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GPU Kernels Engineer

Optimize GPU kernels for efficient training and inference, maximizing performance and hardware utilization.
San Francisco Bay Area
Senior
3 months ago

✨ About The Role

- Develop high-performance GPU kernels focusing on utilization and application performance - Make aggressive optimizations to overcome hardware limitations and develop low precision algorithms for high performance - Collaborate with ML engineers to create model architectures suitable for efficient training and inference - Work with the scaling team to deploy kernels and manage training uptime - Advise on HW/SW co-design and work with hardware vendors to optimize performance

⚡ Requirements

- Strong coding skills in C/C++ and Python with a deep understanding of GPU and/or other AI accelerators - Experience with CUDA or a related accelerator programming language and driving ML accuracy with low precision formats - Ability to collaborate with infrastructure and ML engineers, with at least 3+ years of relevant industry experience - Thrives on achieving performance improvements and has a background in Computer Science and Engineering - Enjoys working on high-performance GPU kernels and optimizing for efficiency and performance
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GPU Kernels Engineer
San Francisco Bay Area
Engineering
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