{"schemaVersion":"jobsearcher.job.v1","id":"3fe87f8a2f07881b2c7970c5","url":"https://jobsearcher.com/jobs/3fe87f8a2f07881b2c7970c5","canonicalUrl":"https://jobsearcher.com/jobs/3fe87f8a2f07881b2c7970c5","title":"Site Reliability Engineer","description":"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.\n\nWe 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.\n\nAbout Tinker\nTinker is our fine-tuning API that empowers researchers and developers to customize frontier AI to their needs — opening access to capabilities that have previously been concentrated in a handful of labs. We manage the infrastructure while allowing Tinkerers full flexibility in training open weights models with their own data, algorithms, and for their own needs. Tinker is rapidly adding new customers, features, and novel use‑cases. We’re hiring to grow the platform alongside the Tinker community.\n\nAbout the Role\nWe're looking for a Site Reliability Engineer to drive the reliability of Tinker end-to-end. You'll work alongside the engineers building the platform and research teams to make every layer of the system more robust and resilient.\n\nWhat You’ll Do\n\nDefine and own end-to-end reliability, from CI/CD flows to production observability and incident response.\n\nDevelop appropriate Service Level Objectives for distributed training systems, balancing job completion reliability and scheduling latency with development velocity.\n\nDesign and implement monitoring and observability across the full training path.\n\nDrive incident response for Tinker platform issues, ensuring rapid recovery, thorough incident reviews, and systematic improvements that prevent recurrence.\n\nHarden multi‑tenant isolation and resource scheduling so that LoRA‑based workload co‑scheduling maximizes utilization without compromising reliability or data separation\n\nCollaborate with security teams to address production vulnerabilities\n\nSkills and Qualifications\n\nBachelor's degree or equivalent experience in computer science, engineering, or similar.\n\nExperience in distributed systems, cloud infrastructure, or site reliability engineering.\n\nProficiency writing software to solve reliability problems, including building tooling and automation.\n\nExperience with production incident response, postmortems, and systematic reliability improvement.\n\nStrong communication skills and track record of coordination across engineering and research teams.\n\nPreferred qualifications — we encourage you to apply if you meet some but not all of these:\n\nDeep experience operating production cloud services at scale (e.g., public cloud platforms, internal cloud services)\n\nBackground in distributed training frameworks and how infrastructure failures surface in training behavior.\n\nTrack record building checkpoint and recovery systems for long-running distributed jobs.\n\nExpertise in Kubernetes at scale: deploying, operating, debugging, and tuning clusters handling heterogeneous GPU workloads.\n\nLogistics\n\nLocation: This role is based in San Francisco, California.\n\nCompensation: Depending on background, skills and experience, the expected annual salary range for this position is $350,000 – $475,000 USD.\n\nVisa 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.\n\nBenefits: Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.\n\n#J-18808-Ljbffr","company":"Thinking Machines Lab","rawCompany":"thinking machines lab","city":"Millbrae","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-07-16T04:03:19.878Z","occupations":[{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1221.00","title":"Computer and Information Research Scientists","slug":"computer-and-information-research-scientists"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541519","title":"Other Computer Related Services","slug":"other-computer-related-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Site Reliability Engineer","description":"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.\n\nWe 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.\n\nAbout Tinker\nTinker is our fine-tuning API that empowers researchers and developers to customize frontier AI to their needs — opening access to capabilities that have previously been concentrated in a handful of labs. We manage the infrastructure while allowing Tinkerers full flexibility in training open weights models with their own data, algorithms, and for their own needs. Tinker is rapidly adding new customers, features, and novel use‑cases. We’re hiring to grow the platform alongside the Tinker community.\n\nAbout the Role\nWe're looking for a Site Reliability Engineer to drive the reliability of Tinker end-to-end. You'll work alongside the engineers building the platform and research teams to make every layer of the system more robust and resilient.\n\nWhat You’ll Do\n\nDefine and own end-to-end reliability, from CI/CD flows to production observability and incident response.\n\nDevelop appropriate Service Level Objectives for distributed training systems, balancing job completion reliability and scheduling latency with development velocity.\n\nDesign and implement monitoring and observability across the full training path.\n\nDrive incident response for Tinker platform issues, ensuring rapid recovery, thorough incident reviews, and systematic improvements that prevent recurrence.\n\nHarden multi‑tenant isolation and resource scheduling so that LoRA‑based workload co‑scheduling maximizes utilization without compromising reliability or data separation\n\nCollaborate with security teams to address production vulnerabilities\n\nSkills and Qualifications\n\nBachelor's degree or equivalent experience in computer science, engineering, or similar.\n\nExperience in distributed systems, cloud infrastructure, or site reliability engineering.\n\nProficiency writing software to solve reliability problems, including building tooling and automation.\n\nExperience with production incident response, postmortems, and systematic reliability improvement.\n\nStrong communication skills and track record of coordination across engineering and research teams.\n\nPreferred qualifications — we encourage you to apply if you meet some but not all of these:\n\nDeep experience operating production cloud services at scale (e.g., public cloud platforms, internal cloud services)\n\nBackground in distributed training frameworks and how infrastructure failures surface in training behavior.\n\nTrack record building checkpoint and recovery systems for long-running distributed jobs.\n\nExpertise in Kubernetes at scale: deploying, operating, debugging, and tuning clusters handling heterogeneous GPU workloads.\n\nLogistics\n\nLocation: This role is based in San Francisco, California.\n\nCompensation: Depending on background, skills and experience, the expected annual salary range for this position is $350,000 – $475,000 USD.\n\nVisa 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.\n\nBenefits: Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.\n\n#J-18808-Ljbffr","datePosted":"2026-07-16T04:03:19.878Z","dateModified":"2026-07-16T04:03:19.878Z","hiringOrganization":{"@type":"Organization","name":"Thinking Machines Lab","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Millbrae","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"3fe87f8a2f07881b2c7970c5"},"url":"https://jobsearcher.com/jobs/3fe87f8a2f07881b2c7970c5"}}