Supercompute Infrastructure Engineer
Menlo Park
Full Time
2 hours ago
Senior LevelEngineeringWorldwide
$80K - $120K

USD per year

Job Description

Supercompute Infrastructure Engineer

Location

Menlo Park, Remote

Address

Menlo Park, California

Employment Type

Full time

Department

Bits: LLMs, machine learning, infra, etc.

About Periodic Labs

We are an AI + physical sciences lab building state of the art models to make novel scientific discoveries. We are well funded and growing rapidly. Team members are owners who identify and solve problems without boundaries or bureaucracy. We eagerly learn new tools and new science to push forward our mission.

About the Role

You will lead, design, build, and operate large-scale compute clusters to power AI scientific research. You will write software that orchestrates large GPU and CPU clusters, manages resource allocation and automates cluster lifecycle operations. You will work on bringup, operations and maintenance of all aspects of these clusters. You will build tools and get directly involved in large scale frontier research experiments to make Periodic Labs the world's best AI + science lab for physicists, computational materials scientists, AI researchers, and engineers. We’re looking for distributed systems engineers with experience in managing large-scale compute environments, high-performance clusters, or similar hyperscale infrastructure.

You might thrive in this role if you have experience with:

  • >=5,000 GPU clusters
  • Cluster scheduling and orchestration tools like k8s and slurm
  • Cloud environments such as GCP, AWS, or Azure
  • Observability and monitoring tools like DataDog, Prometheus, Grafana, or VictoriaMetrics
  • IaC tools like terraform and ansible
  • GitOps tools like Github CI and ArgoCD
How to Apply
About Periodic Labs

Periodic Labs aims to create an AI scientist and autonomous laboratories for them to operate, focusing on accelerating science in the physical sciences. They build AI scientists and autonomous labs to generate high-quality experimental data, enabling new scientific discoveries and applications such as discovering higher-temperature superconductors and aiding semiconductor manufacturers.

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