Top Machine Learning Jobs in Toronto

Build trusted technical relationships with enterprise customers, troubleshoot Samsara hardware, software, APIs, and AI solutions, and optimize implementations. Serve as the primary technical contact, manage incident communications, identify growth opportunities, maintain account records, and collaborate across stakeholders. The role also supports Technical Account Management team development and requires occasional customer travel plus after-hours or weekend coverage when needed.

Lead the Fraud and Ad Quality product portfolio, defining strategy, roadmap, go-to-market, and execution for ad fraud detection, invalid traffic measurement, and content quality solutions. Partner with Engineering, Data Science, Business Development, Commercial, and Product Marketing teams to guide architecture, prioritize initiatives, drive adoption, and deliver innovative ML/AI-enabled products for digital advertising customers.

Develop AI-enabled solutions for market surveillance, including alert investigation, trading-pattern analysis, anomaly detection, evidence gathering, and exception handling. Apply Python, SQL, machine learning, and LLM technologies to order, trade, and market data. Collaborate with compliance, surveillance, and technology stakeholders to translate operational requirements into scalable analytical and workflow solutions supporting trading compliance and market-abuse detection across equities and derivatives.

Leads multiple software engineering teams building scalable, resilient applications that reduce fraud and improve customer experience. Responsibilities include people leadership, talent and succession planning, engineering craftsmanship, application availability, resilience, scalability, hands-on development, technology experimentation, and mentoring. The role also influences product and business stakeholders on strategy and roadmaps.

Leads the teams developing Samsara Assistant, Agent Studio, and agent extensibility. Manages approximately 10 machine learning engineers, applied scientists, and full-stack engineers through two tech leads. Owns product activation, answer quality, repeat usage, technical direction, agent platform frameworks, cross-functional partner adoption, and team hiring and development. The role combines AI product leadership, software engineering, platform strategy, and customer-focused growth for production agentic systems.

Leads and grows software engineering teams, including hiring, coaching, performance management, and career development. Defines technical strategy and roadmaps for backend, frontend, mobile, API, and AI-powered products. Oversees architecture, design reviews, cross-functional delivery, and production systems at scale while translating ambiguous customer problems into measurable outcomes. Partners with product, design, and customer teams and raises engineering quality, velocity, and organizational standards.

Distinguished Engineer responsible for defining technical vision, architecting scalable cloud solutions, ensuring engineering quality, and solving complex system problems. The role provides cross-organizational technical leadership across software engineering, architecture, networking, and cloud platforms. Responsibilities include mentoring engineers, influencing technology standards, contributing hands-on code and designs, advising on system performance and operability, and driving innovation for Capital One’s business travel and expense platforms.

Lead the design and implementation of AI products for edge devices, optimizing machine learning models under edge-compute constraints. Work with petabyte-scale sensor, video, text, diagnostic, transaction, and location data; collaborate with ML, firmware, hardware, and full-stack engineers; prototype new AI experiences; ship production systems at scale; and mentor ML engineers.

Own the strategy, roadmap, and results for AI-powered marketing products, including discovery, content, campaigns, websites, email, social, and attribution. Lead cross-functional collaboration with engineering, design, AI/ML, client success, and sales. Run customer betas, improve product quality, drive adoption and retention, build business cases, and connect marketing channels to measurable revenue outcomes.

Lead and grow a founding engineering team building an AI orchestration platform for real-time, high-volume messaging decisions. Define architecture, guide distributed systems development, drive initiatives from prototype to production, and partner with product, machine learning, data platform, and engineering teams. Ensure reliability through observability, incident response, testing, CI/CD, and on-call practices while remaining hands-on with system design and implementation.

Leads GitLab’s Product, Sales, and Finance Data Science teams, managing managers and a 12-person organization. Sets data science standards, prioritizes investments, partners with executives, drives product adoption and revenue growth, and oversees experimentation, causal inference, predictive modeling, and AI initiatives. Develops talent, builds succession, and collaborates with Analytics Engineering and Data Engineering on a shared data and AI roadmap.

Owns quality assurance for cryptocurrency and sanctions compliance programs, including sampling, decision reviews, metrics, risk reporting, corrective actions, and continuous improvement. Partners with BSA/CFT and Sanctions program owners and leadership to ensure compliance standards align with regulatory requirements and product growth. Requires deep AML, KYC, sanctions, and fintech compliance expertise, strong analytical and communication skills, executive influence, and AI fluency.

Build and improve Confluence AI experiences across frontend, backend, and AI integrations. Own features from design through launch, apply generative AI, retrieval, agents, and evaluation techniques, create automated quality testing, monitor production performance, run adoption experiments, and collaborate cross-functionally. Mentor engineers and contribute to architecture, observability, testing, safeguards, and scalable software delivery.

Lead full-cycle recruitment for specialized AI and machine learning roles across Canada. Build talent pipelines, partner with engineering and research leaders, provide talent market intelligence, optimize recruiting metrics and processes, and close highly sought-after technical candidates. The role requires advanced sourcing expertise, Canadian technology market knowledge, compensation negotiation skills, and strategic partnership with senior technical stakeholders.

Leads AI transformation, governance, quality oversight, risk management, and responsible adoption across Pfizer Global Supply and QSEO. Establishes GxP-compliant AI lifecycle practices, inspection-readiness frameworks, governance forums, portfolio monitoring, inventory management, metrics, and reporting. Advises senior leaders on AI regulations, deployment risks, investment priorities, and compliance while leading cross-functional initiatives and influencing stakeholders across Quality, Digital, Operations, and R&D.

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 GitLab’s Product Data Science team, setting its strategy, roadmap, analytical standards, and priorities. Partners with Product and Engineering leaders on experimentation, causal inference, analytics, and production modeling. Manages, hires, coaches, and retains data scientists while building a high-performing function. Provides hands-on technical review of models, analyses, and queries, and communicates insights and risks to senior leaders.

The Data Scientist will partner with Sales, Revenue Operations, and Finance to analyze GTM performance, build and productionize machine learning models, conduct experiments, forecast outcomes, and identify growth opportunities. Responsibilities include statistical analysis, causal inference, Python and SQL development, MLOps, agentic workflow automation, semantic-layer contributions, executive reporting, and communicating insights to nontechnical stakeholders in a fully remote environment.

Own company-critical technical problems and long-term strategy across multiple organizations. Architect scalable customer-facing systems and platforms, remain hands-on in software development, influence senior product and engineering leaders, establish engineering standards, and drive responsible AI adoption in products and workflows. The role requires deep expertise in large-scale software systems, consumer products, distributed systems, and production ML and LLM applications.

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 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 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.

Drives new and expansion revenue among small and medium-sized business fleet customers. Responsibilities include prospecting, qualifying leads, conducting discovery conversations, delivering product demonstrations, managing opportunities in Salesforce and Salesloft, using partner and referral programs, and collaborating with revenue operations, marketing, and account teams. The role requires strong communication, organization, sales aptitude, customer relationship skills, and interest in developing expertise in telematics and fleet management.

Develops and maintains enterprise AI security strategy, architecture, governance, standards, and roadmaps. Designs secure patterns for AI applications, models, data pipelines, infrastructure, APIs, LLMs, RAG solutions, and AI agents. Assesses AI-specific threats, supports architecture reviews and vendor evaluations, and partners with technology, risk, legal, compliance, and security teams. Provides guidance on identity, access controls, encryption, monitoring, incident response, responsible AI, and regulatory compliance while educating teams on secure AI practices.