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Software Engineer, Kernels/CUDA (C++)

Reposted 2 Months Ago
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In-Office
Seattle, WA, USA
180K-440K Annually
Senior level
In-Office
Seattle, WA, USA
180K-440K Annually
Senior level
Design, build, and optimize massive GPU clusters and low-level CUDA kernels for AI training and inference. Work on Linux kernel internals, virtualization (KVM, Firecracker), custom orchestration, profiling, and infrastructure-as-code to maximize performance and scalability for production AI workloads.
The summary above was generated by AI

SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars.
SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next.

SOFTWARE ENGINEER, KERNELS/CUDA (C++)

We are building one of the world’s largest AI supercomputers from the ground up. As part of the Compute Infrastructure team, you will own both the raw GPU supercomputer and the platform layer that runs on top of it. You will work across the full stack — from low-level GPU kernel optimizations and Linux kernel internals to massive-scale orchestration and virtualization — to make training and inference at SpaceXSI as fast, reliable, and scalable as possible.

This is a broad, high-impact role that combines hardcore supercompute and compute infrastructure work. Your contributions will directly accelerate Grok’s training speed and overall AI progress.

RESPONSIBILITIES:

  • Design, build, and optimize massive GPU clusters for extreme-scale training and inference workloads
  • Develop and tune low-level CUDA kernels (GeMM, Attention, etc.), using CUTLASS, Tensor Cores, and Nsight for maximum performance
  • Profile, debug, and eliminate bottlenecks across GPU memory hierarchy, networking fabric, filesystems, and multi-GPU operation
  • Collaborate closely with AI research teams to deliver production-grade performance and scalability

PREFERRED SKILLS AND EXPERIENCE:

  • Deep low-level systems programming (C/C++/PTX/SASS)
  • Strong experience with large-scale GPU clusters or distributed compute infrastructure at production scale
  • Hands-on work with GPU kernel optimization (CUTLASS, custom kernels, Nsight profiling)
  • Track record of building or running high-performance infrastructure for AI workloads (training or inference platforms)
  • Ability to reason from first principles and optimize for both memory-bound and compute-bound scenarios

COMPENSATION AND BENEFITS:

$180,000 - $440,000 USD

Base salary is just one part of our total rewards package at SpaceXSI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks.

SpaceXSI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice.

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