Research Engineer, Structured Intelligence

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.

Snapshot

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. Our approach encourages collaboration across all groups within the Research team, fostering ambitious creativity and innovative research. We have 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

The Structured Intelligence team at DeepMind is interested in approaches that make "infinite use of finite means". We leverage rich inductive biases drawn from physics, numerical methods, symbolic logic, cognitive science, and allied fields to develop AI and ML methods that make best use of data, and generalise broadly and robustly. Some key example areas we focus on are graph neural networks, learning simulation, generative models, and model-based decision-making.

The role

Research Engineers work on a diverse and stimulating range of projects including: developing algorithms and prototype applications, providing software design and programming support to research projects, along with architecting and implementing software libraries. Our Research Engineers are pivotal to our research, and are responsible for driving collaborative research projects through strong technical innovations and engineering implementations. 

Key responsibilities

• Providing software design and programming expertise to research projects - pairing closely with Research Scientists to better engineer and implement novel theoretical ideas.
• Digest and understand complex research papers, theory and practice.
• Own, report and present (verbally and in writing) engineering developments and experimental results to both the immediate and broader research teams, and externally. 
• Architect and implement robust and scalable research libraries.
• Implement and evaluate algorithms - acting as a key contributor to the development and iteration throughout the research cycle. 
• Write high quality code (Python and/or C++) to be shared within a research group or more broadly.
• Promoting engineering excellence through mentoring and reviewing.

The Structured Intelligence team is especially focused on:

• Machine learning (ML) for the physical sciences and/or complex dynamical systems.
• Simulators, partial differential equations, and numerical methods.
• Graph neural networks.
• Combinatorial optimization.
• Model-based decision-making.
• Climate and sustainability-related research.

What we offer

• A variety of complex problems to work on, with the opportunity to learn constantly through experimentation. 
• Access to a team of leading researchers, engineers and problem solvers to learn from - with the opportunity to contribute your own thinking and specialist knowledge to add to our mission.
• Constant learning, training and development opportunities, from technical courses to being a better presenter - design it to work best for you!
• Access to leading technology, ever-evolving tech stacks and Google-scale systems to allow your work to flourish.

About you

In order to set you up for success as a Research Engineer at DeepMind, we look for the following skills and experience:

• BSc/BEng degree in computer science, mathematics, physics, electrical engineering, ML or equivalent.
• Proven experience, either in industry or a research lab, working on complex ML problems and engineering workflows. 
• Strong knowledge and experience of Python.
• Experience with data processing and visualisation.
• Working knowledge of Jax, Tensorflow or similar frameworks.
• Proven knowledge of ML and/or statistics, e.g. deep learning, etc. 
• Strong knowledge of algorithm design - with a proven ability to write ML algorithms from scratch.

In addition, the following would be an advantage: 

• MSc/MEng/PhD degree computer science, mathematics, physics, electrical engineering, ML or equivalent.
• Experience with research and publishing, e.g. authored papers.
• A track record of successful collaborative software development, either open-source or proprietary.
• Experience with simulators, partial differential equations, and/or numerical methods.
• Experience in ML for the physical sciences and/or sustainability.
• Experience with large-scale and/or distributed computing.
• Working knowledge of C/C++.

Closing date: Friday, 18th November 5:00pm GMT