Machine Learning Systems Administrator - HPC Infrastructure

Zyphra • San Francisco, CA

7d • Onsite

About The Position

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.
You’ll work across:
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.

Requirements

• 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

Nice To Haves

• 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)

Responsibilities

• 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

Benefits

• Comprehensive medical, dental, vision, and FSA plans
• Competitive compensation and 401(k)
• Relocation and immigration support on a case-by-case basis
• On-site meals prepared by a dedicated culinary team; Thursday Happy Hours
• In-person team in San Francisco, California. with a collaborative, high-energy environment

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed