Supercompute Engineer
Periodic Labs - Menlo Park, California, United States
Posted Apr 30, 2026
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- Salary
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- 401(k) match
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Schedule
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- Weekend work
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Where they hire
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About this role
Supercompute Engineer Menlo Park, California, United States About Periodic Labs The most important scientific discoveries of our time won't happen in a traditional lab. We're an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what's scientifically possible. About the Role As a Supercomputing Engineer at Periodic Labs, you will design, build, and operate the high-performance computing infrastructure that powers our AI and scientific research. Our models demand extreme compute at scale - large GPU and CPU clusters, high-speed interconnects, low-latency parallel storage, and workload schedulers that make every cycle count. You will work directly with researchers and infrastructure engineers to ensure our compute environment is fast, reliable, and optimized for scientific discovery at the frontier. This is a deeply hands-on role. You will architect and tune systems, automate provisioning, diagnose performance bottlenecks, and design for resilience at scale. You'll partner with research and ML teams to understand their workloads and shape an HPC environment that removes friction and accelerates science. What You'll Do - Design, deploy, and operate large-scale GPU and CPU clusters for AI training, scientific simulation, and research workloads - Manage and optimize high-speed interconnect fabrics (InfiniBand, RoCE) and parallel filesystems (Lustre, GPFS, WEKA, or equivalent) for maximum throughput and minimum latency - Own workload scheduling and resource management
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