Research Engineer Intern 2023, London

London, UK

Applications have closed


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...

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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.


Our 2023 internship programme offers students from a variety of academic backgrounds to gain experience in the field of Engineering & AI. This is a fantastic opportunity to lay the groundwork for a successful career by working in any one of our specialist teams. 

About us

At DeepMind, we've built an outstanding culture and work environment where long-term ambitious research can thrive. 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 you

We welcome applications from current students at any level (Bachelors, Masters, Doctorate) who have completed at least two years by the time the internship starts of university-level study in a technical subject (computer science, engineering, maths, physics, etc.)

You need to have full fluency and be comfortable to complete a project in Python. You should have an interest in AI or machine learning, but experience or formal study is not a requirement. We are strongly interested in profiles eligible for full-time opportunities after the internship if the conditions are met.

The role

As a Research Engineering intern at DeepMind, you will utilise software engineering and a research mindset to advance our groundbreaking AI research programme in collaboration with other members of the team.

Our interns work on a project together with the support and mentorship of a host Research Engineer. Whatever project you work on, you will be part of a diverse, interdisciplinary, collaborative team of highly talented people.

Our interns work on a diverse and stimulating range of projects including: developing new learning algorithms and prototype applications, creating analysis and visualisation tools to analyse the behaviour of our agents, and prototyping DeepMind Research to solve impactful real world problems in partnership with Google.

Machine learning experience is not required for this internship position!

We are hiring Research Engineering Interns across four teams. Please indicate your team preferences when applying for this role.

Core Research Engineering

The Core Research Engineering team at DeepMind focusses on pushing the boundaries of Machine Learning and Artificial Intelligence theory & practice, working in collaboration with others to enable DeepMind to succeed on its mission: solve intelligence to advance science and benefit humanity. This fundamental research includes but is not limited to deep neural network models, reinforcement learning algorithms and biologically-inspired models with the overall goal of building powerful general-purpose learning algorithms. We work alongside scientists and engineers from other parts of the organisation.


The Robotics lab is a group of multidisciplinary research scientists, research engineers, and software engineers who pioneer new approaches in robotics. Robotics is a critical part of developing general-purpose learning algorithms because systems must learn to deal with the incredible complexity and ever- changing conditions of the real world. We collaborate with multiple teams across DeepMind to endow our systems with the ability to learn, allowing them to respond and adapt to a variety of variable environments. In particular, we focus on learning complex manipulation and navigation tasks and understanding how systems respond to the physical world.


Science is at the heart of everything we do at DeepMind. From the very beginning, we took inspiration from science to build better algorithms. Now, we want to use our toolkit to accelerate scientific discovery. This multidisciplinary team of researchers and engineers work on innovative projects where AI can impact our fundamental understanding of the physical world. Projects within the Science group explore the potential for AI to enable breakthroughs in biology, quantum chemistry, energy, mathematics and material design; all critical to solving many of the world’s most intractable problems. 


The Applied team applies DeepMind’s cutting-edge research to Google products and infrastructure used by millions of People. Our core teams are based in London and Mountain View, California, and work on a variety of applications for machine learning. Our collaborative efforts have reduced the electricity needed for cooling Google’s data centres by up to 30%, used WaveNet to create more natural voices for the Google Assistant, and created on-device learning systems to optimise Android battery performance. Partnering with Google provides us with a unique set of opportunities and capabilities, allowing us to translate our research breakthroughs into real-world products and solutions. In this way, we can demonstrate the benefits of our work and build towards a positive, inclusive and responsible AI future.



Job stats:  474  196  2

Tags: Biology Chemistry Computer Science Deep Learning Engineering Machine Learning Mathematics Physics Prototyping Python Research Robotics

Perks/benefits: Career development

Region: Europe
Country: United Kingdom

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