Sustainability Research Engineer, DeepMind

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 - $210000 (USD) + 15% bonus target + equity + benefits Learn more about benefits at Google . Enhance technologies for power grids such as dynamic line rating. Work closely with the Energy grids and Weather teams to integrate dynamic line rating into grid optimization and operation. Prepare reports and presentations. Minimum qualifications: Bachelor's degree in Electrical Engineering, Power Engineering, a related technical field, or equivalent practical experience. 3 years of experience with software engineering/programming. 3 years of experience in power or performance modeling or systems performance analysis. 2 years of experience in machine learning fields. Experience working with real grid operator data. Preferred qualifications: Experience with modeling or simulation of Grid-Enhancing Technologies (GETs). Experience building power systems optimization models in Python or Julia. Experience with complex physical or environmental data systems, with specific interest or expertise in weather forecasting, climate modeling, energy grid systems, or related sustainability fields.