Research Scientist, ML Efficiency, Google Research

Who you are

You hold a PhD degree in Computer Science or a related field, or possess equivalent practical experience. You have a track record of scientific publication submissions for conferences, journals, or public repositories such as CVPR, ICCV, NeurIPS, ICML, and ICLR. Your experience includes working in university or industry labs with a primary focus on AI research, showcasing your understanding of transformer architecture internals. You possess excellent technical leadership and communication skills, enabling you to conduct multi-team cross-functional collaborations effectively. Your passion lies in deep/machine learning, computational statistics, and applied mathematics, driving your commitment to advancing the field.

What you'll do

As a Research Scientist at Google, you will set up large-scale tests and deploy promising ideas quickly and broadly, managing deadlines and deliverables while applying the latest theories to develop new and improved products, processes, or technologies. You will create experiments and prototype implementations, designing new architectures that address real-world problems across the breadth of computer science. Your role will involve optimizing the end-to-end model deployment pipeline, including entirely new formulations of pretraining, instruction tuning, and reinforcement learning. You will collaborate with hardware and software teams to optimize kernels and inference engines across different hardware and model architectures, focusing on improving latency, memory bandwidth, and workloads.

What we offer

At Google, you will be part of a dynamic research environment that encourages innovation and exploration. You will have the freedom to emphasize specific types of work while contributing to a portfolio of research projects driven by fundamental research, new product innovation, and infrastructure goals. The collaborative culture at Google fosters an atmosphere where your ideas can flourish, and you will have the opportunity to work alongside some of the brightest minds in the industry. We encourage you to apply even if your experience doesn't match every requirement, as we value diverse perspectives and backgrounds.