GPU Kernel Engineer
Location: Hybrid (preferably SF or Vienna), San Francisco, CA
Salary: Competitive Salary, Competitive Equity
Job Type: Full-time
Our Company:
We are a public benefit corporation dedicated to building and safely deploying aligned, superhuman AGI. Our mission is to build a future where productivity and ingenuity are no longer limited by human labor. Our focus is on the development and deployment of AGI, which represents the ultimate evolution in the human journey of tool-building and automation. We believe that this vision is possible and are dedicated to realizing it.
Our Mission:
We are a public benefit corporation dedicated to building and safely deploying aligned, superhuman AGI. We are looking for candidates who are aligned and mission-driven.
We are looking for an exceptional GPU Kernel Engineer who will work on ensuring high throughput and low latency during training and inference with giant neural networks.
Responsibilities:
- 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.
Requirements:
- 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 attention to Denis Somoso, Head of Talent Acquisitions to email address: careers [ at ] alphaaiweb3.com or by clicking the "apply now" button below.
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