Top Tech Jobs & Startup Jobs in Montreal

As a Data Engineer, you'll develop storage infrastructure, collaborate with teams, implement data systems, and contribute to product strategy. You'll work with advanced AI systems and process production-grade data.

Drive independent, high-impact research on frontier AI topics, publish findings, collaborate widely, and mentor new researchers in the field.

Provide legal guidance for product development and commercialization: create templates and playbooks, manage IP and open source compliance, mitigate product lifecycle risks, coordinate legal input for launches, advise product, engineering and business teams, and monitor relevant technology regulations.

Lead end-to-end technical programs for ML infrastructure (inference, serving, efficiency, endpoints). Coordinate cross-functional teams, prioritize overlapping projects, manage timelines, budgets and scope, drive incident management and continuous improvement, and communicate status to engineering and leadership.

As a Software Engineering Intern, you will contribute to building features for user-facing products, APIs, and scalable services for machine learning. Responsibilities include crafting code, designing data pipelines, implementing tools, and enhancing technical documentation.

The engineer will develop features for an AI workspace platform, deploy AI solutions in public sector environments, and interact with clients.

The Director of People Operations will establish systems and infrastructure for managing People operations at scale, addressing operational challenges in a globally distributed environment.

Design, build, and maintain automation and testing infrastructure for the North platform: CI/CD pipelines, GitHub workflows, containerized test environments (Docker/Kubernetes), Helm and ArgoCD deployments, infrastructure-as-code, benchmarking, parallel test execution, and cross-team standards to improve test coverage, reliability, and deployment confidence.

Build and ship full‑stack features for North, an enterprise AI workspace. Develop secure autonomous agents, execution engines, integrations, observability and evaluation systems. Collaborate with researchers to productionize models and deliver performant, low‑resource deployment code while adhering to strict security and privacy constraints.

Lead the deployment of AI solutions for public sector clients, ensuring compliance with security standards while integrating AI into enterprise workflows.