Top Machine Learning Jobs in Toronto

Leads full-stack software engineering across the development lifecycle, owning technical design, architecture, and development of fault-tolerant applications. Establishes engineering standards, improves developer tooling and frameworks, provides technical support, and mentors junior and intermediate engineers. The role uses modern cloud, API, microservices, database, and frontend technologies in a hybrid environment.

Leads Mastercard’s global AI thought leadership strategy by researching AI trends, developing original viewpoints and executive content, managing publication lifecycles, measuring program impact, and partnering with AI, product, marketing, communications, and executive teams. Represents Mastercard at industry events, customer forums, and analyst engagements while translating complex AI topics into compelling business narratives.

Leads data engineering for cyber analytics by designing pipelines, ETL processes, storage, graph databases, and data models. Partners with data scientists and technology teams to integrate ML and AI solutions, manage production deployments, and build cohesive analytical datasets. Oversees and develops a team of data engineers, manages priorities, and collaborates with technical and business stakeholders.

Design, launch, and improve Mastercard’s Responsible AI governance framework. The role integrates governance processes with risk-control tools, partners with business, technical, legal, regulatory, and risk teams, evaluates operations data and stakeholder feedback, manages process-improvement roadmaps, communicates framework changes to leadership, and supports audits. The position requires strong stakeholder management, communication, negotiation, analytical, change-management, and organizational skills, along with knowledge of Responsible AI and AI technologies.

Leads a team developing AI capabilities for CrowdStrike’s cross-platform endpoint sensor. Owns the AI-on-endpoint roadmap, including machine learning model operationalization, telemetry data pipelines, on-device inference, architecture, feature delivery, and cross-functional collaboration. Manages hiring, mentoring, engineering quality, testing, performance, and releases across Windows, macOS, and Linux sensor platforms.

Design and develop AI capabilities for CrowdStrike’s cross-platform endpoint sensor across macOS, Linux, and Windows. Responsibilities include operationalizing machine learning models, building telemetry pipelines for training and inference, integrating features with core OS subsystems, debugging performance and memory issues, and leading architecture, delivery, mentoring, and cross-functional collaboration.

Leads compliance technology oversight for transaction monitoring, sanctions screening, customer risk scoring, and AI-driven case resolution models. Builds AI-powered automation, governance frameworks, human-in-the-loop controls, real-time monitoring dashboards, data-quality controls, and model performance processes. Partners with engineering, machine learning, policy, regulators, and independent monitors to ensure models and data pipelines are explainable, auditable, exam-ready, and aligned with AML requirements across fiat and virtual currency products.

Own the product vision, roadmap, KPIs, and business outcomes for software products. Conduct customer discovery, translate insights into priorities, collaborate with technology, data, strategy, and design teams, and guide technical tradeoffs. Build stakeholder alignment, deliver customer-focused experiences, and use quantitative and qualitative analysis to refine product direction. The role requires at least three years of software product management experience and successful software product delivery.

Lead technical strategy and development of Confluence AI experiences across frontend, backend, and AI integrations. Design scalable systems, apply generative AI, retrieval, agents, evaluation, and safeguards, and improve product quality, adoption, trust, and customer value. Drive complex initiatives from architecture through launch, partner cross-functionally, mentor engineers, establish quality practices, and guide experimentation and continuous improvement across Atlassian.

Lead data science initiatives for agentic AI products, partnering with data scientists, AI/ML engineers, and product managers. Build, deploy, validate, and optimize machine learning models using large-scale numeric and textual data. Design A/B tests, analyze telemetry, translate technical findings into business strategy, research emerging technologies, and develop talent while guiding enterprise-scale AI decisions.

Develop and scale production machine learning models for credit decisioning, including default prediction and approval decisions. Build training, decisioning, monitoring systems, data pipelines, features, and algorithms. Conduct research, develop prototypes, and collaborate with engineering, credit, and product teams to deliver machine learning products from inception through business impact.

Build machine learning, causal inference, optimization, and decision systems supporting customer acquisition, lifecycle engagement, marketing measurement, and conversion. Develop intent, conversion, lifetime value, and marketing allocation models; estimate incremental impact; and translate research into production systems. Partner with Marketing, Product, Engineering, and Sales while owning model evaluation and improvement.

Supports sales, customer success, and product development for Mastercard Identity through data analysis, machine learning, rules-based fraud models, and proof-of-value testing. Advises customers on fraud workflows, analyzes data features, supports API integration QA, and provides product recommendations. Builds customer relationships, translates business needs into technical solutions, contributes to product specifications and training, and serves as a subject matter expert on identity data and products.

Leads end-to-end delivery of digital products and data-enabled solutions for R&D and Innovation. Translates scientific and business needs into technical requirements, architectures, integrations, and scalable solutions. Collaborates with product, data, AI, security, privacy, infrastructure, and vendor teams to manage backlogs, testing, releases, support, and continuous improvement. The role also evaluates responsible AI opportunities, establishes engineering standards, supports adoption, and monitors product performance and user feedback.

Design, build, deploy, and operate production optimization applications powered by machine learning and advanced algorithms. Develop evaluation and testing systems, ensure reliability and observability, and direct AI coding agents through precise specifications and reviews. Collaborate with customers and cross-functional teams to translate business needs into scalable solutions, communicate risks, and influence product direction.

Leads AWS-focused consulting engagements, serving as the primary architect and client-facing technical advisor. Designs and implements enterprise cloud solutions, migrations, service delivery frameworks, and scalable architectures. Guides delivery teams, supports project governance and risk management, contributes to pre-sales scoping and pricing, and ensures successful implementation. Requires extensive AWS architecture and migration experience, multiple AWS certifications, French and English fluency, and willingness to obtain or maintain Canadian Secret clearance eligibility.

Design and analyze experiments, develop statistical and machine learning models, identify patterns in large datasets, build data pipelines, establish product health metrics, and translate insights into decisions. The role partners closely with product, engineering, operations, and other data science teams to improve Lyft payment experiences, payout features, earnings transparency, and platform integrity.

Develops advanced fraud analytics and machine learning solutions using large structured and unstructured datasets. Builds predictive models, identifies patterns and trends, evaluates AI/ML feasibility, and provides data-driven recommendations to business leaders. Partners with product and analytics teams on planning and roadmaps, delivers technical and analytical support, and applies risk management principles to protect the bank.

Leads and develops a data science team, mentors scientists, and oversees production machine learning models for product features and internal business systems. Designs experimentation programs, partners with Engineering, Product, Design, and executives, and drives applied AI initiatives across scheduling, hiring, payroll, pricing, personalization, sales, and marketing.

Leads AI research teams and guides advanced research initiatives from experimentation through production adoption. Evaluates emerging AI methods, oversees rigorous benchmarking and validation, builds academic and internal partnerships, and collaborates with engineering, product, and business teams. The role balances exploratory research with enterprise delivery while advancing responsible, secure, reliable, and scalable AI capabilities. It also influences AI strategy, technical investment decisions, and organizational standards for research excellence.

Supports the governance, risk, and compliance program with a focus on third-party risk management. Conducts vendor assessments, maintains security policies and standards, performs risk analysis, supports SOC 2 audits, gathers evidence, tracks findings, and conducts internal audits. The role also uses AI and machine learning tools to improve GRC processes and promotes security awareness across the organization.

Delivers technical consulting for utility-scale wind projects, including wind resource and energy production assessments, SCADA analysis, remote sensing, wake loss, site suitability, performance, uncertainty, and risk studies. Prepares technical reports and client deliverables, supports project teams and customer discussions, mentors colleagues, and develops automation and AI-enabled analytical tools. The role is hybrid in Montreal, Toronto, or Calgary and requires up to 10% domestic travel.

Lead wind energy assessments and performance analyses for utility-scale renewable projects. Analyze SCADA, meteorological, geospatial, and operational datasets; develop Python, MATLAB, or R tools and automated workflows; evaluate energy production, uncertainty, losses, and risks; provide technical consulting, peer review, customer support, and mentoring; and advance AI, data management, visualization, and analytical methodologies.

Leads the architecture, development, and maintenance of data pipelines, reporting frameworks, dashboards, and AI-enhanced analytics solutions. Analyzes complex datasets, delivers strategic insights to senior stakeholders, establishes data governance standards, mentors team members, and guides technical reporting initiatives from conception through deployment.

Leads Vanguard Canada's digital marketing strategy across paid, owned, and earned channels. Oversees customer acquisition, engagement, retention, personalization, analytics, marketing technology, paid media budgets, agency partnerships, and regulatory-compliant communications. Builds integrated digital experiences for investors and advisors, partners with data and technology teams, evaluates emerging AI and marketing solutions, and develops a high-performing digital marketing team.