Category
People & HR (1)
Requirements
  • Experience coordinating schedules, managing calendars, or supporting operations in a fast-paced environment
  • Excellent written and verbal communication skills, especially in direct candidate communications
  • Ability to adapt quickly to different teams, roles, and ways of working without losing your footing
  • Comfortable with Google Workspace, scheduling tools, and Slack
  • A do-what-it-takes mindset: you’re proactive, detail-oriented, and don’t let things fall through the cracks
Responsibilities
  • Maintain data integrity across our Applicant Tracking System and recruiting tools - audit regularly and keep things accurate
  • Support talent mapping, referral processing, inbound application triage, and recruiting events
  • Track interview feedback completion and follow up to make sure nothing stalls
  • Identify process gaps and propose improvements - this role is expected to make the function better, not just execute
  • Collect, organize, and audit interview feedback to ensure nothing gets lost or delayed
  • Maintain up-to-date recruiting information in documentation and in Slack, support data integrity across recruiting systems
  • Manage high-volume interview coordination across multiple time zones, calendars, and stakeholders while maintaining a world-class candidate experience
  • Coordinate all interview logistics, from travel and expenses to room setup and technical support
  • Serve as the main point of contact for candidates, communicating in a warm, professional, and informative manner from initial screening through offer
  • Anticipate scheduling bottlenecks before they happen: monitor interviewer availability, flag conflicts early, and keep hiring velocity high
  • Scale interviewer pools by partnering with teams to identify, train, and prepare new interviewers as hiring volume grows
  • Use modern scheduling tools (e.g., Greenhouse, ModernLoop) to automate scheduling, reduce manual work, and improve response speed
  • Manage high-volume scheduling across time zones, calendars, and multiple stakeholders.
Desired Qualifications
  • 1+ years in a high-volume scheduling or recruiting coordination role
  • Experience with ATS, HRIS, and scheduling tools like Greenhouse, GoodTime, Workday, and ModernLoop
  • Experience partnering closely with recruiters and hiring managers
  • Proven ability to be proactive in ambiguous situations and propose multiple solutions
  • Experience supporting technical or leadership-level hiring
Thinking Machines Lab

Thinking Machines Lab

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Thinking Machines Lab builds customizable, multimodal AI systems for researchers, enterprises, and developers. Its products are delivered through a full-stack approach that covers model training, deployment, and APIs or on-premises licensing, with interfaces that can be tailored to different domains and workflow needs. The team combines deep talent from OpenAI, Meta AI, and Mistral AI, enabling an integrated stack focused on human–AI collaboration and safety rather than generic one-size-fits-all tools. The company aims to make generally capable AI accessible and understandable to scientists and developers, helping them deploy AI in enterprise settings with clear ethical controls.

Company Size

51-200

Company Stage

Seed

Total Funding

$2B

Headquarters

San Francisco, California

Founded

2024

Simplify Jobs

Simplify's Take

What believers are saying

  • Tinker can expand into enterprise fine-tuning, managed APIs, and on-prem licensing.
  • The Google and NVIDIA infrastructure stack supports compute-heavy training and serving.
  • A deep bench from OpenAI, Meta, Anthropic, Apple, and Waymo accelerates execution.

What critics are saying

  • NVIDIA and Google control critical compute access and pricing.
  • Meta poaching can drain core researchers and slow product progress.
  • OpenAI and Anthropic can replicate customizable AI features quickly.

What makes Thinking Machines Lab unique

  • Mira Murati brings OpenAI product leadership and frontier-model credibility.
  • Tinker targets reproducible fine-tuning on open-weight models for controlled deployments.
  • Human-AI collaboration and multimodal customization define the company’s product thesis.

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Benefits

Health Insurance

Dental Insurance

Vision Insurance

Unlimited Paid Time Off

Parental Leave

Relocation Assistance

Company News

NVIDIA
Mar 10th, 2026
NVIDIA and Thinking Machines Lab Announce Long-Term Gigawatt-Scale Strategic Partnership

NVIDIA and Thinking Machines Lab announced today a multiyear strategic partnership to deploy at least one gigawatt of next-generation NVIDIA Vera Rubin systems to support Thinking Machines’ frontier model training and platforms delivering customizable AI at scale.

Bloomberg L.P.
Mar 10th, 2026
Nvidia invests in Thinking Machines Lab, to supply AI chips to ex-OpenAI exec Mira Murati's startup

Nvidia is investing in Thinking Machines Lab, an AI startup founded by former OpenAI executive Mira Murati, and will supply chips to help train and run the company's AI models. The investment strengthens Nvidia's position in the AI sector whilst providing Thinking Machines Lab with crucial computing infrastructure for model development.

Business Insider
Feb 27th, 2026
2 Thinking Machines Lab founders join Meta as $12B startup faces talent exodus

Thinking Machines Lab, the AI startup led by former OpenAI CTO Mira Murati, has lost two founding members to Meta in recent weeks. Christian Gibson, a former OpenAI engineer who worked on the first ChatGPT model, and Noah Shpak, an AI engineer previously at Character.AI and X, have both joined Meta. The departures add to a wave of exits from the San Francisco-based company, which raised $2 billion at a $12 billion valuation last year. The startup recently lost its CTO Barret Zoph and cofounder Luke Metz to OpenAI, along with several researchers. Another cofounder, Andrew Tulloch, departed for Meta last year. Thinking Machines Lab focuses on helping developers custom-build AI models and has attracted top talent despite the ongoing poaching. Meta and Thinking Machines Lab declined to comment.

Maglazana
Feb 26th, 2026
Mira Murati's Thinking Machines Lab raises $2B seed round at $12B valuation, launches Tinker API

Mira Murati, former OpenAI chief technology officer, has launched Thinking Machines Lab, an AI research company that closed a roughly $2 billion seed round led by Andreessen Horowitz, valuing the startup at approximately $12 billion. Nvidia, AMD and Cisco participated in one of the largest early-stage funding rounds in tech history. Founded in February 2025, Thinking Machines Lab assembled researchers from OpenAI, Meta and other AI pioneers to build customizable, accessible AI systems. In October, the company launched Tinker, an API enabling developers to fine-tune large language models more efficiently. The startup faces challenges including intense competition for talent, with several high-profile employees departing to OpenAI and rivals. Murati's rapid progress from launch to product delivery marks a significant development in the evolving AI landscape.

Business Insider
Feb 4th, 2026
Mira Murati's Thinking Machines Lab hires award-winning coder amid executive exodus

Thinking Machines Lab, the AI startup founded by former OpenAI CTO Mira Murati, has quietly hired Neal Wu, a three-time gold medal winner at an international programming Olympiad. Wu is a founding member of AI coding startup Cognition, valued at $10 billion, and brother of its CEO Scott Wu. The hire demonstrates Thinking Machines Lab continues attracting top talent despite aggressive poaching from rivals like Meta. The startup recently lost cofounder Andrew Tulloch to Meta in a deal worth up to $1.5 billion, and CTO Barret Zoph along with two other founding members returned to OpenAI in January. Thinking Machines Lab, which helps developers train and customise AI models, raised $2 billion in seed funding at a valuation exceeding $10 billion before launching a product.

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