The company is looking to improve the performance and efficiency of its AI systems by developing new kernels and algorithms for AI model inference.
Requirements
- Expertise in systems engineering across the tech stack
- Deep understanding of GPU architectures
- Strong holistic background in neural network performance and tooling
- Published research at top AI conferences
- C++/CUDA, GPGPU, Python, Linux
Responsibilities
- Develop or extend parallel generic GPU libraries and kernels
- Help design and deploy market-based resource management systems
- Quickly investigate and summarize options for new system architectures
- Prototype and evaluate novel state-of-the-art methods/models
- Investigate and learn new frameworks and tools
Other
- Full-Time
- On-site at either our SF or LA offices
- Strong intrinsic drive, a true passion for advancing the state of the art, and a mix of excellent research, coding, and communication skills
