Google DeepMind is one of the world's leading AI research labs, and this Research Developer Frontier AI Incubation team — a group pushing the boundaries of foundational AI systems across multiple domains, from personalized model adaptation to multimodal reasoning and agentic workflows.

This isn't a role where you're maintaining existing pipelines. You'll be doing end-to-end technical development — designing algorithms, running experiments, building production-grade architectures, and partnering directly with Google product and development teams to bring cutting-edge AI capabilities into real-world environments. The work spans research and product, and you'll be expected to move fluidly between both.

About the Role: Research Developer, Frontier AI Incubation At the core of this position is the design, training, and optimization of foundational algorithms and machine learning systems . You'll lead technical development from early algorithmic design through to production-grade architecture and scaled serving infrastructure , ensuring that promising research ideas can be deployed broadly and quickly.

Project Helix , agent workspaces, and intelligent system integrations. 185,000 – $190,000 CAD per year , plus a 15% bonus target , equity, and a full benefits package. Montreal, QC, Canada

185,000 – $190,000 CAD/year + 15% bonus target + equity + benefits In this role, you'll be operating across the full technical stack — from early-stage algorithm design through to scaled deployment. The work demands both rigorous scientific thinking and strong engineering execution, and your contributions will directly shape how Google DeepMind's frontier AI systems foundational algorithms and ML systems, including personalized model adaptation, agentic workflows, contextual memory architectures, energetic prompt optimization, and multimodal reasoning





Lead end-to-end technical development from algorithmic design and experimental prototyping through to production-grade architecture and scaled serving infrastructure with Google development and product teams to integrate and harden core technologies within production environments, including Project Helix, agent workspaces, and intelligent system integrations

Google DeepMind is looking for someone who combines a strong foundation in computer science or machine learning with hands-on experience building and deploying ML systems. The ideal candidate is equally comfortable in a research context and a production engineering environment, and can navigate both with confidence.

Bachelor's degree in Computer Science, Machine Learning, Mathematics, Statistics, or equivalent practical experience in machine learning, algorithm design, data structures, or distributed software systems

2 years of programming experience in Python or C++

taking technical projects or ML systems from conceptual formulation through to implementation and deployment

Experience with foundation model development , including techniques such as reinforcement learning from human/AI feedback, supervised fine-tuning, parameter-efficient tuning, or inference optimization (preferred)

Experience with ML frameworks and large-scale model training or serving infrastructure (preferred)

Experience collaborating across research and product boundaries to co-design technical architectures (preferred)

Strong scientific analysis , technical problem-solving, and communication skills (preferred)

Bachelor's degree in Computer Science, Machine Learning, Mathematics, Statistics, or equivalent practical experience; 2 years of experience in machine learning, algorithm design, data structures, or distributed software systems; 2 years of experience programming in Python or C++; 1 year of experience taking technical projects or machine learning systems from conceptual formulation to implementation and deployment.

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📌 Frontier Ai Research Engineer (Montreal)
🏢 Google Canada
📍 Montreal