Software Engineer, Privacy Engineering Engineering London, UK

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.

Snapshot

We are looking for a Software Engineer to join the Google DeepMind Privacy Engineering team to work on private ML serving infrastructure for Google DeepMind and our product partners.

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

As part of the Privacy Engineering team at Google DeepMind, you will play a key role in creating innovative privacy-preserving technologies for GenAI-based agents!

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 including:

• Private inference using large GenAI models (e.g. Gemini)
• Private AI agent memory supporting user’s multi-modal data
• Developing privacy preserving agentic capabilities such as tool use
• New agent architectures that offer privacy-by-design in realistic deployment scenarios

We are looking for a Software Engineer to join the Google DeepMind Privacy Engineering team to work on a new private inference infrastructure for Google DeepMind and our product partners. ML experience is not required for this role and it will not involve training ML models.

Key responsibilities:

You will be contributing to an ambitious Private Inference project. This includes building infrastructure, researching new privacy preserving methods, working with partner and client teams, and most importantly, land transformative impact for GDM and our product partners.

• Invent and implement novel protocols and APIs to build private-by-design distributed systems at Google scale
• Work on low-level components to reduce the Trusted Computing Base of the system, including open source and proprietary components (in Rust, C++, Java and Kotlin)
• Understand the tradeoffs between different encryption schemes and apply them to existing and new systems
• Reason about the properties of distributed systems holistically as components are added to it (e.g. accelerators, persistent memory, etc.)
• Define threat models for existing and new systems, taking into account engineering trade-offs and product requirements
• Think adversarially about the software and hardware stack, and figure out how to mitigate potential attack vectors
• Implement workloads running on Trusted Execution Environments (TEE, a.k.a. Enclaves)
• Design and build a transparent and secured storage system for LLM servers.
• Work with product teams, gather requirements and provide 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 white papers

About You

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

• MS or PhD in computer security or related field, or equivalent practical experience in security and privacy
• Preferably related experience in GenAI and LLM infrastructure or products
• Demonstrated passion for and thought leadership within the technology space generally, and specifically within security and privacy in the ML space
• Results oriented; able to deliver innovative research ideas into production and landed impact
• Demonstrated success in creative problem solving for scalable teams and systems
• Strong back-end, infrastructure and API design skills
• Experience designing, implementing and debugging distributed systems at scale
• Solid C++ / Rust proficiency

Application deadline: 31st January at 5pm GMT

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