Performance Engineering Internship - London



DeepMind is the world leader in artificial intelligence research and its application for positive impact. We’re on a scientific mission to push the boundaries of AI, developing programs that can learn to solve any complex problem without needing to be taught how.

If we’re successful, we believe this will be one of the most important and widely beneficial scientific advances ever made, increasing our capacity to understand the mysteries of the universe and to tackle some of our most pressing real-world challenges, from climate change to radically improved healthcare

The Role

The field of AI research is developing at a fast pace and computational demands are continually growing. The DeepMind Performance team strives to enable researchers to take advantage of new advances in hardware accelerators, such as GPUs and TPUs (Tensor Processing Units). As a Performance Engineering Intern you will work alongside one of our experienced engineers to enable our researchers to effortlessly take advantage of increasing amounts of compute resources.

Possible areas of work

  • Mapping Machine Learning (ML) algorithms to new hardware accelerators
  • Scaling ML workloads to large-scale systems
  • Improving the ML software stack for accelerators
  • Using Machine Learning in Program Optimisation

About You

If you have experience in performance optimisation, parallel computing, compilers or related fields this is a great opportunity to further improve your skills and apply them to make a difference to the exciting field of AI research.

DeepMind welcomes applications from all sections of society.  We are committed to equal employment opportunity regardless of race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity or any other basis as protected by applicable law.  If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.

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