Primeintellect

Primeintellect

Member of Technical Staff - GPU Infrastructure

San Francisco · Staff+

Sponsorship not specified$150k-$300kDetected 13 days ago
PythonBashNode.jsFull-Stack DevelopmentDatabricksDockerKubernetesTerraformAnsibleLinuxDatadogMachine LearningPyTorchLLMsResearchLeadershipCommunication

About the role

  • The next generation of AI companies, enterprises, and research teams do not just need more GPUs.
  • Core Technical Responsibilities This customer-facing role combines deep technical expertise with hands-on implementation.

Responsibilities

  • the infrastructure frontier AI labs build internally, made available to every ambitious AI team.

Requirements

  • 3+ years hands-on experience with GPU clusters and HPC environments
  • Deep expertise with SLURM and Kubernetes in production GPU settings
  • Proven experience with InfiniBand configuration and troubleshooting
  • Strong understanding of NVIDIA GPU architecture, CUDA ecosystem, and driver stack
  • Experience with infrastructure automation tools (Ansible, Terraform)
  • Proficiency in Python, Bash, and systems programming
  • Track record of customer-facing technical leadership
  • This customer-facing role combines deep technical expertise with hands-on implementation.

Nice to have

  • Experience with 1000+ GPU deployments
  • NVIDIA DGX, HGX, or SuperPOD certification
  • Distributed training frameworks (PyTorch FSDP, DeepSpeed, Megatron-LM)
  • ML framework optimization and profiling
  • Experience with AMD MI300 or Intel Gaudi accelerators
  • Contributions to open-source HPC/AI infrastructure projects
  • Growth Opportunity

Compensation

  • Cash Compensation Range of $150-300k plus Equity Incentives

Company info

  • Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models.

This listing is sourced directly from Primeintellect's careers page and normalized into a canonical job model.