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We are looking for a software engineer passionate about improving the performance of cutting-edge ML models on hardware accelerators. You will be part of a team responsible for deploying models, e.g. large language models (LLMs), at scale for use throughout Alphabet. This involves working across the stack, from ML frameworks to compilers, with the aim to serve models at maximum efficiency.
Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.
The rising use of large language models (LLMs) demands efficient and performant serving solutions. As a member of the deployment team you will help us improve the efficiency of our model serving stack, and optimize the performance of the latest models on Google’s fleet of hardware accelerators - throughout the entire LLM deployment lifecycle.
This involves:
This role provides an opportunity to work on a broad set of problems and gain a broad understanding of ML models and hardware performance.
Depending on your skills and interests, some of your responsibilities will be:
In order to set you up for success as a Software Engineer at Google DeepMind, we look for the following skills and experience:
In addition we are looking for experience with at least two of the following:
Application deadline: 5pm BST, Friday 3rd May 2024
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