At a Glance
- Tasks: Create innovative multi-agent learning algorithms and maintain large-scale research platforms.
- 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: Dynamic environment with a focus on safety, ethics, and collective achievement.
- Why this job: Make a real impact in AI development while collaborating with top researchers globally.
- Qualifications: Bachelor's degree in Computer Science or related field; experience in Python/C++ and deep learning frameworks.
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.
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
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 extensive learning opportunities and career growth pathways. With a commitment to ethical practices and public benefit, our teams thrive in a dynamic environment that values creativity and the pursuit of excellence.
StudySmarter Expert Advice🤫
We think this is how you could land Research Engineer, Multi Agent Learning, DeepMind in London
✨Join Local Tech Meetups
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✨Contribute to Open Source Projects
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We think you need these skills to ace Research Engineer, Multi Agent Learning, DeepMind in London
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Google.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Google and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Google
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Google uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
