Thinking Machines Lab

Thinking Machines Lab

Technical Program Manager, Supercomputing

San Francisco

Sponsorship not specified$350k-$475kDetected 10 days ago
Distributed SystemsMachine LearningForecastingLogisticsResearchMentoring

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odds of building a lasting career here

59Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role80
Entry-level history0
PERM / green-card track0
Lottery odds (Level IV)94
Fits your clock70

Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.

Lottery odds assume a STEM candidate.

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Files H-1B transfers

16 transfer filings in the last year, covering 16 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.

Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.

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About the role

  • Compute allocation is a technical judgment problem.
  • Progress depends on understanding those constraints and finding ways to accomplish more within them.
  • You'll work closely with researchers and infrastructure engineers to understand demand, evaluate competing needs, and translate research priorities into practical allocation decisions.

Responsibilities

  • Own compute allocation. Understand current and upcoming demand, develop allocation plans with technical leads, and carry decisions through to execution.
  • Optimize within constraints. Work through tradeoffs across capacity, hardware suitability, workload size, timing, and dependencies. Help teams adapt their plans as requirements and resources change.
  • Improve productive use of compute. Partner with researchers and engineers to investigate the gap between allocated resources and useful work. Identify opportunities to improve scheduling, workload placement, and utilization.
  • Teach teams to plan and use compute well. Help researchers estimate their needs, understand available options, and recognize the consequences of different choices. Build practical understanding through real workloads and decisions.
  • Make your reasoning transferable. Explain assumptions and tradeoffs clearly. Develop examples, guidance, and tools that enable others to handle recurring decisions and recognize when they need help.
  • Own compute allocation.
  • We support visa sponsorship and work with candidates through the process.

Requirements

  • Experience making consequential resource allocation or capacity decisions in a complex computing environment, with clear ownership of the tradeoffs and outcomes.
  • You can reason about how workload requirements interact with system constraints.
  • Demonstrated ability to improve useful output from limited resources.
  • You can explain what constrained the work, which alternatives you considered, and why your approach helped.
  • Ability to teach complex technical ideas through clear explanations and practical examples.
  • You have helped others become more capable and independent.
  • Comfort investigating usage and performance data directly, questioning assumptions, and changing your view when the evidence warrants it.

Nice to have

  • Experience owning compute allocation at an AI research lab or another organization with substantial shared computing resources.
  • Familiarity with GPU clusters, distributed training, scheduling, and workload placement.
  • Understanding of how networking, storage, reliability, and hardware differences affect usable capacity.
  • Experience mentoring researchers, engineers, or technical program managers in compute planning and resource management.
  • We encourage you to apply even if you don't meet every preferred qualification.

Compensation

  • $350,000 - $475,000 USD annually.

Benefits

  • Health, dental, and vision coverage; unlimited PTO; paid parental leave; and relocation support as needed.
  • Strong technical understanding of distributed systems, machine learning infrastructure, or high-performance computing.

Visa & Work Authorization

  • We support visa sponsorship and work with candidates through the process.
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This listing is sourced directly from Thinking Machines Lab's careers page and normalized into a canonical job model.