Research Scientist, Paradigms of Intelligence – Google – Montreal, QC

Google’s Technology & Society organization is looking for a Research Scientist, Paradigms of Intelligence to join a team doing genuinely cutting-edge work in Montreal, QC or Toronto, ON (with additional locations available in the US). This is a rare chance to explore alternative AI paradigms beyond today’s trending approaches — and to publish findings that could shape the next generation of artificial intelligence.

In this role, you won’t be working on incremental improvements. The team’s mandate is to discover novel AI algorithms that are efficient on typical or alternative computing substrates, with a particular focus on how Large Language Model (LLM) techniques can accelerate the discovery of these algorithms. You’ll conduct sustained exploratory research, design experiments, and contribute meaningfully to the broader scientific community through publications and presentations.

About the Role: Research Scientist, Paradigms of Intelligence

As a Research Scientist at Google, you’ll work on real-world problems spanning machine learning, deep learning, natural language processing, program synthesis, and automated code discovery. You’ll set up large-scale tests, deploy ideas quickly, manage timelines and deliverables, and apply the latest theoretical frameworks to develop improved products, processes, and technologies. From prototyping implementations to designing new architectures, the scope of this work is broad and genuinely impactful.

Collaboration is central to this position. You’ll work both in person and remotely with colleagues across Google and with research programs at partner universities and technical institutes worldwide. Sharing ideas — through internal channels, journals, and scientific conferences — is a core expectation of the role, not an afterthought. Google supports individuals and teams with the freedom to emphasize the type of research that matters most to them, within a portfolio of fundamental and applied research projects.

Benefits and Salary

Google offers competitive compensation for this role. For Canadian-based candidates, the salary range is $150,000–$153,000 CAD, plus a 15% bonus target, equity, and a comprehensive benefits package. US-based positions offer $147,000–$210,000 USD under the same bonus and equity structure. Google’s benefits programme is well-regarded and covers a wide range of employee needs — visit Google’s careers page to learn more about the full offering.

Responsibilities

As a Research Scientist on the Paradigms of Intelligence team, your day-to-day work centres on pushing the boundaries of what AI can do — not just optimizing existing systems, but discovering fundamentally new approaches. These responsibilities are what drive Google’s position at the forefront of artificial intelligence research.

• Conduct sustained exploratory research into alternative AI paradigms beyond currently trending methods
• Review scientific literature, identify key open questions, and design experiments to address them rigorously
• Interpret experimental results and translate findings into actionable insights for algorithm development
• Develop and publish breakthroughs in both algorithm discovery methods and the resulting algorithms themselves
• Present research at top-tier journals and scientific conferences, contributing to the wider academic community
• Collaborate in person and remotely with researchers across Google and at partner universities worldwide
• Maintain a respectful work environment while communicating ideas clearly, both verbally and in writing

Requirements / Skills

Google is looking for a researcher who can operate independently at the frontier of machine learning and AI, with a track record of producing publishable, impactful work. The ideal candidate brings deep technical expertise alongside the curiosity and rigour needed to explore uncharted territory in AI algorithm discovery.

• PhD in Computer Science or a closely related field, or equivalent practical experience — this is a minimum requirement
• Scientific publication history with at least one submission to a recognized venue such as CVPR, ICCV, NeurIPS, ICML, or ICLR
• Post-doctoral experience is preferred and will strengthen your application
• Machine learning expertise, including hands-on experience training and fine-tuning Large Language Models (LLMs)
• Experience with program synthesis or automated code discovery using LLM-based techniques
• Strong programming skills with the ability to implement and test complex research ideas efficiently
• First- or last-authored publications at top ML venues (ICLR, ICML, NeurIPS) are a significant asset

How to Apply

To apply, visit the official Google job posting using the link below. Make sure your resume and any relevant publication list are up to date before submitting.

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