Research Scientist, Paradigms of Intelligence

Google's Technology & Society organization is seeking a Research Scientist, Paradigms of Intelligence in Montreal, QC or Toronto, ON, Canada (with additional locations in Cambridge, MA; Mountain View, CA; and New York, NY).

Our team conducts basic research into alternative AI paradigms beyond those currently trending. Our goal is to discover novel AI algorithms that can be efficient to run on typical or alternate computing substrates, using a mix of automated, hand-designed, and hybrid methods — specifically focusing on how advancing Large Language Model (LLM)-related techniques can accelerate this process.

• Carry out sustained exploratory research into alternative AI paradigms.
• Review literature, identify key questions, design experiments, and interpret results.
• Collaborate in person and remotely; maintain a respectful work environment.
• Share ideas verbally and in writing; publish and present work at journals or scientific conferences.

• PhD degree in Computer Science, a related field, or equivalent practical experience.
• One or more scientific publication submission(s) for conferences, journals, or public repositories (such as CVPR, ICCV, NeurIPS, ICML, ICLR, etc.).

• Post-doctoral experience.
• Experience in the field of machine learning.
• Experience in the training and fine-tuning of LLMs.
• Experience in the use of LLMs in fields of program synthesis or automated code discovery.
• Excellent computer programming skills.
• First-authored or last-authored publications in the field of machine learning at top venues (e.g., ICLR, ICML, NeurIPS).

Canada: $150,000 – $153,000 CAD + 15% bonus target + equity + benefits.

PhD in Computer Science or related field (or equivalent practical experience); at least one scientific publication submission to a recognized venue such as NeurIPS, ICML, ICLR, CVPR, or ICCV. Preferred: post-doctoral experience, machine learning expertise, LLM training and fine-tuning experience, program synthesis or automated code discovery experience, strong programming skills, and first- or last-authored publications at top ML venues.