Top AI Jobs in Montreal

As an AI Infrastructure Engineer, you'll develop and optimize AI infrastructure for financial markets, enhancing performance and scalability across GPU systems.

As an Intermediate Machine Learning Engineer, you will develop evaluation techniques, manage large language models, and collaborate on AI feature implementations, ensuring product quality and performance.

Lead a deep tech startup, utilizing your research skills in AI and neural networks to develop a minimum viable product and patent portfolio.

The role involves designing AI-powered tools to enhance developer productivity, improve code quality, and streamline engineering processes. It requires collaboration with engineers to integrate tools into workflows and a strong focus on continuous improvement through metrics and insights.

Lead design and implementation of AI product initiatives on Edge devices, optimizing ML models, and collaborating across business units to enhance performance and customer experience.

The Senior ML Operations Engineer will build and enhance machine learning products, collaborate with teams, and deploy AI solutions to improve healthcare technology.

As a Senior Machine Learning Platform Engineer, you'll enhance ML infrastructure, mentor juniors, and optimize data pipelines for high performance.

Design and implement technical evaluators for LLM assessment, optimize dataset management, and collaboratively build scalable evaluation frameworks to ensure reliability of AI models.

Lead GitLab's Custom Models team, manage high-performing engineers, and develop AI solutions tailored to customer needs while promoting innovation and collaboration.

Develop and improve the GitLab product with focus on AI capabilities and integration of technologies while collaborating in a remote team environment.

As a Staff Firmware Engineer, you will lead the design and development of embedded solutions, drive technology choices, and collaborate with the hardware team to ensure the accuracy of AI algorithms on edge devices. You will mentor engineers and oversee high-impact projects.

Developers will help train LLMs by evaluating and improving code, providing feedback for reinforcement learning, and ensuring code correctness and efficiency.

The Machine Learning Developer contributes to the deployment and maintenance of ML models, ensuring security and performance while mentoring peers.

The role involves training large-language models by evaluating and improving code, requiring strong software engineering, detailed code review skills, and effective communication.

Develop and integrate AI-driven internal tools and systems across various departments, enhancing efficiency and collaboration while ensuring best practices.

The role involves developing and maintaining AI systems within UEFN for Fortnite, collaborating with teams to enhance gameplay experiences.

Lead AI solution architecture and delivery, oversee multi-cloud implementations, mentor teams, and ensure security compliance in AI projects.

The role involves training large language models, reviewing and improving AI-generated code, and providing feedback for model training.

The role involves training large-language models by comparing code snippets, refactoring AI-generated code, and injecting feedback into the RLHF pipeline.

The AI Developer will design, build, and scale AI solutions, involving data analysis, model development, and integration with business teams to enhance organizational processes.

The Senior Applied AI/ML Scientist leads the development of AI/ML solutions, collaborates with teams, and drives product innovation to enhance customer value.

As an Intermediate Frontend Engineer, you will develop UI for GitLab's AI discovery platform, collaborate with teams, and maintain code quality.

The role involves creating training data for AI models, evaluating AI-generated code, and developing React components. Candidates must have 3+ years experience in JavaScript and React.

Design and implement core data systems for AI/ML workflows. Specialize in data infrastructure or labeling systems, collaborating with ML engineers and product teams to deliver effective data and labeling solutions.

The Software Engineer will train large-language models by evaluating and improving AI-generated code, focusing on code quality and correctness.