Top Machine Learning Jobs in Toronto

Use legal training to create and evaluate AI training data: perform legal research and analysis, provide annotation and feedback, support senior team members, communicate insights, participate in stakeholder presentations, and advocate for Responsible AI.

Own the discovery, direction, delivery, adoption, and continuous improvement of AI- and analytics-powered products for Commercial Banking. Translate business and user needs into product requirements, user stories, acceptance criteria, prioritized backlogs, and roadmaps. Partner with business leaders, data scientists, engineers, architects, and product teams to deliver measurable value, improve workflows, champion user experience, and align competing priorities.

Owns product vision and roadmap for Mastercard’s identity and payments data products. Responsibilities include prioritizing product development, creating data-backed business cases, aligning cross-functional stakeholders, defining requirements, managing risks, tracking delivery, representing customer needs, and developing future commercial opportunities. The role also involves mentoring product managers, managing globally distributed teams, and communicating with executive stakeholders.

Lead technical strategy and pre-sales engagement for large enterprise accounts, guiding customers through Databricks adoption and data-driven transformation. Build executive relationships, present technical value propositions, coordinate virtual teams, develop technical champions, align account strategies, and mentor colleagues. The role requires expertise in big data, data science, cloud, ML and AI use cases, plus production programming experience in Python, R, Scala, or Java.

Develop data tools, AI automations, ETL pipelines, dashboards, and machine learning models for payments. Analyze experiments, optimize payment performance and costs, mitigate risk, maintain data systems and cloud infrastructure, and translate business needs into actionable solutions while partnering with Product, Engineering, Finance, and Operations.

Leads and mentors a team of applied machine learning scientists developing predictive AI for regression, classification, and anomaly detection. Provides technical and strategic leadership, designs enterprise-scale AI/ML systems, translates business objectives into scalable solutions, collaborates with engineering and research teams, and ensures governance and regulatory compliance across Canadian Personal Banking.

Develop and validate predictive credit risk models using large retail lending datasets, advanced statistical methods, and machine learning. Build dashboards highlighting expected credit losses and risk drivers, support model validation and compliance, and provide analytical insights to retail risk, finance, and product stakeholders. The role also involves data mining, portfolio segmentation, model documentation, and decision support for lending growth, profitability, and risk management.

Develops and deploys advanced machine learning solutions and enterprise analytics using Python, PySpark, PyTorch, SQL, cloud platforms, deep learning, and large language models. Partners with business owners, engineers, data scientists, and modelers to translate business objectives into technical solutions, generate insights, and deliver production AI/ML systems. Provides technical leadership, stakeholder communication, risk governance, research, mentorship, and continuous improvement across complex initiatives.

Validates retail credit risk, capital, stress-testing, and other financial models. Develops independent statistical and machine-learning benchmarks, evaluates model assumptions and implementation accuracy, documents validation results and limitations, and recommends model approval or improvement. The role also collaborates with model development teams and vendors, monitors evolving regulatory and industry requirements, and supports effective risk-model governance.

Develops and implements IBM z/OS mainframe capacity, availability, and performance strategies. Analyzes workloads, monitors applications and middleware, identifies bottlenecks, and recommends infrastructure, tuning, and optimization solutions. Uses performance monitoring, reporting, visualization, analytics, and capacity-planning tools to maintain SLAs, improve reliability, and reduce operational costs. Collaborates with technical stakeholders, documents solutions, evaluates emerging technologies, and mentors technology teams.

Build and operate scalable full-stack software and AI-powered products for IoT-driven physical operations. Responsibilities include defining technical strategy, developing backend services, APIs, frontend and potentially mobile features, transforming AI capabilities into customer products, partnering across functions, leading complex projects, mentoring engineers, and improving engineering standards.

Develop and maintain ETL processes, SQL Server databases, SSAS data models, SSRS reports, and Power BI dashboards. Build unified data models across ERP systems, improve BI performance, establish development standards, and translate cross-functional business requirements into scalable data and integration solutions. The role also supports modernization of Sofina’s data environment and strategic reporting for finance, sales, supply chain, and other stakeholders.

Leads product design for The Globe and Mail’s digital website and mobile applications. Defines design vision, conducts user research, creates prototypes and interfaces, contributes to design systems and product strategy, and collaborates with product managers, engineers, editorial, and business stakeholders. Mentors designers, leads workshops, validates solutions with users, communicates insights, and designs AI- and machine-learning-enabled experiences.

Leads enterprise AI deployments across contact center and operational functions, managing requirements, vendors, configuration, testing, rollout, performance tracking, governance, and adoption. Coordinates cross-functional technology projects involving IT, Operations, Sales, Training, Field teams, and external partners. Defines KPIs, monitors AI performance, develops business cases, supports change management, and translates data and customer feedback into continuous improvements and new AI use cases.

Develop and operationalize cyber threat intelligence capabilities by collecting, analyzing, and disseminating actionable intelligence. Produce reports, advisories, alerts, briefings, and recommendations for technical and executive audiences. Support incident response and threat hunting, manage intelligence workflows and IOC lifecycles, conduct adversary and trend analysis, and build information-sharing partnerships. Apply AI and machine learning to improve collection, correlation, detection, and early warning while advising security teams on intelligence-driven resilience improvements.

Leads an analytics team responsible for building governed data products, modernizing reporting, standardizing enterprise KPIs, and delivering self-service analytics and executive-ready insights. The role guides data strategy and architecture, manages governance and metadata, partners with business and IT stakeholders, maintains operational reporting, and mentors analysts and developers while using agile delivery practices.

Leads marketing analytics initiatives at the intersection of business, data, and technology. Designs scalable data models, KPI frameworks, analytics engineering solutions, executive dashboards, and self-service BI capabilities using Microsoft Fabric and Power BI. Performs segmentation, forecasting, experimentation, predictive analytics, and marketing performance measurement. Partners with cross-functional and executive stakeholders to modernize analytics, strengthen governance, and deliver actionable insights.

Chief of Staff supporting the Chief AI Officer by managing organizational planning, operating rhythms, budgets, headcount, business reviews, cross-functional dependencies, and strategic initiatives. The role coordinates research, modeling, product, delivery, security, finance, and other teams to ensure priorities are aligned and programs ship effectively. It also leads special projects, facilitates executive communication, resolves ownership and trade-off issues, and represents the AI organization in high-stakes discussions.

Lead the engineering team building Scout, an AI-powered Excel product for creating and updating audit-ready financial models. This player-coach role combines hands-on technical leadership with hiring, mentoring, roadmap ownership, cross-functional collaboration, and operational excellence. The manager will ship reliable client-facing ML/LLM products, establish engineering standards, improve team processes, and build strong relationships with Product, Sales, Customer Success, Support, and financial analysts.

Develop and operationalize cyber threat intelligence capabilities by collecting, analyzing, and disseminating actionable intelligence. Produce reports, advisories, alerts, and briefings; support incident response and threat hunting; manage intelligence processes, IOCs, and TIP governance; and improve intelligence-sharing workflows. Apply AI and machine learning to threat analysis, adversary profiling, IOC generation, and detection workflows while validating accuracy and responsible use. Advise security teams and senior stakeholders on emerging threats, business impact, and mitigation strategies.

Leads enterprise-wide controls, automation, and digital transformation across manufacturing sites. Designs PLC, HMI, DCS, MES, IIoT, analytics, and AI/ML solutions; establishes automation standards; leads capital project workstreams through commissioning; integrates vendors and OT systems; supports cybersecurity, data analysis, training, and technical governance across the network.

Conduct fundamental AI and computer vision research focused on 3D content reconstruction, generation, and editing. Develop state-of-the-art algorithms, design solutions for real-world Huawei products, perform business analysis and solution design, and build rapid research prototypes. Collaborate with research scientists, engineers, and interns, publish findings at leading AI and computer vision conferences, and contribute to large-scale 3D vision and 3D AIGC initiatives.

Leads and develops a software engineering team of 5–6 people, balancing people management with hands-on technical leadership. Responsibilities include reviewing code, guiding architecture, managing integrations, improving development workflows, coaching team members, hiring, and delivering scalable applications on schedule. The role requires collaboration with product, vendors, and cross-functional leaders, along with expertise in C#, .NET, cloud platforms, distributed systems, APIs, databases, DevOps, and secure software development.

Lead data science initiatives supporting Wealthsimple’s Commercial team and AI Voice Agent program. Build reliable data models, develop and maintain machine-learning models, design experiments, conduct analyses, and create dashboards and metrics. Partner with Sales, Operations, Product, Design, Engineering, and leadership to improve sales processes and business outcomes. Mentor teammates and communicate insights to senior stakeholders.

Leads strategy and operations for Global Analytics by managing planning rhythms, priorities, executive forums, portfolio visibility, and cross-functional alignment. Translates complex analytics and AI initiatives into executive narratives, promotes AI product adoption, develops showcases and playbooks, and tracks engagement and business impact. Partners with senior leaders across eBay to drive strategic execution, communicate organizational value, and improve operational effectiveness.