Research Engineer, AI for Weather and Energy

Overview Research Engineer, AI for Weather and Energy "” At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives to create extraordinary impact. We are committed to equal employment opportunities and do not discriminate on the basis of sex, race, religion or belief, ethnicity or national origin, disability, age, citizenship, marital or civil partnership status, sexual orientation, gender identity, pregnancy, or related conditions. If you have a disability or need accommodations, please let us know. Snapshot We have a unique culture and work environment where long-term ambitious research can flourish. Our Sustainability Program aims to revolutionize environmental sustainability with AI. We conduct fundamental research to develop novel AI methods and translate them into real-world applications and products. Our team pioneers AI weather models, including GraphCast, GenCast and FGN, which are advancing weather forecasting. This role focuses on developing cutting-edge deep learning and engineering methods and applying them to sustainability challenges, with opportunities to work on weather, climate, energy and related domains. About us Google DeepMind is a team of scientists, engineers and machine learning experts working to advance AI for public benefit, with safety and ethics as a priority. The role Research Engineers lead efforts in developing and scaling novel algorithmic methods that push the frontier of AI and its applications. We are seeking engineers who enjoy designing robust, scalable software systems for machine learning research and applications, with expertise or interest in environmental sustainability. Strong experience with modern ML architectures, scaling models and optimizing throughput is valued. Key responsibilities Design, implement, scale and evaluate state-of-the-art deep learning models (e.g., Transformers, GNNs) and software prototypes for sustainability-related problems. Build robust and scalable data processing and training pipelines to enable rapid research iterations. Report and present findings clearly and efficiently, 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 We look for candidates with the following skills and experience: BSc, MSc or PhD/DPhil in computer science, mathematics, applied statistics, machine learning or equivalent practical experience. Strong background in deep learning with architectures such as Transformers, GNNs, etc. Strong foundation in machine learning (e.g., supervised learning, probabilistic modeling, graph-based learning, optimization). Excellent software engineering skills and the ability to build robust, scalable systems. Proficiency in deep learning frameworks like JAX, TensorFlow or PyTorch. Experience with large-scale data processing frameworks (e.g., Apache Beam, Spark) or distributed training infrastructure. Advantageous Core OSS contributor. Experience with Python and its ecosystem. Experience with remote sensing data. Experience translating research into product applications. Interest/experience in weather/environmental sustainability and related fields (e.g., fluid dynamics, complex systems, optimization). Publications in top-tier conferences/journals. Compensation The US base salary range for this full-time position is between $182,000 - $215,000 plus bonus, equity and benefits. The recruiter can share the specific salary range for your location during the hiring process. Additional notes Offers are contingent on background checks performed by a third party. See our Applicant and Candidate Privacy Policy for details. #J-18808-Ljbffr

Created: 2025-10-01