Snapshot Science is at the heart of everything we do at Google DeepMind. From the beginning, we took inspiration from science to build better algorithms, and now, we want to use our toolkit to accelerate scientific discovery. By bringing together specialists with backgrounds in machine learning, computer science, physics, chemistry, biology and more, were optimistic that we can build new methods that will push the boundaries of what is possible and help solve the biggest problems facing humanity. Project Overview Google DeepMind (GDM) is pursuing a ground-breaking research program in materials, aiming to accelerate the discovery of new functional materials by combining the predictive power of artificial intelligence (AI) and computational simulation with automated experimentation. Youll join an interdisciplinary team of domain experts, ML researchers and engineers exploring a diverse set of important scientific problems in materials science, physics, quantum chemistry and other areas. Our work is organised into several longer-term focus areas, which aim to achieve step changes to the state-of-the-art. The role To succeed in this role you will need to be passionate about using computation to advance science. As an embedded Software Engineer you will collaborate with other researchers and engineers to develop infrastructure for running experiments and help researchers explore new applications of AI and LLMs to materials science. The team is pioneering in many different domains so you may take part in exploratory work that enables validating early ideas, or work in a maturing area to deepen and build infrastructure to exploit a promising line of research. You may also contribute to the scientific knowledge and experience of the team with your own scientific domain knowledge. Key responsibilities: 37 Use your domain knowledge in the sciences (if applicable) to design, develop and implement high-performance simulations, tools, and analysis workflows. 37 Apply your software engineering expertise to produce high quality, reusable code and components to tackle meaningful strategic problems. 37 Share ideas with other specialists in the team and be highly collaborative, striving to cultivate a culture of continuous development and advancement. 37 Employ cutting-edge technology and techniques to contribute to solving some of the hardest problems. 37 Incorporate your passion for software engineering and high performance computing to enable running scientific calculations at scale and accelerate scientific discovery. About you Software Engineers come from a diverse set of backgrounds, sometimes with degrees in Computer Science and sometimes with extensive experience with real problems, or both. In order to set you up for success as a Software Engineer at Google DeepMind, we look for the following skills and experience: 37 Dedicated software engineer with experience in software design and development, obtained either through a degree or applied experience. 37 Proven experience in Python, C++, and interoperability between the two. 37 Experience with concurrent and distributed software algorithms and architectures. 37 Experience applying software engineering principles in a scientific research environment. In addition, one or more of the following would be strongly preferred: 37 Scientific knowledge (particularly materials science, chemistry, or physics). 37 Experience with high-performance computing (HPC) and running high-throughput scientific simulations at scale. 37 Applied experience with scientific simulations (e.g. molecular dynamics, computational chemistry simulations, etc.) 37 Applied experience with modern deep learning architectures (e.g., transformers, diffusion models). The US base salary range for this full-time position is between $141,000 - $202,000 + bonus + equity + benefits. Your recruiter can share more about the specific salary range for your targeted location during the hiring process. Application deadline: November 14, 2025