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

Google’s Technology & Society organization is looking for a Research Scientist, Paradigms of Intelligence to join their team — with positions available in Montreal, QC and Toronto, ON (as well as Cambridge, MA and New York, NY for US-based candidates). This is a rare opportunity to conduct foundational AI research that goes beyond mainstream paradigms, contributing to breakthroughs that could reshape how artificial intelligence is built and deployed at scale.

The team’s mandate is genuinely ambitious: researching alternative AI paradigms that move beyond current trends, with the aim of discovering novel, efficient algorithms capable of running on standard or alternative computing substrates. If you’re driven by curiosity about what comes next in machine intelligence — and want your research to matter at a global scale — this role is worth a close look.

About the Role: Research Scientist, Paradigms of Intelligence

In this position, you’ll set up large-scale experiments, design new AI architectures, prototype implementations, and deploy promising ideas broadly and quickly. Your research will span topics including large language models (LLMs), agents, foundation models, LLM training and fine-tuning, and algorithm discovery — with a specific focus on how advancing LLM-related techniques can accelerate the discovery of novel AI algorithms. You’ll work on real-world problems in machine learning, deep learning, natural language processing, and more.

Beyond internal projects, you’ll be expected to publish and present your findings at top scientific journals and conferences, contributing actively to the global research community. Collaboration — both in-person and remotely — is central to this role, and the team values maintaining a respectful and intellectually rigorous work environment.

Benefits and Salary

Google offers a competitive compensation package for this role. In Canada, the base salary range is $150,000–$153,000 CAD, with a 15% bonus target, equity, and a comprehensive benefits package. US-based candidates can expect a range of $147,000–$210,000 USD plus the same bonus target and equity structure. Google’s benefits programme is well-regarded and covers health, wellness, and additional perks — visit Google’s careers page to learn more.

Responsibilities

As a Research Scientist on the Paradigms of Intelligence team, your day-to-day work centres on pushing the boundaries of AI algorithm discovery and contributing original, publishable findings. You’ll be expected to drive your own research agenda while collaborating closely with engineers and fellow scientists across Google and partner institutions.

• Conduct sustained exploratory research into alternative AI paradigms, including LLM-driven algorithm discovery and automated methods
• Apply research results in practice — implement findings and share them with researchers and engineers across the organization
• Review literature systematically to identify key open questions and gaps in current AI research
• Design experiments at scale, interpret results, and iterate toward novel algorithmic solutions
• Collaborate both in person and remotely with cross-functional teams while maintaining a respectful and productive work environment
• Publish and present original research at top-tier journals and scientific conferences such as NeurIPS, ICML, ICLR, ACL, NAACL, or EMNLP
• Share ideas verbally and in writing, contributing to internal knowledge-sharing and the broader global research community

Requirements / Skills

Google is looking for a researcher who combines deep theoretical grounding in machine learning with a demonstrated track record of independent, published work. The ideal candidate is comfortable operating at the frontier of AI research, has hands-on experience with large language models, and can navigate the balance between ambitious exploration and practical implementation.

• PhD in Computer Science or a related field (or equivalent practical experience) — required
• Two or more first-authored publications since 2021 at NeurIPS, ICML, ICLR, ACL, NAACL, or EMNLP — required
• LLM research experience demonstrated through two or more publications since 2021 — covering areas such as foundation models, transformers, agents, training, or fine-tuning
• Post-doctoral experience is a strong asset
• Experience applying LLMs to program synthesis, AutoML, automated code discovery, or automated science is preferred
• Proficiency in Python with hands-on experience using ML libraries such as JAX, TensorFlow, or PyTorch; C++ experience is also an asset

How to Apply

To apply, use the official link below to submit your application through Google’s careers portal. Make sure your resume and list of publications are current before submitting.

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