Research Engineer, AI for Sustainability

Research Engineer, AI for Sustainability
San Francisco / Mountain View, CA

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
At Google DeepMind, we've built a unique culture and work environment where long-term ambitious research can flourish. Our team is part of our Sustainability Program, whose aim is to revolutionize environmental sustainability with AI. We conduct fundamental research which develops novel AI methods, and we translate our research advances into real-world applications and products. This role focuses on weather and climate, and the connections to energy, water, nature, and other key sustainability domains.

About us
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.

The role
Research Engineers at Google DeepMind lead our efforts in developing and scaling novel algorithmic methods that push the frontier of AI and its applications.

We are looking for creative thinkers with strong algorithm-design and programming skills, with expertise in, or passion for, environmental sustainability. Previous technical experience with machine learning architectures, scaling models, optimizing throughput, learned simulation, fluid dynamics, complex systems, combinatorial optimization, probabilistic modeling, and domain expertise in relevant sustainability problems are valued.

Key responsibilities

• Design, implement, scale and evaluate models and software prototypes for sustainability-related problems.
• Enable rapid research iterations by implementing and optimizing data and training pipelines.
• Report and present findings and developments clearly and efficiently, both internally and externally.
• Contribute to team collaborations to meet ambitious research and product goals.
• Engage with application and product needs, to inform research and engineering decisions.

About You
In order to set you up for success as a Research Engineer at Google DeepMind, we look for the following skills and experience:

• BSc, MSc or PhD/DPhil degree in computer science, mathematics, applied stats, machine learning or similar experience working in industry
• Strong background in machine learning foundations (esp. supervised learning, probabilistic modeling, graph-based learning, and/or optimization).
• Strong systems and engineering skills in deep learning frameworks like JAX. Familiarity with distributed systems and training / inference infrastructures.

In addition, the following would be an advantage:

• Core contributor to OSS projects.
• Experience with JAX and its ecosystem.
• Experience with remote sensing data.
• Experience translating research innovations into product applications.
• Commitment/experience/expertise in weather/environmental sustainability and/or allied areas (e.g., fluid dynamics, complex systems, combinatorial optimization, remote sensing).
• A proven track record of publications in top-tier conferences and/or journals.

The US base salary range for this full-time position is between $182,000 - $215,000 + bonus + equity + benefits. Your recruiter can share more about the specific salary range for your targeted location during the hiring process.

Application deadline: April 18th 2025

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