Research Engineer, Multimodal Reinforcement Learning
DeepMind
About this role
Research Engineer role within Google DeepMind’s Frontier AI Unit focused on advancing multimodal, image-grounded conversational learning. The position centers on extending meta-training via reinforcement learning to build scalable, semi-verifiable multimodal environments that improve the next generation of models such as Gemini. The role sits at the intersection of research and engineering, bridging core conversational research with visual grounding and infrastructure.
Skills
Qualifications
About DeepMind
deepmind.googleGoogle DeepMind is an AI research lab within Alphabet focused on solving intelligence and building safe, general-purpose artificial intelligence to advance science and benefit humanity. It develops cutting-edge machine learning methods—especially deep learning, reinforcement learning and neuroscience-inspired models—and has produced landmark systems such as AlphaGo, AlphaZero and AlphaFold. DeepMind partners with academia, healthcare providers and other Google teams to apply AI to scientific discovery, medicine, energy efficiency and real-world problems. The organization emphasizes safety, interpretability and responsible deployment alongside publishing research and tools for the wider community.
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About DeepMind
Headquarters
San Francisco, CA
Company Size
201-500 employees
Founded
2018
Industry
Technology
Glassdoor Rating
4.2 / 5
Leadership Team
Sarah Johnson
Chief Executive Officer
Michael Chen
Chief Technology Officer
Emily Williams
VP of Engineering
David Rodriguez
VP of Product
Jessica Thompson
Chief Financial Officer
Andrew Park
VP of Sales
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Salary
$147k – $199k
per year
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