Research Developer, Frontier AI Incubation

DeepMind; Montreal (administrative region); On-site; CAD 185,000 - 190,000; Full time

Benefits offered by this job

Equity

Bonus target

Benefits

Job summary

Google DeepMind's Frontier AI Incubation team in Montreal, QC seeks a Research Developer to design and scale foundational ML systems, from algorithmic ideas to production-grade implementations, partnering with Google development and product teams.

You will prototype innovative architectures, optimize performance and serving infrastructure, and help deploy AI capabilities that impact billions of users through rigorous evaluation and collaboration across research and product domains.

Qualifications

• Bachelor's degree in CS, ML, Math, Stats, or equivalent.
• 2 years of experience in ML, algorithm design, data structures, or distributed software systems.
• 2 years of Python or C++ programming experience.
• 1 year of experience taking ML projects from concept to deployment.

Responsibilities

• Design, train, and optimize foundational algorithms and ML systems.
• Lead end-to-end technical development from design to production-grade architecture and scaled serving infrastructure.
• Partner with Google development and product teams to integrate core technologies within production environments.
• Formulate evaluation methodologies to measure capability gains, latency/compute efficiency, alignment, and personalization fidelity.

Skills

Python

C++

Machine Learning

Algorithms

Distributed systems

Education

Bachelor's degree in Computer Science, Machine Learning, Mathematics, Statistics, or equivalent

Tools

ML frameworks

Large-scale training

Serving infrastructure

Job description

At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We are looking for a Research Developer to join our Frontier AI Incubation team in Montreal, QC, Canada.

Responsibilities

• Design, train, and optimize foundational algorithms and ML systems (e.g., personalized model adaptation, agentic workflows, contextual memory architectures, dynamic prompt optimization, and multimodal reasoning).
• Lead end-to-end technical development from algorithmic design and experimental prototyping to production-grade architecture and scaled serving infrastructure.
• Partner directly with Google development and product teams to integrate and harden core technologies within production environments (e.g., Project Helix, agent workspaces, and intelligent system integrations).
• Formulate novel automated and human-in-the-loop evaluation methodologies to measure capability gains, latency/compute efficiency, alignment, and personalization fidelity.

Minimum Qualifications

• 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.

Preferred Qualifications

• Experience developing, fine-tuning, or optimizing foundation models including techniques such as reinforcement learning from human/AI feedback, supervised fine-tuning, parameter-efficient tuning, or inference optimization.
• Experience or interest in personalization, adaptive systems, user modeling, retrieval-augmented generation, or agentic memory architectures.
• Experience with machine learning frameworks and large-scale model training or serving infrastructure.
• Experience collaborating across research and product boundaries to co-design technical architectures.
• Experience in scientific analysis, technical problem-solving, and technical communication.

Compensation

Canada: $185,000 - $190,000 CAD + 15% bonus target + equity + benefits.

Bachelor's degree in Computer Science, Machine Learning, Mathematics, Statistics, or equivalent. 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 ML projects from concept to deployment.