Technical Program Manager, Supercomputing Resources

Bison; San Francisco (CA); On-site; USD 350,000 - 475,000; Full time

Benefits offered by this job

Health coverage

Dental coverage

Vision coverage

Unlimited PTO

Parental leave

Relocation assistance

Job summary

Thinking Machines is looking for a role that owns compute allocation and helps optimize supercomputing resources. You’ll collaborate with researchers and infrastructure engineers to translate priorities into practical allocation decisions, balancing constraints and demand.

You will teach teams to plan compute usage, explain tradeoffs, and develop tools that make specialized knowledge available across the team, improving planning and outcomes.

Qualifications

• Experience making consequential resource allocation or capacity decisions in a complex computing environment, with clear ownership of the tradeoffs and outcomes.
• Strong technical understanding of distributed systems, machine learning infrastructure, or high-performance computing. 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.
• Sound judgment when teams have competing priorities. You earn trust, explain difficult decisions, and work constructively through disagreement.
• A hands‑on, collaborative approach with strong attention to detail and follow‑through.

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.
• Improve productive use of compute. Partner with researchers and engineers to close gaps between allocated resources and useful work.
• Teach teams to plan and use compute well. Help researchers estimate needs, understand options, and reason through tradeoffs.
• Make your reasoning transferable. Explain assumptions and tradeoffs clearly; develop examples and tools for recurring decisions.
• Connect research and infrastructure. Keep plans grounded in usable capacity and anticipate future needs.

Skills

Resource allocation

Distributed systems

ML infrastructure

Data analysis

Mentoring teams

Communication

Job description

Thinking Machines is looking for a role that owns compute allocation and helps optimize supercomputing resources. You’ll collaborate with researchers and infrastructure engineers to translate priorities into practical allocation decisions, balancing constraints and demand.

You will teach teams to plan compute usage, explain tradeoffs, and develop tools that make specialized knowledge available across the team, improving planning and outcomes.