CUDA Kernels Engineer

Key Responsibilities

• Develop high-performance GPU/CPU kernels and make trade-offs that maximize end-to-end hardware utilization
• Utilize knowledge of hardware features and performance characteristics to make aggressive optimizations
• Work with our other platform teams to deploy your kernels, manage our training uptime, and find opportunities for optimization
• Develop low-precision algorithms that deliver high performance with little loss of ML accuracyWork with ML engineers to develop model architectures that are amenable to efficient training and inference
• Work with hardware vendors and advise on HW/SW co-design

Job Requirement

• A strong coder with excellent skills in C/C++ and Python
• Have a deep understanding of GPU, CPU, or other AI accelerator architectures
• Have experience writing and optimizing compute kernels with CUDA or similar languages
• Are familiar with LLM (and/or other foundation model) architectures and training infrastructure
• Have experience driving ML accuracy with low-precision formatsHave 1+ years of relevant industry experience
• Get a great deal of satisfaction with every percentage point in performance improvement
• Senior Engineer for Ph.D. with 2-3 years working experience or Engineer with M.S. with 3-5 year working experience

Preferred Qualifications

• PhD in Computer Science and Engineering with a specialization in Computer Architecture, Parallel Computing, Compilers, or other Systems
• Experience building compilers
• Experience working with hardware developers