Research Scientist / Engineer, Open-Ended Learning in London

Research Scientist / Engineer, Open-Ended Learning in London

London Full-Time 36000 - 60000 £ / year (est.) No working from home possible
Google DeepMind

At a Glance

  • Tasks: Join us to develop systems for open-ended learning and tackle novel challenges in AI.
  • Company: Google DeepMind is at the forefront of AI, focusing on public benefit and scientific discovery.
  • Benefits: Enjoy a collaborative environment with a commitment to safety, ethics, and diversity.
  • Other info: We value diverse perspectives and are committed to equal employment opportunities.
  • Why this job: Be part of groundbreaking research that pushes the boundaries of artificial general intelligence.
  • Qualifications: MSc or PhD in computer science/machine learning or equivalent experience required.

The predicted salary is between 36000 - 60000 £ per year.

Research Scientist / Engineer, Open-Ended Learning

London, UK

Snapshot

Join an ambitious project focused on Open-Ended Learning (OEL) , where the learning process itself generates an endless stream of novel challenges, continually pushing and expanding the capabilities of models and agents. We believe that devising systems that can kickstart and sustain such open-ended co-evolution between agents and their environments is critical to developingincreasingly general intelligence , capable of succeeding in surprising emergent scenarios and exhibiting strong out-of-distribution generalisation. We believe that combining frontier models such as large language models (LLMs) with open-ended learning approaches is on the critical path to building artificial general intelligence.

About us

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.

The Role

Key responsibilities: Implement core infrastructure and conduct research to devise learning systems that kickstart and sustain open-ended learning . Solve essential problems to generate an endless stream of problems that continually challenge and push the capabilities of participating agents. Develop metrics and scaling laws for generality and emergent intelligence, curate and synthesise diverse learning challenges, and study the mechanisms that drive self-improving, open-ended co-evolution between models/agents and their tasks/environments. Embrace the bitter lesson and seek simple methods that scale, with emphasis on strong systems and infrastructure.

Areas of focus:

  • Systems for training agents in complex, evolving, and open-ended environments.
  • Infrastructure for generating, curating, and evaluating diverse and novel learning challenges for LLMs, LLM agents, and beyond.
  • Methods for efficient, continual learning and adaptation in dynamic and unbounded settings.
  • Integrating foundation models (such as LLMs) and open-ended learning approaches (e.g. evolutionary search or quality-diversity to name a few) into open-ended learning pipelines.
  • Developing methods for never-ending learning in open-ended loops.
  • Quantitative evaluations for assessing generality, novelty, feasibility, creativity, emergence, and out-of-distribution generalisation in OEL systems.
  • Scaling law science for open-ended learning and emergent capabilities.

About you

We seek individuals who are passionate about open-ended learning and believe that continuous, self-generated challenges are crucial for developing truly general intelligence. We strive for simple methods that scale and look for candidates excited to improve models through robust infrastructure, innovative data generation, rigorous evaluations, and efficient compute.

In order to set you up for success as a Research Scientist or Research Engineer at Google DeepMind, we look for the following skills and experience:

  • MSc or PhD in computer science or machine learning, or equivalent industry experience.
  • Experience with prompting, evaluating, and fine-tuning LLMs, building LLM agents, and/or designing and implementing open-ended learning approaches .
  • Track record of releases, publications, and/or open source projects relating to open-ended learning, LLMs, or LLM agents.
  • Strong systems and engineering skills in deep learning frameworks like JAX or PyTorch.

In addition, the following would be an advantage:

  • Experience building training codebases for LLMs, LLM/RL agents, open-ended methods in complex, evolving environments.
  • Expertise optimising efficiency of distributed training systems and/or inference systems for long-running learning processes.


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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Research Scientist / Engineer, Open-Ended Learning in London employer: Google DeepMind

At Google DeepMind, we are dedicated to pushing the boundaries of artificial intelligence through innovative research and collaboration. Our London-based team fosters a dynamic work culture that prioritises diversity, creativity, and continuous learning, offering employees unparalleled opportunities for professional growth and impactful contributions to society. Join us in our mission to develop open-ended learning systems that not only advance technology but also ensure ethical practices and public benefit.

Google DeepMind

Contact Details:

Google DeepMind Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Research Scientist / Engineer, Open-Ended Learning 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 / Engineer, Open-Ended Learning in London

MSc or PhD in Computer Science or Machine Learning
Experience with Large Language Models (LLMs)
Prompting, Evaluating, and Fine-tuning LLMs
Building LLM Agents
Designing Open-Ended Learning Approaches
Strong Systems and Engineering Skills
Deep Learning Frameworks (e.g., JAX, PyTorch)

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.