Linux Kernel Engineer for AI Supercomputers

Socket.dev; Palo Alto (CA); On-site; USD 180,000 - 440,000; Full time

Benefits offered by this job

Equity

Medical

Vision

Dental

401(k)

Disability insurance

Life insurance

Perks and discounts

Job summary

SpaceXAI designs, builds, and operates the largest AI supercomputers. As a member of the Platform Core team, you will own the lean Linux-based OS and drivers that drive the hardware, collaborating with hardware teams to push the frontier of AI.

You will deploy, operate, and debug the platform in production, resolve anomalies, and develop observability and configuration tools, while keeping the footprint small and robust.

Qualifications

• Hands-on systems programming experience in C or C++.
• Strong operating systems fundamentals (scheduling, memory management, I/O).
• Understanding of computer networking (host OS stack, switches/routers).
• Excellent written and verbal communication skills.

Responsibilities

• Build and maintain the lean, high-reliability Linux-based OS underpinning our supercomputer network fabric.
• Write (or rewrite) high-performance device drivers to extract the maximum physical capability from our network and compute hardware.
• Manage deployment, operation, and debugging of our platform in production, including:
• Rigorous resolution and root-causing of anomalies to ensure the system is constantly improving in reliability.
• Developing and constantly improving our tools for observability and configuration management.
• Collaborate with our hardware teams and external partners to design the next generation of supercomputer hardware - and then bring up our OS and software stack on it.

Skills

Systems programming (C/C++)

OS fundamentals

Networking basics

Communication skills

Tools

ftrace

perf

Wireshark

tcpdump

eBPF

gdb

Job description

SpaceXAI designs, builds, and operates the largest AI supercomputers. As a member of the Platform Core team, you will own the lean Linux-based OS and drivers that drive the hardware, collaborating with hardware teams to push the frontier of AI.

You will deploy, operate, and debug the platform in production, resolve anomalies, and develop observability and configuration tools, while keeping the footprint small and robust.