Design and implement kernels that support high-performance long-context behavior
Ownership of kernel design, implementation, deployment, and production reliability
Focus on robustness, extensive testing, and functional correctness, while pushing on performance
Evaluate porting Magic’s compute kernels to alternative hardware options
Co-design kernels with understanding and interaction with training, inference, and RL teams

Requirements

Low-level programming experience targeting AI accelerators such as NVIDIA Blackwell or Google TPUs
Develop and optimize GPU kernels in frameworks such as NCCL, MSCCLPP, CUTLASS, CuTeDSL, Triton, Quack, Flash-Attention, and similar frameworks
Experience in other kernel authoring frameworks such as Pallas/Mosaic (GPU or TPU), or Mojo also maps well to the work on Magic's kernel team
Strong depth over shallow breadth: for kernel engineering, we prefer candidates with deep expertise in computer architecture, low-level machine optimizations, and code generation, with breadth across ML
Agility, ownership mindset, and grit

Benefits

Annual salary ranges between $225K - $550K based on experience
Equity is a significant part of total compensation, in addition to salary
401(k) plan with 6% salary matching
Generous health, dental and vision insurance for you and your dependents
Unlimited paid time off
Visa sponsorship and relocation stipend to bring you to SF, if possible
A small, fast-paced, highly focused team

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

low-level programmingGPU kernelskernel designperformance optimizationcomputer architecturecode generationmachine optimizationsfunctional correctnessextensive testingAI accelerators

Soft Skills

ownership mindsetagilitygrit