Software Engineer, Science London, England
Job description
At Google 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
Our 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.
The role
Accelerate research in the natural and physical sciences with a group of research scientists and engineers on a mission-driven team. Together, you will apply ML and other computational techniques to a wide range of challenging problems. Some public examples of our recent work are in protein folding and quantum chemistry, and we are actively pursuing other exciting projects across many scientific disciplines.
Collaborate with researchers and engineers to develop and run experiments exploring new applications of AI in various scientific domains. The team is pioneering in many different areas, from the foundational to the practical, and you may take part in exploratory work, work in a maturing area, or general infrastructure.
Key responsibilities:
- Use your domain knowledge in the sciences (if applicable) to design, develop and implement high-performance simulations, tools, and analyses to challenge root cause scientific theories.
- Apply your software engineering expertise to produce high quality, reusable code and components to tackle meaningful problems in the natural sciences.
- Share ideas with other specialists in the team and be highly collaborative, striving to cultivate a culture of continuous development and advancement.
- Employ cutting-edge technology and techniques to contribute to solving some of the hardest problems.
- Incorporate your passion for science and any previous knowledge or academic experience to join a team of hardworking individuals who openly collaborate with one another.
About you
Software Engineers come from a diverse set of backgrounds, sometimes with degrees in Computer Science and sometimes with extensive experience with real problems, or both. In order to set you up for success as a Software Engineer at Google DeepMind, we look for the following skills and experience:
- Experience contributing your skills in a scientific research environment.
- Dedicated software engineer with experience in software design and development, obtained either through a degree or applied experience.
- Experience with concurrent and distributed software algorithms and architectures.
In addition, one or more of the following would be strongly preferred:
- Applied experience with machine learning, preferably modern deep learning architectures (e.g. Transformers, CNNs, LSTMs).
- Experience optimising large-scale training and fine-tuning large models.
- Experience with low-level optimisation on latest accelerator hardware.
- Experience with Natural Language Processing.
- Proven experience in Python, C++, and interoperability between the two.
- Scientific knowledge (particularly chemistry, mathematics, physics, …).
Closing date: Tuesday 11th July at 5:00pm BST
