We’re looking for someone who is passionate about:
Building elegant infrastructure solutions for enabling and accelerating generative AI research
Working across the boundary of research and deployment and deeply understanding needs across the whole pipeline
Working directly with researchers on the next generation of AI development and the ambiguous engineering problems it introduces
About us
Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.
The role
We are seeking hard-working individuals with experience in machine learning research and full stack development, who are interested in creating and enhancing platforms to help research flourish! You’ll join an inspiring and collaborative environment, working on ground-breaking technology with potentially extraordinary impact.
This person will be responsible for building and streamlining a framework for developing and releasing AI-based systems, ensuring research efforts can iterate quickly and translate seamlessly into production-ready solutions.
Key responsibilities
Develop a framework for efficient preprocessing and AI agent development, to enable rapid research and prototyping.
Work closely with model developers and agent research teams to deeply understand their needs and ensure the framework meets their requirements.
Facilitate the transition of research into production: Develop and implement strategies for bringing research components into production smoothly and effectively, including working directly on the production infrastructure.
About you
In order to set you up for success as a Research Engineer at Google DeepMind, we look for the following skills and experience:
SWE interpersonal skills (discuss technical ideas effectively with colleagues, e.g. through whiteboard, design docs, presentations; interact directly with our end users on various channels)
Strong full-stack software engineering fundamentals, including fluency in Python and C++
Experience working with machine learning at scale
In addition, the following would be an advantage:
Experience working directly on/with AI research teams
Experience working on production infrastructure