Lead AI Infrastructure Engineer — Distributed Training GPUs

SpaceX Super Intelligence; Palo Alto (CA); On-site; USD 180,000 - 260,000; Full time

Benefits offered by this job

Equity

Medical Coverage

Vision Coverage

Dental Coverage

401(k) Retirement Plan

Short-Term Disability Insurance

Long-Term Disability Insurance

Life Insurance

Discounts And Perks

Job summary

SpaceX Super Intelligence is seeking a lead software infrastructure engineer to design, implement, and maintain reliable, high-performance infrastructure for training Grok models on large GPU clusters. You will set technical direction for training architectures and hardware, and build prototypes.

You will collaborate with engineering and operations teams, and lead planning and milestone execution to deliver scalable AI training platforms that meet reliability and efficiency goals.

Qualifications

• A bachelor's degree in computer science, engineering, mathematics, or another technical discipline is required.
• Hands-on systems programming experience in C or C++ is required.
• Strong knowledge of computer architecture and networking, modeling, debugging, performance optimization, and unit testing is desired.

Responsibilities

• Lead the team that designs, implements, and maintains reliable, performant software infrastructure for training Grok models across large GPU clusters.
• Set technical direction for training architectures and hardware.
• Develop prototypes.
• Collaborate across engineering and operations teams.
• Lead planning and milestone execution.

Skills

C

C++

Systems Programming

Distributed Training

AI Infrastructure

Software Reliability

Technical Leadership

Education

Bachelor's degree in Computer Science or related

Tools

Networking

Unit Testing

Job description

SpaceX Super Intelligence is seeking a lead software infrastructure engineer to design, implement, and maintain reliable, high-performance infrastructure for training Grok models on large GPU clusters. You will set technical direction for training architectures and hardware, and build prototypes.

You will collaborate with engineering and operations teams, and lead planning and milestone execution to deliver scalable AI training platforms that meet reliability and efficiency goals.