Overview
As a Research Engineer at Google DeepMind, you help solve sequential decision-making problems under uncertainty for power grids. You work at the intersection of science and software engineering, running experiments, prototyping architectures, and deploying promising ideas at scale. You collaborate with research partners and universities, bridging theory and real-world impact in AI, optimization, and energy systems. Your work supports safe, impactful AI innovations that benefit billions of users.
Responsibilities
- solve sequential decision-making problems under uncertainty for power grids (e.g., unit commitment, congestion management)
- design, prototype, and deploy architectures and experiments at scale
- conduct experiments and evaluate new approaches across AI/ML, optimization, and power systems
- collaborate with universities and research programs to publish and share findings
- work on real-world problems spanning AI, data mining, NLP, hardware/software performance, and compilers
- contribute to research-driven product innovations and broaden deployment of promising ideas
Key requirements
- 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)
- collaboration and teamwork
- ability to communicate research ideas to non-experts
- initiative and intellectual curiosity
- reinforcement learning
- optimal control
- machine learning (ML)
Research Engineer, Energy Grids, Sustainability, DeepMind in London employer: Google
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