Top AI Jobs in Montreal

The Senior Security Engineer will establish security frameworks for AI initiatives, manage non-human identities, and collaborate with cross-functional teams to ensure secure AI adoption across GitLab's internal tools.

Manage a team of AI engineers in developing AI-powered features, collaborating with various stakeholders while also contributing hands-on to the codebase.

As a Senior Engineer at 8am, you will design and implement AI features, collaborate with teams, and develop tools for AI deployment.

Manage a team of engineers, oversee project execution, partner with Product Managers, ensure high-quality software and Agile practices, and drive AI integration efforts.

The software engineer will design and deploy AI-powered automation, enhance user experience, and implement LLM-backed features in collaboration with teams.

The role involves designing and building AI-powered experiences in Dropbox, collaborating across teams, and shipping features to enhance user interactions.

As a QA Annotator, you'll review data, ensure quality of annotations, label content, and flag inaccuracies for AI projects.

The Senior Software Engineer will build core services and SDKs for production-grade systems, lead projects enhancing tools, and collaborate cross-functionally.

Contribute to fullstack features using JavaScript, Ruby, and Python, collaborating with teams for development, bug fixes, and performance enhancement.

The role involves developing features for GitLab's AI-powered platform, advocating for quality improvements, and collaborating within a remote team.

As a Senior Software Engineer, you will evaluate AI-generated code, solve coding problems, and write robust test cases to enhance AI models.

The role involves designing and maintaining robust cloud-native infrastructure, developing scalable data pipelines, automating deployment, and integrating AI solutions to enhance decision-making and business efficiency.

As a Tech Lead in AI Software Development, you will lead system design, mentor developers, ensure quality delivery, and collaborate with cross-functional teams to deliver impactful AI solutions.

Develop and deploy AI-powered applications using LLMs, ensuring integration with web apps, performance optimization, and collaboration with cross-functional teams.

Develop and enhance Autodesk's AI/ML platform by designing systems, automating processes, and ensuring scalable deployment of machine learning solutions, collaborating with cross-functional teams.

Design and develop scalable data infrastructure for AI platform, optimize database performance, create data pipelines, and mentor junior engineers while collaborating across teams.

The Technical Director will lead technical direction, ensure quality project execution, guide teams, and serve as a trusted advisor to clients in AI and Data initiatives.

The Research Engineer will develop the DeOS framework, optimizing AI workloads, managing GPU resources, ensuring scalability, and contributing to open-source projects.

As a Software Developer, you will create training data for AI models, audit tool usage, write test cases, and improve technical outputs. No prior AI experience is necessary, but coding skills are critical.

Design, implement, and maintain gameplay systems in Unreal Engine, collaborating with teams to optimize performance and document code.

The Principal Full Stack Developer will design and build cloud-native applications, collaborate with teams, and contribute to product evolution with a focus on best practices and technology.

The role involves designing, implementing, and maintaining ML algorithms and systems, collaborating with teams, and integrating AI into applications.

As a Senior Backend Developer, you will design, build, and scale backend systems for AI agents, optimize APIs, and mentor junior engineers.

The Senior .NET Developer will design architecture for high-loaded applications, develop functionalities, implement components and services, and ensure quality control.

Design and implement infrastructure for deep learning model training and deployment in self-driving trucks, optimizing performance and metrics tracking.