About the job
As a TPU Kernel Engineer, you'll be responsible for identifying and addressing performance issues across many different ML systems, including research, training, and inference. A significant portion of this work will involve designing and optimizing kernels for the TPU. You will also provide feedback to researchers about how model changes impact performance.
Responsibilities
Identifying and addressing performance issues across many different ML systems, including research, training, and inference; Designing and optimizing kernels for the TPU; Providing feedback to researchers about how model changes impact performance.
Qualifications
Minimum
Have significant experience optimizing ML systems for TPUs, GPUs, or other accelerators; Are results-oriented, with a bias towards flexibility and impact; Pick up slack, even if it goes outside your job description; Enjoy pair programming; Want to learn more about machine learning research; Care about the societal impacts of your work.
Preferred
High performance, large-scale ML systems; Designing and implementing kernels for TPUs or other ML accelerators; Understanding accelerators at a deep level, e.g. a background in computer architecture; ML framework internals; Language modeling with transformers.