Top Tech Jobs & Startup Jobs in Toronto

Develop and productionize fraud detection machine learning models using large-scale behavioral, device, network, and transaction data. Lead investigations into complex fraud attacks, reconstruct attacker behavior, identify trends, and produce technical reports and customer-facing insights. Collaborate with product, engineering, operations, legal, executives, and customers to improve detection systems and automate analytic workflows.

Lead the technical direction and hands-on development of a real-time fraud detection platform, including streaming, storage, distributed systems, machine learning training pipelines, and AI-assisted engineering tools. The role drives architecture, technical planning, operational health, incident prevention, production support, and collaboration with Product and customer-facing teams. It also mentors engineers, establishes AI-assisted development standards, and evaluates LLM- and agent-based tools for engineering operations.

Manage a portfolio of customers as a trusted technical advisor for fraud and risk use cases. Oversee data integration and onboarding, troubleshoot platform performance, architect ML and rule-based solutions, lead deployments and business reviews, and coordinate cross-functionally to drive adoption and product improvements.

Lead and facilitate agile sprint and release processes across engineering teams: run sprint planning, track metrics, coordinate QA and bug fixes, control release scope and branching, run incident response and postmortems, manage cross-team projects, and report status to senior leadership.