Lead AI Infrastructure Engineer — GPU Clusters & Equity

SpaceX Super Intelligence; Seattle (WA); On-site; USD 180,000 - 280,000; Full time

Benefits offered by this job

Equity

Medical Insurance

Vision Insurance

Dental Insurance

401(k) Retirement Plan

Short-Term Disability Insurance

Long-Term Disability Insurance

Life Insurance

Discounts And Perks

Job summary

SpaceX Super Intelligence in Seattle is seeking a senior software infrastructure leader to design, implement, and maintain reliable, high-performance training systems for Grok models across large GPU clusters. You will set technical direction for training architectures and hardware and drive prototypes, collaborating with engineering and operations teams.

You will lead planning and milestone execution, mentor engineers, and ensure robust performance, scalability, and testing.

Qualifications

• Bachelor's degree in computer science, engineering, mathematics, or a related technical discipline is required.
• Hands-on systems programming experience in C or C++ is required.
• Strong knowledge of GPU systems, computer architecture, networking, modeling, debugging, performance optimization, and testing is preferred.

Responsibilities

• Lead the team designing, implementing, and maintaining reliable, high-performance software infrastructure for training Grok models across large GPU clusters.
• Set technical direction for training architectures and hardware.
• Develop prototypes and collaborate across engineering and operations teams.
• Lead planning and milestone execution.

Skills

C

C++

Systems Programming

Software Engineering

AI Infrastructure

Distributed Training

Computer Architecture

Networking

Performance Optimization

Debugging

Unit Testing

Fault Tolerance

Technical Leadership

Modeling

Analytical Skills

Education

Bachelor's degree in Computer Science or related technical field

Job description

SpaceX Super Intelligence in Seattle is seeking a senior software infrastructure leader to design, implement, and maintain reliable, high-performance training systems for Grok models across large GPU clusters. You will set technical direction for training architectures and hardware and drive prototypes, collaborating with engineering and operations teams.

You will lead planning and milestone execution, mentor engineers, and ensure robust performance, scalability, and testing.