Top AI & Machine Learning Jobs in Toronto, ON

Own the architecture and technical strategy for Square’s go-to-market technology stack. Build and operate production AI agents, automated workflows, and scalable integrations that improve sales productivity. Lead complex technical initiatives across teams, establish AI reliability and security guardrails, define evaluations and success metrics, and guide build-versus-buy decisions. Remain hands-on across prototyping, implementation, testing, deployment, and operations while mentoring engineers and influencing senior business and technical stakeholders.

Graduate research co-op focused on building Customer World Models and proactive intelligence: designing representation learning, foundation-model, reinforcement learning, and agentic systems; running experiments, publishing, and deploying research into production to improve long-horizon decision-making and customer-facing automation.

Build and operate production machine learning systems for ranking, retrieval, recommendations, search, propensity, churn, LTV, and next-best-action decisioning. Design reliable signal contracts covering freshness, provenance, confidence, eligibility, and calibration. Lead feature pipelines, model serving, experimentation, monitoring, and feedback loops while evaluating fairness, risk, compliance, trust, and long-term customer impact. Collaborate across product, growth, data, platform, modeling, risk, and compliance teams.

Own the end-to-end People data and AI ecosystem, including pipelines, governed data models, predictive analytics, engagement survey analysis, and agentic AI workflows. Build production systems using Python, SQL, orchestration tools, cloud warehouses, LLMs, and evaluation frameworks. Establish technical standards, privacy guardrails, and human oversight for sensitive workforce data while translating analyses into actionable leadership decisions. Lead through architecture, code, design reviews, and mentorship without managing a team.

Lead pricing modeling and experimentation to optimize margin, conversion, and retention. Build elasticity and willingness-to-pay models, run causal and bandit experiments, decompose merchant economics, and develop agentic deal tooling. Own end-to-end data pipelines, ETL, monitoring, and visualization. Evaluate AI systems for accuracy, bias, and drift, and partner with cross-functional teams to translate results into pricing strategy and automation.

As a Staff Machine Learning Engineer, you will enhance credit modeling, manage full credit modeling stacks, and support innovations within regulated banking frameworks.

Build and deploy agentic and generative AI systems that automate risk and compliance investigations. Own full-stack ML systems, including data integrations, prompt tuning, orchestration, evaluation, productionization, monitoring, and transformer-based modeling across transaction, graph, text, and profile data. Collaborate with product, engineering, platform, and operations teams while leading strategic roadmaps and delivering scalable production systems.

Graduate research interns will own end-to-end projects to build customer world models and proactive intelligence: developing representation learning, foundation model, RL/agentic methods, evaluation frameworks, and shipping research into production to improve customer decision-making.

Lead architecture and technical strategy for AI-driven product quality systems using LLMs and agents. Build scalable evaluation frameworks, detect regressions, generate insights, and drive cross-functional adoption while mentoring engineers and defining standards for trustworthy AI.

Lead development and implementation of AI legal and compliance frameworks. Conduct cross-functional AI reviews, maintain governance docs (model cards, impact assessments), partner with engineering on transparency and fairness requirements, build incident response and monitoring processes, and scale AI legal review workflows.