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GPU Kernel Engineer

GPU Kernel Engineer

GPU Kernel Engineer

Location: Hybrid (preferably SF or Vienna), San Francisco, CA

Salary: Competitive Salary, Competitive Equity

Job Type: Full-time


  • Implement high-throughput low-latency GPU kernels in CUDA or Triton
  • Efficient mixed-precision training and inference
  • Optimize kernel fusions
  • Profile and benchmark competing implementations
  • Maximize multi-GPU communication through efficient overlapping of communication and computation
  • Ensure the compatibility of GPU driver software with the latest operating systems
  • Develop and maintain GPU driver software
  • Develop and implement high-performance algorithms and data structures for GPU processing
  • Collaborate with other engineers to debug and resolve software issues
  • Continuously learn new GPU technologies and architectures
  • Write technical documentation and provide feedback on product design.


  • At least 8 years of relevant software development experience
  • 5+ years of experience in GPU kernel development and optimization
  • MS or PhD in Computer Science, Electrical Engineering, or related field
  • Strong proficiency in C and C++ programming languages
  • Strong programming skills in CUDA and C++
  • Experience with GPU hardware and programming models (e.g., CUDA, OpenCL, Metal, Vulkan)
  • Experience with GPU profiling and performance analysis
  • Experience with deep learning frameworks such as TensorFlow or PyTorch
  • Familiarity with GPU architectures, including memory hierarchy and parallel computing
  • Knowledge of software development best practices, including debugging, testing, and version control
  • Excellent problem-solving and analytical skills
  • Strong communication and collaboration skills.

Benefits and Perks:

  • Benchmark-based compensation in the 75th or 90th percentile, including base salary, equity, and benefits
  • Flexible working hours
  • In-person (SF or Vienna) or remote work options
  • A small, fast-paced, highly focused team.

The Ideal Candidate:

We are looking for an ambitious and high-energy individual who is aligned and mission-driven. The ideal GPU Kernel Engineer will work on ensuring high throughput and low latency during training and inference with giant neural networks. While experience is important, we value a budding superstar over an 8-year experienced engineer with a PhD whose experience looks perfect on paper but may not be the right fit for our team. We want a candidate who is joining a mission-driven team that’s well-equipped with the best talent to build aligned and more complete AI to accelerate humanity’s progress on the world’s most important problems.

To apply, the interested candidate may submit his/her updated English resume to the email address: careers [ at ] or by clicking the "apply now" button below.