We're looking for engineers to push forward fundamental research and technology in Artificial Intelligence, as part of our interdisciplinary and collaborative Foundational Research team.

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.

Our Foundational Research team in Zurich, Switzerland, is pioneering the future of AI. A key initiative is our Universal Knowledge project, focused on enabling LLMs to deeply reason and accurately answer questions about specific document collections. This involves cutting-edge research into enhancing LLM reasoning capabilities and exploring the vital interface between natural language and structured data or formal languages. We're developing advanced techniques for extracting semi-structured knowledge, building intelligent systems that can truly understand and leverage domain-specific information to unlock new levels of AI understanding.

As a Research Engineer, you'll use your technical skills and machine learning knowledge in research projects, engineering initiatives, and applications of research.

Your work may involve:

• Working out how to make research methods run with large scale computers.

• Performance engineering, benchmarking, and optimisation.

• Solving key research challenges, via designing and running experiments, sharing analyses and proposing next steps.

• Bringing engineering expertise into research projects. Sharing your skills and knowledge with other engineers and researchers.

• Designing, building, and improving infrastructure for research.

We take a holistic view of people's backgrounds, and do not expect you to be an expert in all areas. We invest a lot of time in training and helping people to continually learn as part of their role.

The core skills we look for in Research Engineers are:

• Degree in computer science, electrical engineering, science, mathematics or equivalent experience.

• Programming experience, particularly with Python-based scientific libraries such as JAX, PyTorch, TensorFlow, NumPy. 

• Familiarity with machine learning, mathematics and statistics needed to follow relevant research papers (linear algebra, calculus, etc).

• Experience deploying and maintaining machine learning models in a production environment is required. 

• Strong interest in applying machine learning research to real-world problems is essential.

In addition, the following would be an advantage: 

• Large-scale system design, distributed systems.

• Experience with knowledge bases, knowledge representation, natural language processing.

• Experience with training, fine-tuning, post-training of LLMs.

• Strong communication skills (via discussion, presentation, technical and research writing, whiteboarding).

• Academic research experience in machine learning, publications, or research experience in related fields.

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 opportunities 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.

Application deadline: 12pm GMT Thursday 31st August 2025 

Note: In the event your application is successful and an offer of employment is made to you, any offer of employment will be conditional on the results of a background check, performed by a third party acting on our behalf. For more information on how we handle your data, please see our Applicant and Candidate Privacy Policy.