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.
\nWe're looking for a GRC Lead who personally drives our certifications (SOC 2, ISO 27001, FedRAMP and others as we grow) from scoping through audit close, and runs our compliance processes day to day. You'll collect the evidence, write the control documentation, and sit across from the auditor yourself.
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\nRequirements
\nNice to Have
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\nThinking 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.
\nThe IT team builds secure infrastructure and efficient processes that enable our employees to move quickly. We operate an all-Mac environment and use tools such as Okta, Google Workspace, and Kandji to support a rapidly growing workforce across multiple offices.
\nThis role will serve as the primary IT partner for our New York employees and office. You will work closely with the IT and Security team in San Francisco to maintain consistent systems, security standards, and employee experiences across locations.
\nThinking 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.
\nThe IT team builds secure infrastructure and efficient processes that enable our employees to move quickly. We operate an all-Mac environment and manage our endpoint fleet as a distributed platform, applying production-engineering practices to device management and security.
\nThinking 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.
\nWe're looking for an Operations Analyst who will focus on making our products safe by default while supporting fast product iteration and ambitious ideas.
\nYou’ll work closely with product engineers, security, researchers, and designers to bake safety and integrity into the way we design, build, and ship human-AI collaboration tools. Day to day, you'll be in the moderation queue while building the tooling and policy that make the next round of moderation faster and more accurate.
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\nSkills and Qualifications
\nMinimum qualifications:
\nPreferred qualifications:
\nYou’ll Thrive in This Role if
\nLogistics
\nThinking Machines Lab's mission is to empower humanity through advancing collaborative general intelligence.
\nWe're looking for a full stack engineer to build and ship the products and services that Tinker users interact with every day.
\nThinking Machines Lab's mission is to empower humanity through advancing collaborative general intelligence.
\nWe're hiring a Recruiting Coordinator to accelerate our hiring efforts for Research and build a high-quality, efficient recruiting engine. You will be responsible for owning interview scheduling, improving recruiting operations, reporting, and delivering a thoughtful, high-touch candidate experience.
\nThinking Machines Lab is seeking a Reliability Engineer to ensure the reliability of its GPU supercomputing fleet. The successful candidate will track and resolve hardware issues, diagnose problems, and collaborate with vendors.
\nThinking Machines Lab is seeking a Network Engineer to own the lowest layers of the network stack for large-scale training and inference. The successful candidate will be responsible for interconnect reliability at scale, across large GPU fabrics.
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\nPreferred qualifications:
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\nWe're seeking an infrastructure research engineer to design and build scalable, efficient training systems for large models. As a key member of our team, you'll take ownership of the training stack end-to-end, ensuring every GPU cycle drives scientific progress. Your goal is to make experimentation and training at Thinking Machines fast and reliable, allowing our research teams to focus on science, not system bottlenecks.
\nKey responsibilities include designing, implementing, and optimizing distributed training systems, developing high-performance optimizations, and establishing standards for reliability, maintainability, and security. You'll collaborate with researchers and engineers to build scalable infrastructure and publish learnings through internal documentation, open-source libraries, or technical reports.
\nWe're looking for someone who blends deep systems and performance expertise with a curiosity for machine learning at scale. A strong understanding of deep learning frameworks, such as PyTorch, and experience working on distributed training for large models are preferred. If you have a track record of improving research productivity through infrastructure design or process improvements, that's a plus.
\nThis role is based in San Francisco, California, and offers a competitive salary range of $350,000 - $475,000 USD per year, depending on background, skills, and experience. We sponsor visas and offer generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.
","enriched_at":1776527879640},{"id":"job_7e28478b-c37","title":"Research, Audio Expertise","source_url":"https://job-boards.greenhouse.io/thinkingmachines/jobs/5002212008","location":"San Francisco","job_type":"full-time","experience_level":"senior","work_arrangement":"onsite","category":"Engineering","description":"We're seeking a researcher to advance the frontier of audio capabilities. You'll explore how audio models enable more natural and efficient communication/collaboration, preserving more information and capturing user intent.
\nThis is a highly collaborative role. You'll work closely across pre-training, post-training, and product with world-class researchers, infrastructure engineers, and designers.
\nAs a researcher in this role, you'll be expected to:
\nShare code, datasets, and insights that accelerate progress across industry and academia.
\nThis role blends fundamental research and practical engineering, as we do not distinguish between the two roles internally. You will be expected to write high-performance code and read technical reports.
\nIt's an excellent fit for someone who enjoys both deep theoretical exploration and hands-on experimentation, and who wants to shape the foundations of how AI learns.
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