Top Python Jobs in Toronto

Lead hardware and embedded security across Motive devices, including secure boot, firmware, FOTA, manufacturing, threat modeling, architecture reviews, and lifecycle risk management. Partner with hardware and engineering teams to define security requirements, validate controls, remediate findings, and build secure-by-default components. Address hardware, IoT, cloud, runtime, supply chain, and application security across device lifecycles.

Build and operate secure, resilient distributed systems for secrets and key management across Cloudflare’s global network. Re-architect internal PKI and machine or workload identity systems, participate in on-call incident response, support internal developers, and advise engineering teams on secure system design. The role requires software development, distributed systems expertise, Linux/UNIX administration, and hands-on security implementation experience.

Build and maintain network edge security systems that improve API security posture, detect and mitigate abusive traffic, and respond to emerging threats. Responsibilities include developing streaming analytics pipelines, integrating CDN and security vendors, managing production systems, contributing to machine learning models, and implementing AI-driven traffic classification. The role requires software or security engineering experience, expertise in Java, Kotlin, TypeScript, Python, SQL, Spark, CDN platforms, and AWS.

Own and improve Dropbox’s Windows endpoint platform, including provisioning, application delivery, patching, security configuration, compliance, troubleshooting, and fleet health reporting. Build reliable PowerShell and systems automation, advance code-managed endpoint operations using tools such as Intune, FleetDM, osquery, infrastructure-as-code, and GitOps, and lead cross-functional platform improvements. Mentor engineers, review code and designs, document practices, and deliver multi-phase reliability initiatives.

Leads the design, development, and optimization of scalable data architectures, ETL pipelines, ingestion frameworks, data quality processes, governance practices, and audit systems. Partners with cross-functional teams to translate requirements into data solutions, analyzes data for business insights, communicates recommendations, and mentors Data Engineers. The role also serves as a technical authority and supports continuous improvement across data engineering practices.

Build Apollo’s AI-powered Builder Studio end to end, including chat-driven app creation, live previews, generated-app runtimes, workflows, integrations, delegated permissions, security, and reliability. The role requires strong full-stack development, production LLM experience, frontend expertise with complex UIs, backend and workflow design, and ownership of an ambiguous 0-to-1 product.

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 and deploy AI-powered solutions for enterprise and campus customers. Scope customer environments, prototype agentic AI solutions, design secure multi-tenant and hybrid architectures, and productionize validated solutions. Responsibilities include backend engineering, cloud infrastructure, data engineering, IAM, encryption, secure networking, CI/CD, observability, and production support. The role is highly customer-facing, involving executive discovery, live demonstrations, go-live support, and regular domestic and occasional international travel.

Develop and ship web, mobile, and API features for Affirm’s card acquisition experience. Break projects into deliverable phases, collaborate with product, design, and analytics, write tested and extensible code, support production availability through metrics and on-call activities, review code, and contribute to interviewing and team development.

The Data Engineer will develop and maintain data pipelines, ensure data quality, and collaborate with business teams to implement insightful data solutions.

Contribute to fullstack search engineering projects, developing and launching scalable backend systems and user-facing solutions. Collaborate with teammates and stakeholders, balance speed and quality, protect system reliability, navigate large codebases, debug code, participate in reviews, and communicate effectively. The role supports growth through feedback and development activities.

Build, maintain, and execute automated functional, integration, and regression tests using SmartBear TestComplete, ReadyAPI, and Playwright. Test Java Spring applications across Linux and Windows environments, validate relational database data, investigate defects, maintain test assets, and collaborate with developers throughout the Agile lifecycle to support reliable application modernization and releases.

Modernize legacy Unix/Linux applications and scripts through refactoring, automation, containerization, and cloud migration. Develop automation with Bash, PowerShell, Python, and Groovy; deploy applications using Docker, OpenShift, Kubernetes, and AWS; and troubleshoot across Linux and Windows environments. Support application modernization involving JBoss, Tomcat, Nginx, HAProxy, and legacy Java applications while collaborating with development and technology teams on enterprise migration initiatives.

Lead the technical direction, architecture, and development of Compass, an LLM-powered agent platform. Design multi-agent systems, MCP and A2A integrations, orchestration, evaluation, and observability infrastructure. Drive cross-team technical projects, production support, engineering quality, mentoring, and adoption of AI-assisted development practices. Partner with Product, QA, Design, Operations, and Engineering stakeholders to deliver reliable agentic systems.

Build and maintain authentication and fine-grained authorization systems using Auth0 and OpenFGA. Own OAuth 2.0 and OpenID Connect implementations, identity federation, token flows, and permissions for AI agents. Lead cross-team technical projects, set engineering standards, review code, and mentor engineers. The role requires strong backend development skills and experience with identity providers, ReBAC systems, and complex multi-tenant authorization models.

Own the operational health of strategic merchant integrations through monitoring, troubleshooting, SLA delivery, root-cause analysis, and technical inquiry resolution. Design custom API integration solutions, lead cross-functional technical initiatives, influence product roadmaps, develop playbooks and runbooks, manage strategic accounts, and mentor other Technical Account Managers.

Architect and own marketing data infrastructure, including Databricks pipelines, Gold Layer tables, semantic models, and trusted analytics foundations. Lead cross-functional data initiatives, translate ambiguous business needs into scalable solutions, improve reliability and quality, and mentor engineers. Build and monitor production LLM and agent systems, automate workflows with AI, and deliver high-quality Python and SQL while validating AI-generated code. Partner with Marketing, Sales, BI, Data Science, and R&D teams.

Lead design, build, and deploy of large-scale data platforms for LLMs, RAG, and agentic AI systems. Hands-on coding, architecting fault-tolerant pipelines, establishing MLOps/DataOps best practices, mentoring engineers, and operationalizing research into production across Exabyte-scale distributed systems.

Lead backend engineering work for Affirm’s lakehouse infrastructure, delivering reliable, scalable distributed data systems. Own quarterly goals, guide engineers through ambiguous problems, collaborate with product and analytics stakeholders, improve technical standards, monitor system availability, support on-call operations, and mentor team members. The role focuses on large-scale data platforms and technologies including Iceberg, Flink, Airflow, Spark, Kafka, Snowflake, AWS, MySQL, Kubernetes, and Terraform.

Designs and builds secure, scalable systems protecting products, infrastructure, and customer data. Responsibilities include authentication and OAuth integrations, authorization platforms, BYOK capabilities, security tooling, cloud security controls, threat modeling, vulnerability remediation, and security testing. The role partners with engineering and product teams, establishes secure development practices, leads complex security projects, and mentors engineers.

Leads enterprise data quality and governance initiatives, including data profiling, validation, cleansing, monitoring, metadata management, cataloging, lineage, classification, and data protection. Partners with business stakeholders, data owners, engineering, architecture, analytics, and security teams to define quality standards, remediate issues, improve governance-platform adoption, and establish data sensitivity controls. Provides technical leadership across global data environments and supports AI-enabled classification and responsible data use.

Graduate research co-op focused on building Customer World Models and proactive intelligence: designing representation learning, foundation-model, reinforcement learning, and agentic systems; running experiments, publishing, and deploying research into production to improve long-horizon decision-making and customer-facing automation.

Build GitLab code security capabilities spanning dependency analysis, SBOM and lockfile parsing, vulnerability detection, AI-assisted analyzers, and automated dependency remediation. Design evaluation harnesses, package analyzers for CI and AI workflows, improve security report accuracy, and extend ecosystem coverage. Own initiatives from design through delivery, mentor engineers, collaborate across product and engineering teams, document systems, and participate in on-call support.

Graduate research internship to own end-to-end research on Customer World Models and proactive intelligence: design representations, develop methods (foundation models, RL, causal reasoning, agentic systems), run experiments, publish, and help ship ML systems that anticipate and act on customer needs.

Lead engineering for AI voice-agent experiences used by drivers. Define product and technical direction, build full-stack services, design agent coordination and memory systems, establish APIs and service boundaries, and evaluate AI behavior in production. Mentor engineers, document architectural tradeoffs, and introduce AI-assisted engineering practices using tools such as Codex, Claude Code, and Cursor.