over 2 years ago
Base Salary
$225k - $550k/yr
Responsibilities
- Design and implement kernels supporting high-performance long-context behavior.
- Own kernel design, implementation, deployment, and production reliability.
- Prioritize robustness, extensive testing, functional correctness, and performance optimization.
- Evaluate porting compute kernels to alternative hardware options.
- Co-design kernels with the training, inference, and reinforcement learning teams.
Requirements
- Low-level programming experience targeting AI accelerators such as NVIDIA Blackwell or Google TPUs.
- Experience developing and optimizing GPU kernels with frameworks such as NCCL, MSCCLPP, CUTLASS, CuTeDSL, Triton, Quack, and Flash-Attention.
- Experience with kernel authoring frameworks such as Pallas, Mosaic, or Mojo is also relevant.
- Deep expertise in computer architecture, low-level machine optimizations, and code generation, with breadth across machine learning.
- Agility, an ownership mindset, and grit.
Benefits
- Annual salary range of $225K-$550K based on experience, plus significant equity.
- 401(k) plan with 6% salary matching.
- Health, dental, and vision insurance for employees and dependents.
- Unlimited paid time off.
- Visa sponsorship and relocation stipend to San Francisco, if possible.
- Small, fast-paced, highly focused team.
Categories
About Magic
Magic builds frontier-scale code models designed to act as an AI coworker for software developers and engineering teams, automating code generation and research tasks. Its products center on developer-facing models and tooling that integrate into software workflows for teams seeking higher velocity and reliability. Founded in 2022 and headquartered in San Francisco, the privately held company focuses on AI-driven developer tools spanning information technology and machine learning.