Research Engineer, Data-efficient and Bayesian Learning

DeepMind welcomes applications from all sections of society. 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.

About us

The Data-Efficient and Bayesian Learning (DEBL) team engages in foundational research across a broad range of areas including deep learning, Bayesian and probabilistic learning, causal inference, fairness and data efficient learning. We are driven by research that discovers and illuminates the fundamental principles underlying learning and intelligence, and that leads to developments of basic building blocks and design principles in DeepMind’s technological stack. The road to AGI is long, and our aim is to ensure that each step taken rests on solid ground..

We have a hardworking and inclusive culture, driven by curiosity-led research and collaborations across DeepMind on both basic and applied research questions.

Snapshot

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 year!

The role

Research Engineers in DEBL work on a diverse range of projects including: developing and optimising learning algorithms and models, providing software design and programming support to research projects, crafting and implementing software libraries, and enabling large scale experimentation on research projects. The RE role also involves providing engineering advice and support to the team.

Key responsibilities:

• Provide software design and programming support to research projects
• Design and implement software libraries
• Implement, optimise, and evaluate algorithms and models
• Report and present software developments including status and results clearly and thoughtfully both internally and externally, verbally and in writing
• Support large scale research experiments, presenting results clearly and thoughtfully both internally and externally, verbally and in writing

About you

Essential

• Technical degree (e.g., BSc, BEng, MSc, MEng) in computer science, mathematics, physics, electrical engineering, machine learning or equivalent experience
• Experience (commercial, academic, or as a hobbyist) with using machine learning
• Extensive knowledge of and experience with programming in Python
• Experience working with JAX, Tensorflow, or PyTorch
• Experience and interest in probabilistic, Bayesian and/or Deep learning.

Nice to have

• Experience with multi-threaded design and parallel/distributed computing
• Experience with implementing numerical methods and data visualisation
• Contributions to open source projects

Competitive salary applies.

Applications close on Wednesday 17th August.