Top Machine Learning Jobs in Toronto

Lead technical product development for Business Identity offerings: define API and data requirements, prioritize roadmap, coordinate cross-functional teams, manage product lifecycle from discovery to go-to-market, and measure outcomes to ensure scalable, secure identity and intelligence services.

Lead product strategy and roadmap for AI-native capabilities in CrowdStrike's Next-Gen SIEM. Collaborate with engineering, data science, research, marketing, sales, and support to design, deliver, and position AI-driven detection, investigation, and prevention features. Conduct competitive analysis, define use cases, and engage customers to inform product direction while supporting go-to-market and cross-functional execution.

Lead and mentor a team of Product Managers to drive customer acquisition, engagement, and retention for credit products. Define growth strategies and success metrics while fostering collaboration across technology and design teams.

Lead a small team and contribute hands-on to design, develop, deploy, and iterate AML and crypto risk detection machine learning models. Own technical roadmap, collaborate with Product and Engineering, ensure model quality, explainability, documentation, and governance, and drive production performance and outcomes across the model lifecycle.

Lead the modernization of trade surveillance platforms, manage engineering teams, ensure compliance, and enhance detection using machine learning.

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

Lead a team of ML engineers to develop and improve fraud detection models, defining strategies and fostering collaboration across functions to ensure effective model integration.

The Senior Technical Product Manager will lead product vision for the ML team, collaborating with various teams to enhance user experiences through ML tools and data solutions, tracking KPIs and project lifecycles.

The Director of Digital Technology for Snacking will drive the technology strategy and digital transformation within the Global Snacking division, emphasizing innovation and customer experience, and overseeing tech-related investments and implementations.

As a Staff ML Engineer, you'll design and operate Samsara's ML platform, partnering with teams to deliver scalable ML solutions that enhance safety and efficiency in physical operations.

Lead teams in building end-to-end AI products focused on computer vision and sensor data. Oversee model lifecycle, data management, and deployment. Drive innovation in AI while fostering team development and ensuring customer success.

Lead cross-organizational technical strategy and execution for core sharing and collaboration systems. Architect and implement foundational frontend/backend and platform solutions at massive scale, drive AI/LLM adoption, mentor engineering leaders, resolve systemic bottlenecks, and remain hands-on in critical design, prototyping, and code contributions.

Lead engineering strategy and execution for GitLab's growth and monetization platforms including self-service purchase, billing, usage metering, entitlements, quote-to-cash, integrations (Zuora, Salesforce), and API-first scalable architectures. Align cross-functional partners, ensure reliability, compliance (SOX), and apply AI/ML for predictive pricing and usage forecasting to support usage- and impact-based pricing.

As a Product Manager, you'll lead product vision and strategy, utilizing customer insights and technology to create innovative solutions while collaborating with multiple teams.

Own vision, strategy, and roadmap for cost-optimization and energy-management products for fleets. Translate telematics and operational data into customer-facing features, run discovery, prototype MVPs, define success metrics, and ship end-to-end with cross-functional teams.

Lead full-stack development for Toast IQ, owning user experience, backend services, and product integrations. Drive architecture, mentor engineers, participate in design and code reviews, and apply ML/LLM capabilities to improve product velocity and reliability.

Lead product strategy for consumer credit, underwriting, merchant pricing, and loan economics. Define features, specs, and metrics; partner with engineering, analytics, design, commercial, legal, and capital to launch and scale products across channels and geographies.

Manage a team of ML engineers to develop machine learning solutions for underwriting applications. Set technical strategy, mentor engineers, and collaborate with teams across the organization.

Design and implement core pricing services, improve APIs, lead design reviews, ensure system reliability, and mentor junior engineers.

Lead a data science team to design and deliver merchant registry and profiling ML capabilities for onboarding and monitoring. Define strategy, guide model development and validation, promote reusable data assets, partner with Product and Engineering, drive Agile delivery, hire and mentor team members, and communicate impact to senior leadership to scale production ML systems on modern cloud/data platforms.

Design, implement, and scale production ML components and data pipelines using robust software engineering practices. Collaborate with customers and product teams to generalize use cases into platform features, deploy ML models to production, and maintain infrastructure (Kubernetes, Airflow, Terraform) and data services (BigQuery). Mentor teammates, write well-tested type-hinted code, and support successful customer implementations.

The Enterprise Account Executive will manage the complete sales cycle, build relationships with senior leaders, and drive platform adoption within data-intensive organizations.

The role focuses on extracting, cleaning data, building and maintaining machine learning models, and optimizing business strategies using data science methodologies.

As an Applied Scientist, you will push the limits of AI/ML in home valuation, tackling diverse ML challenges and optimizing decision-making with data.

Design and build an AI assistant and proprietary AI systems for residential property management. Own end-to-end development from ideation to production, maintain high code quality, ship product features, and lead cross-functional engineering efforts.