Snapshot
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.
About Us
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 the development and ongoing improvement of our research through the computational implementation of our latest theoretical work. Research Engineers make many different vital contributions to our engineering infrastructure and research programme.
More specifically this role will be within the Gemini's Multimodal Team to advance agentic capabilities, specializing in vision. The team works across the entire model development pipeline (pretraining, posttraining, inference).
The Role
- Digest and understand complex research papers, theory and thinking, with an ability to write algorithms from scratch. This role is pivotal in training, iterating and improving the performance of our agents.
- Own, report and present engineering developments and experimental results to both the immediate and broader research teams, status and results clearly and efficiently both internally and externally, verbally and in writing.
- Architect and implement software libraries to allow our research to improve and scale.
- 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.
- Encouraging engineering excellence through mentoring and reviewing.
About You
In order to set you up for success as a Research Engineer at Google DeepMind, we look for the following skills and experience:
- BSc/BEng degree in computer science, mathematics, physics, electrical engineering, machine learning or equivalent (MSc/MEng preferable).
- Proven experience, either in industry or a research lab, working on complex ML problems and engineering workflows.
- Strong knowledge and experience of Python and/or C++.
- Proven knowledge of machine learning and/or statistics e.g. Neural Nets, Deep Learning, Reinforcement Learning etc.
- Strong knowledge of algorithm design - with a proven ability to write ML algos from scratch.
In addition, the following would be an advantage:
- Experience with Large Language Models and notably Vision Language Models.
- Working knowledge of JAX/Pytorch or similar frameworks.
- Experience with data analysis at scale, data visualization and data ingestion pipelines for training models.
- A strong interest in Agents.
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.
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What We Do
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. Our long term aim is to solve intelligence, developing more general and capable problem-solving systems, known as artificial general intelligence (AGI). Guided by safety and ethics, this invention could help society find answers to some of the world’s most pressing and fundamental scientific challenges. We have a track record of breakthroughs in fundamental AI research, published in journals like Nature, Science, and more.Our programs have learned to diagnose eye diseases as effectively as the world’s top doctors, to save 30% of the energy used to keep data centres cool, and to predict the complex 3D shapes of proteins - which could one day transform how drugs are invented.







