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.
- 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.
- Other info: We value diverse perspectives and are committed to equal employment opportunities.
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.
Create a Job Alert
Interested in building your career at DeepMind? Get future opportunities sent straight to your email.
Apply for this job
*
indicates a required field
First Name *
Last Name *
Email *
Phone
Resume/CV *
Enter manually
Accepted file types: pdf, doc, docx, txt, rtf
Enter manually
Accepted file types: pdf, doc, docx, txt, rtf
LinkedIn Profile
Link to external profile e.g. LinkedIn, GitHub etc.
#J-18808-Ljbffr
Research Scientist / Engineer, Open-Ended Learning employer: Google DeepMind
Contact Detail:
Google DeepMind Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Scientist / Engineer, Open-Ended Learning
✨Tip Number 1
Familiarise yourself with the latest advancements in open-ended learning and large language models. This will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Showcase your hands-on experience with deep learning frameworks like JAX or PyTorch. Be prepared to discuss specific projects where you've implemented these technologies, as practical knowledge is highly valued.
✨Tip Number 3
Connect with current employees or alumni from Google DeepMind on platforms like LinkedIn. They can provide insights into the company culture and expectations, which can be invaluable for tailoring your approach.
✨Tip Number 4
Stay updated on the latest research papers related to open-ended learning and LLMs. Being able to discuss recent findings or methodologies can set you apart as a knowledgeable candidate during interviews.
We think you need these skills to ace Research Scientist / Engineer, Open-Ended Learning
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in open-ended learning, LLMs, and deep learning frameworks like JAX or PyTorch. Use specific examples to demonstrate your skills and achievements in these areas.
Craft a Compelling Cover Letter: Write a cover letter that reflects your passion for open-ended learning and how it aligns with the goals of Google DeepMind. Mention any relevant projects or publications that showcase your expertise and enthusiasm for the role.
Showcase Your Projects: If you have worked on open-source projects or have publications related to LLMs or open-ended learning, include links to these in your application. This will provide concrete evidence of your capabilities and commitment to the field.
Highlight Collaborative Experience: Emphasise any experience you have working in teams or collaborative environments, especially in research settings. Google DeepMind values teamwork, so showcasing your ability to work well with others can strengthen your application.
How to prepare for a job interview at Google DeepMind
✨Show Your Passion for Open-Ended Learning
Make sure to express your enthusiasm for open-ended learning during the interview. Share specific examples of how you've engaged with this concept in your previous work or studies, and discuss why you believe it's crucial for developing general intelligence.
✨Demonstrate Technical Expertise
Be prepared to discuss your experience with deep learning frameworks like JAX or PyTorch. Highlight any projects where you've implemented LLMs or open-ended learning approaches, and be ready to explain the challenges you faced and how you overcame them.
✨Prepare for Problem-Solving Questions
Expect to tackle problem-solving scenarios related to generating and curating learning challenges. Practice articulating your thought process clearly, as this will showcase your analytical skills and ability to think on your feet.
✨Highlight Collaboration and Communication Skills
Since the role involves working with a diverse team, emphasise your ability to collaborate effectively. Share examples of how you've worked with others in past projects, focusing on how you communicated complex ideas and contributed to team success.