Research Scientist, Autonomous Assistants
Research Scientist, Autonomous Assistants

Research Scientist, Autonomous Assistants

London Full-Time 28800 - 48000 £ / year (est.) No home office possible
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At a Glance

  • Tasks: Lead research on next-gen autonomous assistants to enhance human support in daily tasks.
  • Company: Join Google DeepMind, a leader in AI innovation focused on public benefit and scientific discovery.
  • Benefits: Enjoy a collaborative environment, cutting-edge technology, and opportunities for impactful research.
  • Why this job: Be at the forefront of AI development, shaping the future of autonomous agents with real-world applications.
  • Qualifications: PhD or equivalent experience in a technical field; research background in autonomous systems preferred.
  • Other info: Diversity and inclusion are core values; we welcome applicants from all backgrounds.

The predicted salary is between 28800 - 48000 £ per year.

Research Scientist, Autonomous Assistants

London, UK

Snapshot

We are looking for Research Scientists to join the Autonomous Assistants team, and produce research in the development of next-generation technologies to power increasingly open-ended autonomous agents which strive to assist, support, and supplement humans in their daily personal and professional lives.

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

Within the team, Research Scientists are encouraged to lead/support a research agenda aimed at producing practically applicable technological advances in the ability of increasingly autonomous agents to assist, support, and empower humans.

The expectation is that research scientists will conduct novel research according to ambitious long-term agendas, while maintaining a strong focus on methods and tools offering practical benefits in the short term as a form of pragmatic grounding. Central to this process is the idea that rapid iteration over and refinement of solutions catering to real-world use-cases provides a strong basis for better understanding the research boundary in a fast paced field.

Key responsibilities:

  • Spearhead the ideation and development of new use-cases and desired capabilities of assistant-like agents of any form, advised by the current state of research.
  • Partner with research engineers to develop ambitious prototypes pertaining to desired or anticipated assistant agent use-cases, and design and implement evaluation protocols around these prototypes.
  • Identify, motivated by empirical study of existing methods\’ failures or limitations on use-case-based evaluations, the roadblocks and research challenges, and…
  • …develop novel technical or methodological solutions to overcome such obstacles and limitations.
  • Identify sources of data, design and implement data collection processes (supported by research engineering partners), and conduct human annotation and evaluation campaigns for the production and evaluation of strong baselines for each use-case.
  • Help identify, within Google DeepMind’s broad portfolio of research projects, methods which could be adapted or tried against our evaluations, as well as teams and individuals with which the team could partner to overcome challenges whilst providing grounding and evaluation for that collaborator\’s research agenda.

About You

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

  • PhD in a technical field or equivalent practical experience.
  • Experience in a research domain connected to the production of increasingly autonomous assistants, (e.g. LLM-powered agents, RL/IL, applications in NLP, evaluation design).
  • A desire to produce the next generation of agentic systems capable of learning from and efficiently adapting to deployment in real-world scenarios.

In addition, the following would be an advantage:

  • Strong end-to-end system building and prototyping skills.
  • Experience with one or more of: fine-tuning LLMs, running human data collection/annotation campaigns, self-play, multi-agent systems.
  • Experience with open-ended learning, RL, and frontier methods for training LLMs (RLHF, RLAIF, multi-turn RL, multi-agent interactions, reward function design and modelling, etc.).
  • A curiosity about, or experience with research topics surrounding personalization, memory, reasoning, self-improvement, and safety.

Closing date: Friday, 1st August at 5:00pm BST.

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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UK Demographic Questions

Google DeepMind is committed to equal opportunity employment regardless of race, religion or belief, ethnic or national origin, disability, age, citizenship, marital status, domestic or civil partnership status, sexual orientation, gender identity or any other basis as protected by applicable law. A voluntary self-identification question enables us to monitor and evaluate the effectiveness of our equal opportunities policy within our recruitment process. Your information is used in an aggregated form for these limited purposes and will not form part of your application.

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Research Scientist, Autonomous Assistants employer: Google DeepMind

At Google DeepMind, we pride ourselves on being an exceptional employer, fostering a collaborative and innovative work culture that empowers our Research Scientists to lead groundbreaking research in autonomous technologies. Located in London, our team benefits from a vibrant tech ecosystem, ample opportunities for professional growth, and a commitment to ethical AI development, ensuring that your contributions have a meaningful impact on society. Join us to be part of a diverse team dedicated to pushing the boundaries of artificial intelligence while prioritising safety and public benefit.
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Contact Detail:

Google DeepMind Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Research Scientist, Autonomous Assistants

✨Tip Number 1

Familiarise yourself with the latest advancements in autonomous agents and AI technologies. This will not only help you understand the current landscape but also allow you to engage in meaningful conversations during interviews, showcasing your passion and knowledge.

✨Tip Number 2

Network with professionals in the field of AI and autonomous systems. Attend relevant conferences, webinars, or meetups to connect with researchers and engineers. Building these relationships can provide insights into the company culture and potentially lead to referrals.

✨Tip Number 3

Prepare to discuss your previous research experiences in detail, especially those related to autonomous assistants. Be ready to explain your methodologies, findings, and how they could apply to the role at Google DeepMind, demonstrating your ability to contribute from day one.

✨Tip Number 4

Stay updated on ethical considerations and safety protocols in AI development. Being knowledgeable about these topics will show that you are not only technically proficient but also aware of the broader implications of your work, aligning with Google DeepMind's values.

We think you need these skills to ace Research Scientist, Autonomous Assistants

PhD in a technical field or equivalent practical experience
Experience in research related to autonomous assistants
Knowledge of LLM-powered agents and reinforcement learning
Prototyping and end-to-end system building skills
Experience with fine-tuning LLMs
Ability to run human data collection and annotation campaigns
Understanding of multi-agent systems
Familiarity with open-ended learning and frontier methods for training LLMs
Curiosity about personalization, memory, reasoning, and safety
Strong analytical and problem-solving skills
Excellent communication and collaboration abilities
Experience in designing and implementing evaluation protocols
Ability to identify and overcome research challenges
Data collection process design and implementation skills

Some tips for your application 🫡

Tailor Your CV: Make sure your CV highlights relevant experience in research and development of autonomous systems. Emphasise any projects or roles that demonstrate your skills in machine learning, NLP, or system prototyping.

Craft a Strong Cover Letter: Write a cover letter that clearly outlines your motivation for applying to Google DeepMind. Discuss how your background aligns with their mission and the specific role of Research Scientist in Autonomous Assistants.

Showcase Relevant Projects: Include links to any relevant projects or publications in your application. This could be GitHub repositories, research papers, or prototypes that showcase your expertise in autonomous agents and related technologies.

Highlight Collaboration Skills: Since the role involves partnering with research engineers, emphasise your teamwork and collaboration experiences. Mention any instances where you successfully worked in interdisciplinary teams to achieve research goals.

How to prepare for a job interview at Google DeepMind

✨Showcase Your Research Experience

Be prepared to discuss your previous research projects in detail, especially those related to autonomous systems or AI. Highlight any innovative solutions you developed and how they contributed to the field.

✨Demonstrate Technical Proficiency

Familiarise yourself with the latest technologies and methodologies relevant to the role, such as LLMs, reinforcement learning, and evaluation design. Be ready to explain how you've applied these in your work.

✨Prepare for Problem-Solving Questions

Expect to face scenario-based questions that assess your problem-solving skills. Think about potential roadblocks in autonomous assistant development and how you would address them using empirical data.

✨Express Your Passion for AI

Convey your enthusiasm for advancing AI technologies and their applications in real-world scenarios. Share your vision for the future of autonomous assistants and how you see yourself contributing to that vision.

Research Scientist, Autonomous Assistants
Google DeepMind
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