Build AI responsibly to benefit humanity

Research Engineers are software engineers with a deep understanding of machine learning and deep learning, bringing a combination of engineering, mathematical, and research skills to advance GDM’s mission. They are experimentalists, acting as critical bridge between theory and implementation – designing, building, and scaling complex systems to test and evaluate new ideas. That often leads to co-authorship on leading research papers.

Key responsibilities include implementing and optimizing frontier models. Building robust infrastructure for distributed computing. And applying expertise across specialized domains, like Gemini or robotics.

Researchers focus on what AI can do. Software engineers make it happen, by scoping, developing, maintaining, and upgrading our software. Their passion for machine learning helps them turn technical solutions into engineering challenges. They define software roadmaps and architecture – and solve long-term problems from end to end.

Software engineers understand the research environment and use it to inform engineering focus.Key responsibilities include developing reliable and efficient software, built for scale. And sharing deep software engineering expertise across the business.

Product Managers set out roadmaps for our AI products, and drive them from concept to implementation – in Google and Google DeepMind applications. They support cross-functional teams of researchers and engineers to launch AI models and platforms that meet user needs. And they translate complex AI technical capabilities into actionable product specifications.

Key responsibilities include planning and guiding product development through to deployment, alongside balancing business success with societal responsibilities.

Our large-scale, strategic, cross-functional initiatives rely on Program Managers. This group is responsible for end-to-end program design, managing complex dependencies and handling risks. They also make sure we maintain operational excellence, while meeting (or exceeding) our strategic goals.

Key responsibilities include translating strategic ambitions into clear objectives and actionable plans. While aligning stakeholders and communication across the organization.

Technical Program Managers are embedded within specific research and engineering units. They use deep technical understanding to manage programs’ entire lifecycles – from early research to production launch and beyond. That means co-developing program strategies, influencing key engineering decisions, and accelerating breakthroughs.

Key responsibilities include performing technical due-diligence. Evaluating complex and technical proposals. And translating complex concepts for diverse audiences across the organization.

Research Scientists are creative and collaborative, bringing scientific expertise to advance GDM’s mission. They hold deep theoretical knowledge and an interdisciplinary mindset. Think of them the engine of innovation as we work towards our mission to “solve intelligence”.

Driven to push the boundaries of AI, they formulate novel hypotheses and algorithmic paradigms that spark world-changing breakthroughs. They normally hold a PhD, may plan and execute both large- and small-scale research projects, and frequently contribute to foundational research papers.

Key responsibilities include identifying core research questions, designing and evaluating novel models, and pioneering new approaches in specialized domains like Gemini.

Our Operations team are multi-disciplinary experts, with a focus on creating and maintaining world-class spaces, infrastructure, and systems – so that our groundbreaking research, programs, and product development can happen.

Key responsibilities include leading our internal and external engagement strategies, hiring the world’s brightest minds, and fostering a collaborative culture.

Our Responsibility team makes sure we build AI models boldly – yet thoughtfully. They partner with internal teams, and the wider AI community, to embed ethics into our work and rigorously test our systems. They also address the societal impacts of our technology to guide our path forward.

The team consists of experts from areas including CBRN, assurance evaluations, and AI governance. Key responsibilities span policy, research, and engineering – giving us insight from many angles, to help us remain responsible.

A 30-minute introductory call with your Recruiter, to cover your background and experiences. They’ll tell you more about the role, and learn more about why you applied. You’ll have the chance to ask questions, then the Recruiter will outline the next stages of the process.

At this stage, we may also ask you to join an interview with the hiring manager for the role. They’ll ask more questions about specific capabilities, and help you build a better understanding of what their team does.

Over two or three further calls, we’ll evaluate you against the competencies and skills required for success in the position. We’ll make sure you have a good understanding of what to expect and how to prepare.

You’ll meet potential peers during these conversations, and be able to ask more questions about working life at Google DeepMind.

During the final round, you’ll meet Team Leads and leadership – including your potential manager. We’ll still focus on core skills, but through the lens of team goals, future plans, and our culture, mission, and values.

Think of it as a mutual assessment. We’ll give you plenty of time to ask questions, so you can be confident we’re the right fit for you.

The hiring team will review your application against our criteria. If you’re the best candidate for the role, your Recruiter will share the exciting news and talk you through our competitive compensation and benefits package.

They’ll then formally invite you to join Google DeepMind.