We are looking for a Senior Researcher - GPU Performance – Hardware/Software Codesign researcher to explore hardware/kernel-level optimizations to deliver significant efficiency gains for Large Language Models and Generative AI experiences. The qualified candidate will have a solid background in GPU architecture, accelerator design, machine learning, or systems research and the ambition to apply them to large scale production systems. This role combines deep technical knowledge in GPU architecture with practical implementation skills to create efficient, scalable computational kernels. Further, the qualified candidate is expected to demonstrate a history of solving hard technical problems and is motivated to tackle the hardest problems in building a full end-to-end AI stack. An entrepreneurial approach and ability to take initiative and move fast are essential.

Design, implement, and optimize GPU kernels for complex computational workloads such as AI inferencing.

Research and develop novel optimization techniques for generation of GPU kernels.

Profile and analyze kernel performance using advanced diagnostic tools.

Generate automated solutions for kernel optimization and tuning.

Collaborate with other researchers to improve model performance.

Document optimization strategies and maintain performance benchmarks.

Contribute to the development of internal GPU computing frameworks.