Location
London

Hours
Full Time

Salary
Negotiable

About the Role
At Google, research-focused Software Engineers are embedded throughout the company, enabling them to set up large-scale tests and deploy promising ideas quickly and broadly. Ideas may originate from internal projects or collaborations with research programs at partner universities and technical institutes worldwide. From creating experiments and prototyping implementations to designing new architectures, engineers tackle real-world problems including artificial intelligence, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, and core search technologies.

As a Research Engineer at Google DeepMind, you will combine science and software engineering to solve sequential decision-making problems under uncertainty for power grids. This includes challenges such as unit commitment and congestion management at scale. DeepMind is a pioneering AI lab focused on advancing AI development to address complex global challenges and accelerate high-quality product innovation for billions of users. We prioritize safety, ethics, and public benefit while pushing boundaries across multiple domains. Our global teams provide diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.

Responsibilities include solving sequential decision-making problems under uncertainty for power grids at scale, and preparing reports and presentations to communicate findings and progress.

Experience
- Minimum 3 years of experience in reinforcement learning or optimal control
- Minimum 3 years of experience in software engineering
- Minimum 3 years of experience in Machine Learning (ML)
- Preferred experience working with power grid systems
- Preferred experience with mathematical optimization

About you
You are a motivated research engineer capable of bridging the gap between scientific research and software engineering. You have a strong interest in solving complex sequential decision-making problems under uncertainty, particularly in the context of power grids. You thrive in interdisciplinary teams and are committed to advancing AI technologies responsibly and ethically.

Qualifications
Bachelor's degree or equivalent practical experience is required.