Research Engineer, Scalable Deep Learning

Mountain View, California, US

Full Time Senior-level / Expert
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Artificial intelligence could be one of humanity’s most useful inventions. We research and build safe artificial intelligence systems. We're committed to solving intelligence, to advance science and benefit humanity.

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Applications will close at 6pm BST on Friday 19th August and will be reviewed shortly thereafter.

At DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy or related condition (including breastfeeding) 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.



At DeepMind, we've built a unique culture and work environment where long-term ambitious research can flourish. Our special interdisciplinary team combines the best techniques from deep learning, reinforcement learning and systems neuroscience to build general-purpose learning algorithms. We have already made a number of high profile breakthroughs towards building artificial general intelligence, and we have all the ingredients in place to make further significant progress over the coming years!


About us

We’re a dedicated scientific community, committed to “solving intelligence” and ensuring our technology is used for widespread public benefit. 

We’ve built a supportive and inclusive environment where collaboration is encouraged and learning is shared freely. We don’t set limits based on what others think is possible or impossible. We drive ourselves and inspire each other to push boundaries and achieve ambitious goals.

We constantly iterate on our workplace experience with the goal of ensuring it encourages a balanced life. From excellent office facilities through to extensive manager support, we strive to support our people and their needs as effectively as possible

The Scalable Deep Learning team develops architectures and methods that reliably benefit from increases in data, model size and computational resources. We combine new architectures, theoretical insights and world-class engineering to expand the capabilities of DeepMind's large-scale models.


The role

Research Engineers at DeepMind apply their research and engineering skills to accelerate our research progress through prototypes, scaling up algorithms, overcoming technical obstacles, and designing, running, and analysing experiments.

Working in a collaborative environment that fosters learning and development, you will contribute to DeepMind's efforts that develop large-scale deep learning models. Over time you'll continue to deepen and broaden your knowledge on a range of research and engineering topics in large-scale deep learning.

Key responsibilities:

  • Design, implement and evaluate scalable deep learning methods.
  • Report and present research findings and developments including status and results clearly and efficiently both internally and externally, verbally and in writing.
  • Collaborate with the team to meet ambitious research goals


About you


  • Experience writing code in Python.
  • Bachelor's degree in a technical subject (e.g. machine learning, AI, computer science, mathematics, physics, statistics, etc.), or equivalent experience.

Nice to haves :

  • Experience writing code in C++.
  • Knowledge of ML/scientific libraries such as TensorFlow, JAX, PyTorch, NumPy and Pandas.
  • Machine learning experience in industry, academia and personal projects, whether in computer science or other fields such as physics, computational biology, or mathematics.
  • Experience implementing or using distributed systems, for example databases, highly available web APIs, large-scale deep learning training setups, etc.


Tags: Deep Learning Distributed Systems Engineering Machine Learning ML NumPy Pandas Python PyTorch Research Statistics TensorFlow

Region: North America
Country: United States
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