Research Engineer, Materials Science

deepmind· Science
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📍 Mountain View, California, US

About this role

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.

 

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, we’re 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.

You'll 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 (as exemplified in e.g. DM21 and GNoME).

 

The role

 

To succeed in this role you will need to be passionate about advancing material science using machine learning and other computational techniques.

As an embedded Research 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 will take part in exploratory work that enables validating early ideas, and work in a maturing area to deepen and build infrastructure to exploit a promising line of research. You will also contribute to the scientific knowledge and experience of the team with your own scientific domain knowledge.

Key responsibilities:

  • Plan and perform rapid prototyping of machine learning techniques applied to problems in science.
  • Undertake exploratory analysis to inform experimentation and research directions.
  • Make improvements to model architectures and training procedures of machine learning models.
  • Implement tools, libraries and frameworks to speed up and enable new research.
  • Report and present software developments, experimental results and data analysis clearly and efficiently.
  • Collaborate with internal and external scientific domain experts.

About you

 

 

Research 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 Research Engineer at Google DeepMind, we look for the following skills and experience:

  • Degree in computer science, electrical engineering, science, mathematics or equivalent experience.
  • Experience applying software engineering principles in a scientific research environment.
  • Knowledge of linear algebra, calculus and statistics equivalent to at least first-year university coursework.
  • Experience exploring, analysing, and visualising large and noisy datasets.
  • Experience using Jax, PyTorch, TensorFlow, NumPy, Pandas or similar ML/scientific libraries.

In addition, we also look for at least one of the following:

  • Specific domain expertise in areas like inorganic chemistry, solid-state physics, or materials synthesis.
  • Experience applying modern deep learning architectures (e.g., transformers, diffusion models) to chemistry or material science challenges (e.g. ML force fields).
  • Experience running large-scale scientific simulations (e.g. molecular dynamics, computational chemistry simulations, etc.) on Cloud or HPC clusters.
  • Experience developing custom LLM agents or tool-using systems.
  • Experience with concurrent and distributed software algorithms and architectures.
  • Masters or PhD in computer science, electrical engineering, science, mathematics or equivalent experience.
   

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.

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

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.

Frequently Asked Questions

Is the salary disclosed for the Research Engineer, Materials Science position at deepmind?
The salary for this Research Engineer, Materials Science role at deepmind is not publicly listed. Click "Apply Now" to learn more about the compensation package on their official careers page.
Where is the Research Engineer, Materials Science position at deepmind located?
This Research Engineer, Materials Science role at deepmind is based in Mountain View, California, US. The position is listed as on-site or hybrid. Check the full job description or apply directly to confirm the work arrangement.
Which team or department does the Research Engineer, Materials Science at deepmind belong to?
This Research Engineer, Materials Science position is part of the Science department at deepmind. See the full job description for more information about the team structure and responsibilities.
How do I apply for the Research Engineer, Materials Science position at deepmind?
Click the "Apply Now" button on this page. You will be redirected to deepmind's official application portal hosted on greenhouse where you can submit your application directly.
When was the Research Engineer, Materials Science job at deepmind posted?
This Research Engineer, Materials Science position at deepmind was posted on Oct 31, 2025. Apply as soon as possible — early applications are often reviewed first.
Research Engineer, Materials Science
deepmind
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