Research Engineer, Energy Grids, Sustainability
Confirmed on the employer's own hiring board on Oct 18, 2026. First seen by Alion on Sep 23, 2026.
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.
We are looking for a research engineer (someone who can do both science and software engineering) who can help solve sequential decision making problems under uncertainty for power grids. This can include solving problems like unit commitment or congestion management.
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.
Responsibilities
- Solve sequential decision-making problems under uncertainty for power grids at scale.
- Prepare reports and presentations.
Qualifications
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 3 years of experience in reinforcement learning or optimal control.
- 3 years of experience in software engineering.
- 3 years of experience in Machine Learning (ML).
Preferred qualifications:
- Experience working with power grid systems.
- Experience with mathematical optimization.