Top Machine Learning Jobs in Toronto

Conduct fundamental research in video generation, video editing, and 3D computer vision. Develop state-of-the-art AI and computer vision algorithms, create research prototypes, solve real-world problems, publish in leading conferences, integrate innovations into Huawei products, and supervise interns within collaborative R&D projects.

Conduct research and develop state-of-the-art speech and audio AI technologies. Responsibilities include literature reviews, algorithm implementation, data collection and analysis, deep learning and signal processing, and documenting, presenting, and publishing results while collaborating with researchers under supervision.

Lead design and delivery of ML and AI solutions by mining large datasets, building predictive models, and collaborating with product and analytics teams to drive data-driven business decisions and improve customer experience. Provide technical consulting, scale analytics solutions, and apply risk-aware decision making.

Develop and maintain software tools and infrastructure supporting machine learning and AI workflows. Build backend services, APIs, automation tools, and integrations; support large-scale experiments, evaluation, and data processing. Debug issues, improve reliability and performance, collaborate with researchers and engineers, gather user feedback, provide technical support, and write clean, tested code.

Conduct research and development in computer vision, machine learning, LLMs, and vision-language models. Develop image and video understanding or generation systems, multimodal reasoning and agentic applications, and optimize models for mobile computing constraints. Responsibilities include prompt engineering, model adaptation, fine-tuning, evaluation, and applied AI research.

Develop, test, and maintain GenAI/ML-based application components; implement new features, unit tests, and fixes; collaborate with stakeholders and tech partners; participate in code reviews, incident management, and continuous improvement; mentor team members and ensure solutions meet performance, security, and governance standards.

Lead AI risk assessments and governance for the model lifecycle. Ensure AI solutions meet enterprise policies and regulations, maintain risk registers, monitor controls, partner with Privacy/Security/Legal, drive remediation, and report AI risk posture to leadership while improving governance frameworks to enable responsible AI adoption.

Lead AI risk assessments and governance processes to ensure AI solutions meet enterprise policies and regulatory requirements. Monitor model lifecycle risks, maintain risk registers, coordinate remediation, and partner with Privacy, Security, Legal, and business teams. Develop reporting and improve AI governance frameworks to enable responsible innovation.

Analyze large financial datasets, build dashboards and data models (Power BI/Tableau/Excel), support forecasting, KPIs, and reporting automation; collaborate with finance and accounting to deliver data-driven insights and audit support.

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.

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.

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

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.

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 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.

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.

Own the vision, strategy, roadmap, development, adoption, and continuous improvement of eBay’s experimentation platform. Partner with users, design, engineering, and product teams to define requirements, prioritize investments, launch capabilities, and measure outcomes. The role requires expertise in experimentation fundamentals, runtime and triggering, analysis pipelines, and monitoring for bias, novelty, and interference, along with strong strategic, analytical, communication, collaboration, and delivery skills.

Conduct quantitative investment research using Python and MATLAB, applying statistics, machine learning, and optimization to develop systematic strategies. Clean, visualize, and model financial datasets; review and implement research; optimize portfolio tools and infrastructure; present findings; and propose original ideas across asset classes including equities, fixed income, currencies, and commodities.

Conduct quantitative research to develop and test systematic investment strategies across asset classes. Apply statistics, machine learning, optimization, and programming to financial datasets; review and implement research papers; source, clean, visualize, and model data; present findings; propose original ideas; and improve portfolio implementation infrastructure and analytical tools.

Lead and manage financial crimes audit program for high-risk areas, assess internal controls and regulatory compliance, plan audits, perform risk assessments, manage issues, oversee audit teams as Auditor-in-Charge, coordinate with other audit groups, and apply data analytics and emerging technologies to testing and reporting.

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.

Designs, develops, tests, and optimizes scalable machine learning and deep learning systems. Builds ML applications, algorithms, tools, and data pipelines; transforms unstructured data into useful information; trains models, monitors drift, analyzes results, and scales analytics solutions for business decision-making. Requires collaboration with data and analytics professionals and sound risk-aware decision-making within banking policies and regulations.

Designs, develops, tests, and deploys scalable machine learning and deep learning systems. Builds and improves data pipelines and lakes, trains models, prevents model drift, optimizes algorithms and frameworks, and converts unstructured data into useful insights through image and speech applications. Performs statistical analysis, interprets results, and develops repeatable analytics and decision-support solutions while adhering to banking risk-management requirements.