AI Compute Allocation Program Lead

Thinking Machines Lab Inc.; San Francisco (CA); On-site; USD 350,000 - 475,000; Full time

Benefits offered by this job

Health, dental, and vision coverage

Unlimited PTO

Paid parental leave

Relocation support

Job summary

Thinking Machines Lab Inc. in San Francisco invites you to drive compute allocation for frontier AI research. You will own allocation decisions, work with researchers and infrastructure engineers, and translate priorities into practical plans under constraints.

You will teach teams to plan compute needs, improve scheduling and utilization, and develop tools to make recurring decisions. This role rewards clear reasoning, collaboration, and the ability to adapt as workloads evolve.

Qualifications

• Experience making resource allocation decisions in a complex computing environment with clear ownership of tradeoffs and outcomes.
• Strong understanding of distributed systems, ML infrastructure, or HPC; ability to reason about workload interactions and constraints.
• Ability to explain tradeoffs and constraints with clarity and provide practical guidance.
• Ability to teach complex technical ideas through clear explanations and concrete examples.
• Experience mentoring researchers, engineers, or TPMs in compute planning and resource management.

Responsibilities

• Own compute allocation; understand demand, develop allocation plans, and carry decisions through to execution.
• Optimize within constraints across capacity, hardware suitability, workload size, timing, and dependencies.
• Improve productive use of compute; collaborate to close gaps between allocated resources and useful work.
• Teach teams to estimate needs, understand options, and reason through tradeoffs with real workloads.
• Develop examples, guidance, and tools to enable recurring decisions.
• Connect research and infrastructure; align plans with usable capacity and future needs.
• Learn from outcomes; revisit assumptions as workloads and priorities evolve.

Skills

Resource allocation

Distributed systems

Machine learning infra

Teach complex ideas

Data-driven decisions

Cross-team collaboration

Attention to detail

Tools

GPU clusters

Scheduling systems

HPC infrastructure

Job description

Thinking Machines Lab Inc. in San Francisco invites you to drive compute allocation for frontier AI research. You will own allocation decisions, work with researchers and infrastructure engineers, and translate priorities into practical plans under constraints.

You will teach teams to plan compute needs, improve scheduling and utilization, and develop tools to make recurring decisions. This role rewards clear reasoning, collaboration, and the ability to adapt as workloads evolve.