Top Python Jobs in Toronto

Designs and maintains reliable data pipelines and computed tables using SparkSQL and PySpark. Integrates IoT, product, customer, external, unstructured, and ML-related data into scalable data models supporting analytics, causal inference, model training, and dashboards. The role requires ETL development, data orchestration, API integration, strong data quality and uptime, and collaboration with Data Science, AI/ML, Analytics, and engineering teams. This is a remote position for candidates residing in Canada.

Leads technical go-to-market activities for enterprise customers, including discovery, architecture design, technical validation, demonstrations, proofs of concept, onboarding oversight, adoption, and expansion. Acts as a trusted technical advisor across the customer lifecycle while carrying revenue quota. Designs migration and deployment strategies, resolves technical objections, leads executive reviews, automates workflows with AI, and develops technical enablement resources.

Serve as a quota-carrying technical advisor for enterprise customers throughout pre-sales validation, onboarding, deployment architecture, adoption, renewal, and expansion. Design Cloudflare network and security solutions, lead technical discovery, demonstrations, proofs of concept, migration blueprints, QBRs, and executive engagements. Translate technical capabilities into business value, identify risks and expansion opportunities, and automate workflows using AI, LLMs, scripting, and internal platforms. Travel up to 20–50% may be required.

Build and scale backend-focused software for Braze’s petabyte-scale Data Lakehouse. Develop data pipelines, asynchronous processing, ETL applications, and end-to-end features across platforms such as Snowflake, ClickHouse, and Databricks. Drive architectural decisions, contribute to technical strategy, and deliver scalable web applications handling high volumes of data and traffic in an agile environment.

Build and maintain backend-focused, end-to-end software for Braze’s petabyte-scale Data Lakehouse platform. Develop infrastructure and tools supporting Snowflake, ClickHouse, and Databricks, manage high-volume event data, and deliver front-end experiences when needed. Collaborate across teams, apply strong software design and algorithms knowledge, and help scale systems handling billions of daily rows and significant customer and internal workloads.

Serves as a quota-carrying technical advisor for enterprise customers throughout the full sales and adoption lifecycle. Leads technical discovery, architecture design, proofs of concept, presentations, onboarding blueprints, deployment guidance, QBRs, and expansion strategy. Partners with account executives and customer engineering teams to translate Cloudflare’s networking, security, performance, and developer platform capabilities into business outcomes. Uses AI and automation to streamline technical workflows, while creating enablement materials and managing integration risks.

Architect, build, and optimize BuildOps’ full-stack platform using React.js, Node.js, GraphQL, REST, and SQL. Lead technical decisions, API and database optimization, observability, testing, cloud infrastructure, and event-driven architecture. Mentor engineers, establish engineering best practices, guide cross-team technical initiatives, and collaborate with product, QA, customers, and partners to deliver reliable, scalable software.

Lead technical presales engagements for HPE Mist campus and branch networking solutions. Partner with sales teams on discovery, architecture, demonstrations, proof-of-concept projects, competitive positioning, and customer adoption. Configure and troubleshoot wireless, wired, WAN, access control, cloud management, automation, and AI-driven networking solutions. Advise executives and technical stakeholders, enable partners and internal teams, and coordinate with Customer Success, Support, Product Management, and Engineering. Travel may be required up to 50%.

Test and validate AI models and software for automotive use cases: generate ground truth, build annotated datasets and testing frameworks, evaluate technologies, support R&D engineers, coordinate projects and outsourced work, and collaborate with internal and external partners to drive innovation and product readiness.

Build and scale reliable Snowflake data pipelines, ML pipelines, monitoring systems, and AI-driven agentic tooling that automates pipeline generation, testing, and maintenance. The role partners with analysts, data scientists, product teams, and analytics engineers to deliver scalable end-to-end data infrastructure for Babylist’s e-commerce platform.

Lead complex security incident investigations from assessment through recovery, coordinating containment, remediation, evidence preservation, and stakeholder communication. Analyze threats across endpoint, identity, cloud, SaaS, network, and application environments. Build code, queries, automation, and AI-assisted workflows to improve evidence collection, detection, case management, and response. Lead post-incident reviews, drive lasting improvements, mentor responders, and participate in the incident response on-call rotation.

Design and maintain data architecture and pipelines to support compliance and risk teams. Build and optimize data models, standardize metrics, and create data dictionaries. Implement data quality, lineage monitoring, AI-driven agents for false-positive reduction and automation, and participate in on-call rotations to ensure SLAs are met.

Lead design and optimization of data models and pipelines for compliance and risk; standardize metrics and documentation; build data quality, lineage, and monitoring (including AI agents for automation); manage ETL scheduling, on-call pipeline support, and collaborate with product and non-technical partners to translate business needs into automated, production-ready data solutions.

Design, develop, deploy, and maintain full-stack agentic AI applications from concept through production. Responsibilities include agent orchestration, data and tool integration, MCP server connectivity, frontend UI/UX development, cloud deployment, engineering-process analysis, technology evaluation, testing, validation, documentation, and innovation project coordination. The role collaborates with R&D teams and internal customers to create reliable AI solutions that improve efficiency, quality, and scalability.

Lead the design, development, and technical strategy for high-availability financial services supporting Affirm’s card loan platform. Build scalable APIs, data models, microservices, and event-driven systems; troubleshoot performance and reliability issues; collaborate cross-functionally on loan attribution and lifecycle requirements; and mentor engineers through technical guidance, design reviews, and code reviews.

Own the direction and implementation of Babylist’s personalization domain, including recommendation, search, feed models, custom embeddings, and shared representations. Take ambiguous problems from concept through production, owning architecture, deployment, monitoring, retraining, evaluation, and customer impact. Partner with product, design, and data, establish AI development standards, make cross-team technical decisions, and coach senior engineers while remaining hands-on with complex machine learning systems.

Leads the technical design and development of fault-tolerant, cross-functional full-stack applications for Capital One’s travel portal. Builds front-end and back-end systems, contributes to architecture and high-level design, establishes engineering standards, improves developer tools and experience, provides technical support, and mentors junior and intermediate engineers. Collaborates throughout the software development lifecycle in an agile, hybrid work environment.

Own third-party risk management and business continuity programs while building production data pipelines, integrations, policy-as-code controls, continuous monitoring, and agentic AI workflows. The role requires defining technical direction, integrating imperfect data sources, automating evidence collection, and partnering across Security, Procurement, Resilience, and Engineering teams to improve governance and operational resilience.

Analyze player behavior, product performance, revenue, retention, and engagement for Zynga Poker. Design experiments, dashboards, ETL pipelines, telemetry, fraud models, and business intelligence solutions. Partner with product, game design, economy, and consumer insights teams to guide decisions and improve player experiences. Contribute to AI-enabled analytics workflows, game integrity initiatives, and analytics best practices.

Provides technical support for production radiology systems, responding to time-sensitive customer incidents, troubleshooting Windows, networking, hardware, storage, and database issues, documenting cases, managing a 20–30 ticket backlog, and coordinating with internal technical and business teams. The role is remote within Canada, requires weekday shifts and an on-call rotation, and supports systems that may affect patient care.

Owns end-to-end DevOps, cloud infrastructure, CI/CD, Kubernetes, Infrastructure as Code, monitoring, security, reliability, and production operations. The role designs automated deployment processes, manages cloud environments, troubleshoots complex infrastructure and networking issues, implements observability and disaster recovery, optimizes cloud costs, and guides engineering teams on secure, scalable DevOps practices.

Build and scale AI-enabled developer experience, CI/CD, deployment safeguards, observability, and automated response systems. The role focuses on making software delivery autonomous, safe, reliable, and easier for engineering teams to adopt. Responsibilities include architecting enterprise-scale platforms, orchestrating AI agents, reducing technical debt and operational toil, partnering with product engineering teams, and establishing AI-native SDLC workflows. The engineer will also provide technical leadership and turn emerging AI capabilities into production-ready internal platforms.

Build and improve test infrastructure, automation frameworks, CI/CD pipelines, and end-to-end testing strategies. Lead quality initiatives, develop AI-augmented testing solutions, monitor test environments, support incident resolution, and use quality and performance metrics to improve software reliability. Collaborate with Infrastructure, SRE, engineering leaders, and product teams in an agile environment to expand test coverage and enable safe, efficient delivery.

Graduate research interns will own end-to-end projects to build customer world models and proactive intelligence: developing representation learning, foundation model, RL/agentic methods, evaluation frameworks, and shipping research into production to improve customer decision-making.

Develop and scale backend streaming and data infrastructure using technologies such as Kafka, Flink, AWS, and Kubernetes. Design, launch, test, and maintain distributed systems, monitor service availability, participate in on-call support, collaborate with product and engineering stakeholders, review code, and contribute to technical planning and team development.