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 scientist, the work you will do will significantly move the needle within a Product Area that has high strategic importance to Google - which could be one of our existing collaborations or one of the new ones we will start up in 2017. You will also build close relationships with our partners at Google Research, collaborating on projects of shared interest.
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 from Google Play to Ads to Shopping, and who wish to immerse themselves in some of the most cutting-edge ML and AI research.
- Perform research to make reinforcement learning more applicable to real world problems.
- Provide research consultancy on applied projects: determine the scope of the problem, the best place to apply machine learning, and evaluate different approaches.
- Interface with product teams to identify potential new problem areas for future projects.
- Integrate new fundamental research ideas into applied projects.
- Collaborate with Software Engineers to design and run experiments, including designing and evaluating new algorithms as well as implementing known algorithms.
- Report and present experimental results and research findings clearly and efficiently, both internally and externally.
- PhD in computer science, mathematics, physics, electrical engineering, machine learning or equivalent.
- Proven knowledge of machine learning and/or statistics.
- 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.
- Experience with implementing numerical methods and data visualization.
- Good knowledge of algorithm design.
- Expertise in reinforcement learning and / or deep learning.
- Experience with GPU programming.
- Experience with multi-threaded design and parallel/distributed computing.
- Interest in neuroscience.
- A passion for AI.