Research Engineer, Workspace

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

The Product team collaborates closely with a wide variety of teams across Google/Alphabet, leveraging Google DeepMind expertise to deploy advanced machine learning algorithms with the goal of improving Alphabet products and services. 

We are a driven, collaborative, diverse team based in London and Mountain View. Our current and past engagements include teams in Workspace, Cloud, Android, Assistant, Youtube and Maps. We collaborate closely with Google DeepMind and Google Research teams on several projects. Each project typically consists of a team of engineers working closely with our product partners and with our researchers, product managers and program managers.

About us

Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.

The role

Key Responsibilities:

You’ll be applying the most promising models and research to high-impact real world problems, by rapid-prototyping initial concepts, and designing and running experiments to evaluate the opportunity. You will gain an understanding of the path from research to production whilst working on real world problems, with the chance to see your work make a difference. You’ll be part of a small project team led by Research Engineers, with the potential for partnership with research scientists and significant impact in the short term, and close mentorship from Product Impact Unit leadership.

Some of our current projects are focusing on the areas below so experience in any of these is highly beneficial:

• Natural Language Generation/Understanding

• Multimodal Understanding

• Reinforcement Learning

• Meta Learning

• Multitask Learning

• Generative Media

About you

We seek out individuals who thrive in ambiguity and who are willing to help out with whatever moves prototypes forward. We regularly need to invent novel solutions to problems, and often change course if our ideas don’t work out, so flexibility and adaptability to work on any project is a must.

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

• BSc, MSc or PhD/DPhil degree in computer science, mathematics, applied stats, machine learning or similar experience working in industry

• Proven knowledge and experience of Python or C++

• Knowledge of machine learning and statistics 

• Knowledge of algorithm design

• Proven experience of Tensorflow or similar ML frameworks (e.g. JAX) is highly desirable

• Recent experience conducting applied research to improve the quality and training/serving efficiency of large transformer-based models

• Experience fine-tuning large models (e.g. supervised, RLHF)

• Experience applying and productionizing state-of-the-art large visual, language and multimodal research

• Software Engineering experience and experience working on large-scale ML projects highly desirable 

• Proven experience working in industry, working on projects from proof-of-concept through to implementation highly beneficial.

• A passion for Artificial Intelligence

• Great communication skills and proven interpersonal skills

In addition, the following would be an advantage:

• Experience in applying experimental ideas to applied problems

• Cross functional collaboration experience

• Prior experience collaborating with researchers

• Prior experience working with product teams