Research Engineer, Agentic Privacy (London)
Research Engineer, Agentic Privacy (London)

Research Engineer, Agentic Privacy (London)

London Full-Time 43200 - 72000 ÂŁ / year (est.) No home office possible
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At a Glance

  • Tasks: Join us as a Research Engineer to innovate in AI privacy and security.
  • Company: Google DeepMind is a leading AI research lab focused on solving intelligence for public benefit.
  • Benefits: Enjoy a collaborative environment, flexible work options, and opportunities for personal growth.
  • Why this job: Make a real impact in AI while working with top experts in a supportive community.
  • Qualifications: Bachelor's in computer science or related field; strong programming and machine learning skills required.
  • Other info: Diversity and inclusion are core values; we welcome applicants from all backgrounds.

The predicted salary is between 43200 - 72000 ÂŁ per year.

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.

We’re a dedicated scientific community, committed to “solving intelligence” and ensuring our technology is used for widespread public benefit. We’ve built a supportive and inclusive environment where collaboration is encouraged and learning is shared freely. We don’t set limits based on what others think is possible or impossible. We drive ourselves and inspire each other to push boundaries and achieve ambitious goals.

As a Research Engineer in Strategic Initiatives, you will use your machine learning expertise to collaborate with domain experts and other machine learning scientists within our strategic initiatives programs. Your primary focus will be on building technologies to make GenAI-based agents more secure and private. GenAI agents are increasingly used to handle sensitive data on behalf of users. For them to operate in a secure, trustworthy, and reliable manner, there are many unsolved, impactful problems we are working on and expect you to contribute to. This includes building infrastructure, researching new privacy preserving methods, building prototypes and demos, working with partner and client teams, and most importantly, land transformative impact for GDM and our product partners.

Key responsibilities:

  • Invent and implement novel recipes for generating and running agentic privacy benchmarks at Google scale and adapt evaluation methodology to a diverse set of agentic pipelines.
  • Work on agent orchestration prototypes combining multiple AI components to reliably solve complex tasks in nuanced scenarios.
  • Elucidate spaces of trade-offs between performance factors (utility, privacy, latency) and investigate novel ideas to push the Pareto frontier of these trade-offs.
  • Integrate novel agentic technologies (e.g. memory usage and personalization) into research prototypes.
  • Work with product teams to gather research requirements and consult on the deployment of research-based solutions to help deliver value incrementally.
  • Amplify the impact by generalizing solutions into reusable libraries and frameworks for privacy preserving AI agents across Google, and by sharing knowledge through design docs, open source, external blog posts and publications.

About You

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

  • Bachelor in computer science, security or related field, or equivalent practical experience.
  • Passion for accelerating the development of private machine learning using innovative technologies.
  • Strong programming experience.
  • Demonstrated record of python implementations of machine learning pipelines.
  • Quantitative skills in maths and statistics.
  • Experience with common scripting languages and pipelining tools.

In addition, the following would be an advantage:

  • Experience in applying machine learning techniques to problems surrounding scalable, robust and trustworthy deployments of models.
  • Experience with GenAI language models, formal methods, and/or private storage solutions.
  • Demonstrated success in creative problem solving for scalable teams and systems.
  • A real passion for AI!

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.

Research Engineer, Agentic Privacy (London) employer: Google DeepMind

At Google DeepMind, we pride ourselves on being an exceptional employer, fostering a collaborative and inclusive work culture that encourages innovation and continuous learning. Located in London, our team of passionate professionals is dedicated to advancing artificial intelligence for the public good, offering unique opportunities for personal and professional growth while tackling some of the most pressing challenges in technology today. With a strong commitment to diversity and equal opportunity, we ensure that every employee can thrive and contribute meaningfully to transformative projects.
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Contact Detail:

Google DeepMind Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Research Engineer, Agentic Privacy (London)

✨Tip Number 1

Familiarise yourself with the latest advancements in GenAI and privacy-preserving technologies. Being well-versed in current trends will not only help you during interviews but also demonstrate your genuine interest in the field.

✨Tip Number 2

Engage with the AI community by attending relevant conferences, webinars, or meetups. Networking with professionals in the industry can provide valuable insights and potentially lead to referrals for the position.

✨Tip Number 3

Showcase your programming skills by contributing to open-source projects related to machine learning or privacy. This hands-on experience can set you apart from other candidates and highlight your practical abilities.

✨Tip Number 4

Prepare to discuss specific examples of how you've tackled complex problems in previous roles. Highlighting your creative problem-solving skills will resonate well with the team at Google DeepMind, who value innovative thinking.

We think you need these skills to ace Research Engineer, Agentic Privacy (London)

Machine Learning Expertise
Strong Programming Skills
Python Implementation of Machine Learning Pipelines
Quantitative Skills in Maths and Statistics
Experience with Scripting Languages
Pipelining Tools Proficiency
Creative Problem Solving
Knowledge of GenAI Language Models
Understanding of Privacy Preserving Methods
Experience with Agent Orchestration Prototypes
Ability to Work with Cross-Functional Teams
Research Methodology Adaptation
Infrastructure Development for AI Technologies
Communication Skills for Knowledge Sharing

Some tips for your application 🫡

Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, programming, and any specific projects related to privacy and security. Use keywords from the job description to align your skills with what Google DeepMind is looking for.

Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for AI and your understanding of the role. Discuss how your background in computer science or related fields makes you a suitable candidate, and mention any specific experiences that relate to agentic privacy.

Showcase Your Projects: If you have worked on relevant projects, especially those involving GenAI or privacy-preserving technologies, include them in your application. Provide links to your GitHub or any publications that demonstrate your expertise and creativity in problem-solving.

Highlight Collaborative Experience: Since the role involves working with domain experts and product teams, emphasise any past experiences where you successfully collaborated with others. This could be through team projects, research initiatives, or any cross-functional work that demonstrates your ability to communicate and work effectively with diverse groups.

How to prepare for a job interview at Google DeepMind

✨Show Your Passion for AI

Make sure to express your genuine enthusiasm for artificial intelligence during the interview. Discuss any personal projects or research you've done in the field, as this will demonstrate your commitment and passion for advancing technology.

✨Highlight Your Technical Skills

Be prepared to discuss your programming experience, particularly with Python and machine learning pipelines. Bring examples of your work that showcase your quantitative skills in maths and statistics, as well as any relevant projects involving GenAI language models.

✨Prepare for Problem-Solving Questions

Expect to face questions that assess your creative problem-solving abilities. Think of specific scenarios where you successfully tackled complex challenges, especially those related to privacy and security in machine learning. Use the STAR method (Situation, Task, Action, Result) to structure your responses.

✨Understand the Company Culture

Research Google DeepMind's values and mission, particularly their focus on collaboration and ethical AI. Be ready to discuss how your own values align with theirs and how you can contribute to their supportive and inclusive environment.

Research Engineer, Agentic Privacy (London)
Google DeepMind
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  • Research Engineer, Agentic Privacy (London)

    London
    Full-Time
    43200 - 72000 ÂŁ / year (est.)

    Application deadline: 2027-06-05

  • G

    Google DeepMind

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