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Research Engineer, Applied ML (Mountain View)
The DeepMind Applied group collaborates with teams at Google and elsewhere to apply our cutting-edge research to products and infrastructure used by many millions of people across the world.
We’re very proud to already have very close partnerships with many teams at Google, with a diverse portfolio of projects touching many Google product areas.
Our new DeepMind Applied team in Mountain View will engage in much of this important work with our partners at Google, in close collaboration with the DeepMind team back in London.
The Applied team in Mountain View will be made up of a mixture of software engineers and research scientists who work together to solve real-world problems at Google-scale.
As an Applied Research Engineer, you’ll design and build the infrastructure, tools, and libraries needed to train, experiment, debug, and launch machine learning models at scale. You’ll work closely with engineers and scientists from our team and from product teams to deploy our models in their serving stacks. You’ll assist in running and analysing live experiments and full launches. Due to the focus of the role on systems and infrastructure no prior machine learning experience is necessary.
As a full-time member of DeepMind, you will work in close partnership with the London DeepMind Applied team. You will be encouraged, especially early on, to spend as much time as is practical in London.
DeepMind Applied uses TensorFlow as our main infrastructure. The London team has been seeded with several senior ex-Googlers and DeepMind Applied’s code practices and processes are very much aligned with Google’s.
The role will suit candidates who enjoy metrics-driven work, building momentum through successive experiments and launches anywhere, such as Google Play, and who wish to immerse themselves in some of the most cutting-edge ML and AI research.
• Bachelors in computer science, mathematics, physics, electrical engineering, machine learning or equivalent.
• Flexible in choice of programming language. Competent in one or more of the Google supported languages (C++, Java, Python, Go) with a desire to learn more.
• Knowledge of algorithm design.
• Expertise in reinforcement learning and / or deep learning.
• Experience with multi-threaded design and parallel/distributed computing.
• A passion for AI.