Machine Learning Systems Administrator - HPC Infrastructure

As a Machine Learning Systems Administrator - HPC Infrastructure, you will be responsible for maintaining and developing the core infrastructure behind our machine learning research and production efforts. You’ll work closely with various training and inference teams to ensure the smooth operation of our systems while laying the groundwork for scalable, secure, and efficient workflows.

• Administration and automation of our Linux-based cluster environments

• Managing user onboarding/offboarding, security auditing, and access control

• Monitoring system resources and job scheduling

• Supporting and improving developer workflows (e.g., VSCode compatibility, Docker)

• Enabling and supporting AI/ML workloads, including large-scale training jobs

• Comfortable operating across a wide range of infrastructure concerns and excited to own and improve critical systems.

• You’ll have a significant impact on both developer productivity and training and inference performance.

• Strong experience with Linux system administration, user and access management, and automation

• Demonstrated expertise in scripting languages for system tooling and automation (bash, Python, etc.)

• Familiarity with containerized environments (e.g., Docker) and job scheduling systems like Slurm

• Experience building tooling for cluster validation and reliability (GPU, networking, storage health checks)

• Experience setting up and managing developer tools and third-party services (e.g, Cloud storage providers, Dockerhub, Slack, Gmail, Telegraf, experiment trackers, etc.)

• Excellent debugging and troubleshooting skills across compute, storage, and networking

• Strong communication skills and ability to collaborate across technical and non-technical teams

• Experience with infrastructure as code (e.g., Ansible, Terraform)

• Prior work supporting ML/AI infrastructure, including GPU management and workload optimization

• Exposure to backend development for ML model serving (e.g., vLLM, Ray, SGLang)

• Experience working with cloud platforms such as AWS, Azure, or GCP

• Familiarity with containers (Docker, Apptainer) and their integration with scheduling systems (Slurm, Kubernetes)

• Our research methodology is grounded in methodical, step-by-step approaches to ambitious goals. Both deep research and engineering excellence are equally valued

• We strongly value new and crazy ideas and are very willing to bet big on new ideas

• We move as quickly as we can; we aim to minimize the bar to impact as low as possible

• We all enjoy what we do and love discussing AI

• Comprehensive medical, dental, vision, and FSA plans

• Competitive compensation and 401(k) plan

• Relocation and immigration support on a case-by-case basis

• In-office snacks and meals provided

• Unlimited PTO and company holidays

• In-person team in San Francisco with a collaborative, high-energy environment