At a Glance
- Tasks: Create innovative multi-agent learning algorithms and optimise research workflows.
- Company: Join Google DeepMind, a pioneering AI lab focused on transformative technology.
- Benefits: Competitive salary, diverse career pathways, and opportunities for professional growth.
- Other info: Work in a dynamic environment with a commitment to safety and ethics.
- Why this job: Make a real impact in AI development while collaborating with top researchers.
- Qualifications: Bachelor's degree in Computer Science and 5 years of software development experience required.
The predicted salary is between 70000 - 90000 £ per year.
Minimum qualifications
- Bachelor’s degree in Computer Science or a related technical field, or equivalent practical experience.
- 5 years of experience in software development using Python or C++.
- Experience in deep learning frameworks, such as JAX or PyTorch.
- Experience in standard analysis and scientific computing libraries such as numpy, pandas, and matplotlib.
Preferred qualifications
- PhD with a research focus on Machine Learning, Reinforcement Learning, or Multi-Agent Systems.
- Experience training large-scale models on accelerators (TPUs, GPUs) in a distributed environment.
- Experience working with language models such as designing agentic harnesses, memory retrieval, or fine-tuning.
- A track record of leading complex software projects and a passion for enabling groundbreaking research through engineering.
- Deep expertise building and optimizing complex systems in JAX.
- A strong background in multi-agent reinforcement learning, algorithmic game theory, or computational economics.
About The Job
At Google, research-focused Software Engineers are embedded throughout the company, allowing them to setup large-scale tests and deploy promising ideas quickly and broadly. Ideas may come from internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world. From creating experiments and prototyping implementations to designing new architectures, engineers work on real-world problems including artificial intelligence, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more. But you stay connected to your research roots as an active contributor to the wider research community by partnering with universities and publishing papers. Artificial intelligence will be one of humanity’s most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority. We are pushing the boundaries across multiple domains. Our global teams offer learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.
Responsibilities
- Contribute to the creation of novel multi-agent learning algorithms and frameworks, with a focus on performance and scalability in Just-In-Time (JIT) compilation, Autograd, and XLA (JAX).
- Build and maintain large-scale simulation platforms and end-to-end research pipelines to run experiments on Google DeepMind’s cutting-edge infrastructure, including massive TPU pods.
- Partner deeply with Research Scientists to transform mathematical concepts and research hypotheses into robust, production-quality code and reproducible experiments.
- Lead the engineering direction for complex research projects, establish best practices for code quality and maintainability, and mentor junior engineers on the team.
- Optimize every part of the research workflow, from data processing and model training to results analysis, to accelerate the pace of discovery.
Research Engineer, Multi Agent Learning, DeepMind in London employer: Google DeepMind
At Google DeepMind, we pride ourselves on being an exceptional employer that fosters a culture of innovation and collaboration. Our research engineers are empowered to work on groundbreaking AI projects while enjoying access to state-of-the-art resources and a supportive environment that prioritises professional growth and ethical practices. With opportunities to partner with leading universities and contribute to the wider research community, our team members are at the forefront of technological advancement, making a meaningful impact on global challenges.
StudySmarter Expert Advice🤫
We think this is how you could land Research Engineer, Multi Agent Learning, DeepMind in London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Google DeepMind!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Research Engineer, Multi Agent Learning, DeepMind at Google DeepMind.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Google DeepMind.
✨Apply Directly through Our Website
When you find a suitable opening like Research Engineer, Multi Agent Learning, DeepMind at Google DeepMind, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Research Engineer, Multi Agent Learning, DeepMind in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Google DeepMind, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Google DeepMind. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Google DeepMind
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Google DeepMind!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
