Material Science Research Engineer, DeepMind

Google LLC

Mountain View, CA

JOB DETAILS
SKILLS
Algorithms, Analysis Skills, Architectural Design, Artificial Intelligence (AI), Calculus, Chemistry, Cloud Computing, Computational Chemistry, Computer Science, Consulting, Consumer Packaged Goods, Customer Service Management, Data Analysis, Data Mining, Data Sets, Deep Learning, Electrical Engineering, Embedded Software, English Language, Equal Employment Opportunity (EEO), Facilities Management, Field Sales, Financial Services, Genetics, Inorganic Chemistry, JAX (Java API for XML), Japanese Language, Korean Language, Linear Algebra, Machine Learning, Manufacturing, Material Science, Materials Engineering, Mathematics, Natural Language Processing (NLP), Network Operations Center, Operations Management, Performance Analysis, Performance Management, Physics, Product Support, Project/Program Management, Prototyping, Publications, Quality Engineering, Rapid Prototyping, Recruiting/Staffing Agency, Regulatory Requirements, Sales, Sales Management, Scientific Principles, Scientific Research, Software Architecture, Software Engineering, Statistics, Stock Purchase Plans, Structural Engineering, Technical Leadership, Testing
LOCATION
Mountain View, CA
POSTED
3 days ago

Material Science Research Engineer, DeepMind - Google Careers

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Material Science Research Engineer, DeepMind

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Minimum qualifications:

  • Bachelor"s degree in Computer Science, Electrical Engineering, Mathematics, Statistics, a related technical field, or equivalent practical experience.
  • 2 years of experience applying software engineering principles in a scientific research environment.
  • Experience working with linear algebra, calculus and statistics.
  • Experience performing data exploration or data analysis across datasets.
  • Experience with JAX, PyTorch, or TensorFlow.

Preferred qualifications:

  • Master's degree or PhD in Computer Science, Electrical Engineering, Science, Mathematics, or equivalent practical experience.
  • 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 materials science issues (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.

About the job

At Google, research-focused Software Engineers are embedded throughout the company, allowing them to setup large-scale tests and deploy promising ideas quickly and broadly. Ideas may come from internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.

From creating experiments and prototyping implementations to designing new architectures, engineers work on real-world problems including artificial intelligence, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more. But you stay connected to your research roots as an active contributor to the wider research community by partnering with universities and publishing papers.

Artificial intelligence will be one of humanity's most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.

We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $147000 - $211000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

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.

Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google"s Applicant and Candidate Privacy Policy.

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google"s EEO Policy, Know your rights: workplace discrimination is illegal, Belonging at Google, and How we hire.

If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes.

Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.

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