Top Tech Jobs & Startup Jobs in Montreal

Evaluate and label model-generated and human-written code outputs, debug and assess code/agent trajectories, prompt models for complex data science tasks, review visualizations, and report quality trends to improve model behavior.

Lead North's integrations strategy and execution: prioritize, ship, and drive adoption of connectors and ecosystem tooling. Partner with customers and engineering to convert integrations into reusable platform capabilities (auth, connector framework, data sync, permissions). Define developer/partner experience (APIs, SDKs, plugins) and instrument analytics to measure adoption, time-to-stand-up, and retention.

The Staff Software Engineer will develop and deploy high-performance machine learning systems, optimizing large language models for production environments. Responsibilities include ensuring high availability and low latency for AI applications and working collaboratively across teams.

The Site Reliability Engineer will develop, deploy, and operate AI infrastructure, focusing on high-performance and scalable machine learning systems using Kubernetes and cloud platforms.

As a Forward Deployed Engineer, you will build and ship features for an AI workspace platform, develop autonomous agents, and manage end-to-end deployments, collaborating closely with clients in various sectors.

As a Software Engineer in Data Infrastructure, you will build and maintain high-performance data storage systems for AI training, collaborate with experts, and optimize data processing.

Lead strategic sourcing and procurement for professional services categories, including consulting, marketing, legal, communications, and other external services. Manage end-to-end procurement, RFPs, vendor negotiations, category strategies, contracts, supplier performance, compliance, savings initiatives, and purchase-to-pay processes. Collaborate with FP&A, Accounting, Legal, and business stakeholders while maintaining documentation, controls, and performance reporting.

Owns revenue enablement programs for North American field teams from design through rollout, measurement, and iteration. Partners with Product, Marketing, Sales Leadership, and RevOps to align go-to-market priorities. Develops playbooks, certifications, training, and competitive resources; operationalizes MEDDPICC; tracks enablement KPIs; improves content platforms and AI workflows; coaches sellers; and translates field insights into updated enablement materials.

Build and maintain internal applications that support annotators, ML researchers, product managers, and other stakeholders. Develop user-facing browser and server experiences using full-stack technologies, design resilient mission-critical systems, improve engineering velocity, and collaborate through pairing, architecture, documentation, and technical talks. The role requires comfort across frontend and backend development, complex SQL, stakeholder collaboration, and adoption of new technologies.

Build and scale ML-optimized HPC infrastructure, manage Kubernetes-based GPU/TPU superclusters, optimize for AI/ML training, and mentor teams while innovating in ML infrastructure.