Top Machine Learning Jobs in Toronto

Lead end-to-end test strategy and delivery for complex platforms. Act as SDET or Journey Test Lead, maximizing automation (Java, Rest Assured, Selenium, Appium), designing test architecture, service virtualization, test data management, and early-quality practices. Mentor teams, troubleshoot, and drive quality across multiple delivery teams and product lines.

Lead and execute IT audits, assess IT risk and compliance (e.g., PCI DSS, PIPEDA), advise business and IT on controls, develop audit plans, report findings to senior management, and help integrate AI into audit practices while managing and mentoring the audit team.

Design, optimize, test, and benchmark prompts and agent tool descriptions to improve AI performance. Collaborate with Customer Success and Data Science, automate evaluation and testing, document prompt practices, and research new NLP and model-specific prompting strategies.

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.

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.

As a Staff Machine Learning Engineer, you'll lead AI initiatives using large-scale data, optimize ML models for edge devices, and collaborate with cross-functional teams.

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 technical vision, research, and engineering for a unified computer vision platform. Define long-term research agenda, drive MLOps and deployment across edge/cloud, set performance metrics, manage and scale distributed teams, and translate product needs into scalable, production-ready visual intelligence solutions.

As an Intern Researcher, contribute to research on large language model-based agents, focusing on evaluation and autonomous reasoning. Involves formulating problems, conducting experiments, and contributing to publishable work.

Build and maintain Python back-end systems and ML pipelines for medical claims processing. Design scalable, high-performance architecture, resolve performance issues, handle complex data structures, document system components, and collaborate with front-end engineers in a fast-paced AI-driven environment.

Design, develop, and maintain scalable full-stack features for SOTI XSight using C#, .NET, TypeScript, and Angular. Drive architecture, integrate analytics/AI, mentor developers, troubleshoot complex issues, and collaborate with stakeholders to deliver high-quality, cloud-ready solutions.

The Associate Director of Data Sciences drives SOTI's AI and data strategy, develops AI capabilities, and mentors teams to enhance product efficiencies.

The Campaign Operations Associate will manage technical operations, monitor campaign performance, diagnose issues, and coordinate with cross-functional teams to enhance operational workflows.

The AI Product Manager will lead the development of AI-powered applications, collaborating with engineers and designers to align AI technologies with user needs and business objectives.

As an AI Product Manager, you will lead the product development for AI-driven features, collaborating with engineers and designers to optimize user experiences and ensure alignment with business objectives.

The AI Developer II role involves delivering AI and machine learning solutions, integrating into teams, and evolving AI software products across various projects.

Lead a product portfolio for Clio's core case management experience, utilizing legal expertise to drive innovation and user adoption while simplifying attorney workflows with AI tools.

The Product Manager will oversee AI capabilities development within Caseware, shaping priorities, requiring technical fluency, and ensuring quality through evaluation frameworks and collaboration with domain experts.

Design, build, and operate production ML models, services, and platforms for pricing, risk, and decision systems. Own end-to-end model pipelines, deployment, monitoring, and iteration. Collaborate with researchers and product to productionize prototypes, tackle data drift and sparsity, lead design reviews, and mentor teammates.

As a Research Machine Learning Scientist, you will develop and apply deep learning techniques on large-scale datasets while collaborating with engineers. You will also research and innovate in AI applications to improve banking services.

As an ESG & CSR Responsible AI Intern, you'll develop AI ethics principles, collaborate with teams, conduct audits and promote transparency in AI practices.

Lead statistical and data science efforts for biologics development across Pharma Technical Operations: design experiments (DOE), analyze complex datasets using advanced statistics and ML/AI, build tools and automated workflows, interpret and communicate results, ensure regulatory alignment, mentor junior staff, and deliver training to upskill the organization.

Lead strategy, vision, and roadmap for a cross-functional squad across Everand and Fable. Drive product development for recommendations, search, and ranking systems, balance experiments and large investments, partner with engineering, design, research, and data to ship features that help readers discover books.

Lead development and production of underwriting and credit decisioning models across Cash App Borrow and Afterpay. Own full modeling lifecycle: problem formulation, feature engineering, training, calibration, experimentation, deployment, monitoring, and iteration. Build decision frameworks, agentic engineering workflows, and collaborate with cross-functional partners to align model behavior with business and regulatory goals.

Lead Agile teams delivering AI/ML initiatives: run Scrum ceremonies, remove impediments, manage plans/risks/dependencies, align stakeholders and executives, coordinate cross-functional AI program delivery and governance.