At a Glance
- Tasks: Lead research on post-training large language models and design scalable experiments.
- Company: Join Google DeepMind, a leader in AI research and innovation.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on innovation and research excellence.
- Why this job: Make a real impact in AI by working on cutting-edge technology and agentic tasks.
- Qualifications: Experience in research or engineering with a focus on AI and machine learning.
The predicted salary is between 60000 - 80000 £ per year.
Google Deep Mind is seeking a Research Scientist or Research Engineer to lead the full research process for post‑training large language models, focusing on agentic tasks.
You will design scalable experiments and build reliable infrastructure for tool use and reinforcement learning.
You will collaborate with researchers and engineers to deliver direct impact, from hypotheses to ablations and reports, while balancing research velocity with code quality in a large‑scale AI research environment.
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Research Scientist: Post-Training Agentic LLMs in London employer: Google DeepMind
At Google DeepMind, we pride ourselves on being an exceptional employer that fosters innovation and collaboration in the heart of London. Our vibrant work culture encourages creativity and offers ample opportunities for professional growth, while our commitment to ethical AI ensures that your contributions will have a meaningful impact on society. Join us to be part of a team that values diversity and empowers you to excel in your career.
StudySmarter Expert Advice🤫
We think this is how you could land Research Scientist: Post-Training Agentic LLMs in London
✨Get Involved in Research Communities
Dive headfirst into the scientific research world by joining relevant communities and forums. Engage in discussions, share your insights, and even attend conferences or seminars in your field. This not only boosts your visibility but can also lead to potential job opportunities—don't forget to connect with like-minded folks!
✨Show Off Your Research Projects
Have you worked on any cool research projects? Make it easy for potential employers to see your work by creating a portfolio or a personal website. This way, when you apply for roles like the one at Google DeepMind, you can point them to your projects and publications, showcasing your expertise directly.
✨Utilise Professional Networks
Networking is key in scientific research. Join professional bodies or organisations related to your field. They often have job boards and resources tailored for job seekers. Make connections with professionals who may know about openings or can give you tips on landing a full-time position.
✨Keep Your Eyes on Openings & Apply Directly
Don’t just rely on job boards! Keep an eye on the careers section of the websites of companies like Google DeepMind. Apply directly through their website because sometimes they post jobs there before anywhere else. Plus, it shows your proactive approach!
We think you need these skills to ace Research Scientist: Post-Training Agentic LLMs in London
Some tips for your application 🫡
Highlight Your Research Experience:When applying for a full-time role in scientific research, make sure to emphasise your research experience prominently in your CV. Share specific projects you’ve worked on, the methodologies you used, and any significant findings. If you’ve published papers or presented at conferences, definitely include that too – it shows you’re on it in the academic world!
Tailor Your Cover Letter to the Research Area:Your cover letter should reflect your passion for the specific area of research at Google DeepMind. Mention relevant experiences that align with the organisation’s goals or projects. This shows that you’ve done your homework and are genuinely interested in the position – plus, it helps us see how you’d fit into the team dynamics.
Showcase Your Data Analysis Skills:In scientific research, data analysis skills are a big deal! Make sure to detail any relevant analytical tools or software you’re familiar with, like R, Python, or statistical packages. Employers are keen to know you can handle the data-heavy elements of the role, so add specific examples where you’ve used these skills effectively.
Discuss Your Future Research Goals:In your motivation section, it’s a great idea to talk about your future research goals and how they align with the work being done at Google DeepMind. This shows that you’re not just looking for any job, but rather a chance to contribute meaningfully to the field. We love to see applicants who are forward-thinking and enthusiastic about their research journey!
How to prepare for a job interview at Google DeepMind
✨Showcase Your Research Skills
In scientific research, it’s crucial to demonstrate your ability to design and conduct experiments. Come armed with examples of past projects where you've developed hypotheses, collected data, and analysed results. Be ready to discuss any specific methodologies or tools you’ve used, like PCR techniques or statistical software.
✨Prepare for Technical Questions
Expect some technical questions specific to your field. Make sure you're up to speed with recent advancements in scientific research related to the role at Google DeepMind. Brush up on concepts relevant to their projects and be prepared to discuss how you would approach a specific research problem or challenge they might face.
✨Know Your Publications
If you've authored or co-authored any papers, be prepared to discuss them! Highlighting your contributions to published research can really set you apart. It shows not only your expertise but also your ability to communicate complex ideas clearly, which is key in scientific research roles.
✨Exhibit Your Team Spirit
In full-time roles, collaboration is often at the heart of scientific research. Prepare examples that show how you've successfully worked in teams, dealt with conflicts, or contributed to group projects. We want to know how you can work effectively with the team at Google DeepMind to drive research projects forward.
