Top Python Jobs in Toronto

Build backend data and measurement systems connecting marketing acquisition activity to signup, conversion, and GMV outcomes. Develop reliable pipelines, identity and event data systems, attribution capabilities, and marketing technology integrations while incorporating privacy, consent, and consumer-data requirements. Lead engineers through ambiguous problems, own quarterly goals, improve system reliability and code quality, collaborate cross-functionally, and mentor team members.

Lead the design, scalability, reliability, and optimization of continuous integration systems, build pipelines, automated testing, deployment workflows, and developer productivity tooling. Improve feedback cycles, monitoring, alerting, incident response, and engineering enablement across the organization. Mentor CI engineers, establish CI/CD best practices, and align developer infrastructure with broader platform goals.

Develop and deliver full-stack web and mobile application experiences across Affirm’s consumer products. Responsibilities include breaking projects into tasks, collaborating with product, design, and analytics teams, building and maintaining APIs and user interfaces, monitoring application availability, participating in on-call support, conducting code reviews, debugging, and contributing to interviews and team development.

Build and ship full-stack web applications and scalable APIs for Affirm’s advertising platform. Break projects into deliverable phases, collaborate with product, design, and analytics partners, write tested and extensible code, monitor service metrics, support on-call operations, review code, and contribute to engineering growth and hiring activities.

Lead the AI Quality engineering team while remaining hands-on building evaluation infrastructure, observability tooling, diagnostic systems, datasets, annotation workflows, and CI/CD pipelines for production AI agents. Run experiments across prompts, models, routing, caching, and agent harnesses to improve quality, latency, and cost. Partner with AI Core engineering and manage technical direction and team priorities.

Develop backend tools and systems that improve batch development, testing, and reliability. Responsibilities include breaking projects into deliverable phases, collaborating with product and infrastructure teams, monitoring system metrics, supporting on-call operations, writing tested and extensible code, debugging, participating in code reviews, and contributing to engineering growth activities.

Build and launch scalable backend systems and APIs for Affirm’s partner and merchant integrations. Responsibilities include breaking projects into deliverable phases, collaborating with product, design, and analytics teams, monitoring service health, participating in on-call operations, debugging code, conducting code reviews, and supporting team development. The role requires backend development experience with Python or Kotlin, distributed systems knowledge, and familiarity with AWS, MySQL, and Kubernetes.

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.

Lead product data engineering across architecture, data modeling, pipelines, monitoring, lineage, and data quality. Build reliable analytical datasets, support experimentation and machine learning use cases, and resolve business-critical pipeline issues. Partner with product and engineering stakeholders to translate business needs into automated data solutions. The role requires ownership of end-to-end data engineering projects, on-call participation, and development of AI-assisted monitoring and automation.

Lead product data engineering initiatives by designing data models, owning critical pipelines, building data quality and lineage monitoring, and supporting experimentation and ML-ready datasets. Translate business needs into automated data solutions, maintain pipeline SLAs through on-call support, and develop AI-assisted tools for issue detection and resolution. Collaborate with Product, Engineering, Data Science, Machine Learning, and Applied AI teams across Block’s products.

Lead the evaluation, training, fine-tuning, and production integration of machine learning and large language models. Build prompt engineering and model evaluation pipelines, optimize Elasticsearch-backed AI workflows, benchmark commercial and open-source models, and monitor production performance. Collaborate with product, engineering, and security teams to deliver safe, scalable AI capabilities while identifying improvements to data pipelines and engineering processes.

Build and scale Affirm’s managed cache platform using Redis and Valkey. Responsibilities include cluster migrations, capacity and shard planning, failover and replication, upgrades, self-service automation, monitoring, SLOs, incident response, and advising teams on caching strategy. The role also involves designing tested backend systems, collaborating across engineering and product teams, participating in on-call operations, and contributing to code reviews and team development.

Manage the AMER Support Engineering team, including hiring, mentorship, performance development, and technical growth. Lead customer support quality, process improvement, automation, AI adoption, and cross-functional collaboration. Build scalable workflows, promote team ownership and psychological safety, and ensure Support Engineers resolve complex technical issues throughout the support lifecycle. Partner with product and development teams to improve customer outcomes and support efficiency.

Lead hardware and embedded security for Motive devices: establish secure-by-default baselines (boot chain, firmware, FOTA, manufacturing), perform threat modeling and architecture reviews, define security requirements, drive remediation with hardware teams, and build scalable security components and automation across device lifecycle and cloud-connected infrastructure.

Designs and positions telecom analytics solutions for network visibility, service assurance, customer experience, and operational intelligence. Responsibilities include architecting end-to-end data pipelines, applying 4G, 5G, and IMS expertise, integrating probe data and telemetry, enabling AI/ML and Generative AI use cases, and advising engineering and delivery teams. The role also develops reusable architecture patterns, manages solution risks, and supports cloud-native, real-time, and operational analytics implementations.

Designs, builds, and maintains AI-powered developer tools and applications across frontend, backend, APIs, cloud infrastructure, LLM features, agentic workflows, and MCP-based services. The role establishes technical vision, architects scalable systems, reviews code and technical plans, improves platform reliability and AI capabilities, supports production integrations, and collaborates with product, design, engineering, and game development teams.

Develop AI-driven mobile game prototypes and reinvent art production pipelines. Build tools and automation, integrate 2D, 3D, animation, and UI assets, optimize workflows for mobile, collaborate across art and programming teams, and document best practices. The role requires technical artist experience, AI-assisted development, Unity or web prototyping, scripting, and strong understanding of game asset pipelines.

Designs and leads scalable AI systems, full-stack applications, cloud infrastructure, LLM-powered services, and agentic workflows across Zynga’s game studios. Owns architecture strategy, evaluates AI platforms, establishes engineering standards, drives reliability and quality practices, collaborates with stakeholders, manages technical risk, and mentors engineers. Requires strong Python, cloud, Kubernetes, database, algorithms, and AI/ML integration expertise.

Supports identity and access management, troubleshoots internal business systems, resolves technical tickets, validates system functionality, manages engineering escalations, supports critical incidents, automates workflows, and documents resolutions. The role works across Salesforce, Amazon Connect, Okta, Jira, and other tools while partnering with support, product, and engineering teams to improve system reliability and user experience.

Supports identity and access management, troubleshoots technical issues across Salesforce, Amazon Connect, Okta, and internal systems, and resolves tickets for internal support teams. The role validates system functionality, manages Jira escalations, partners with engineering during incidents, automates workflows, documents solutions, and identifies recurring issues for systemic improvement. It requires strong technical troubleshooting, communication, organization, and the ability to interpret code, logs, and system configurations.

Design and build backend APIs, microservices, and checkout platform components for Affirm’s financial products. Improve system performance, reliability, tooling, and engineering standards while collaborating across teams. Own components over their lifecycle, contribute to technical decisions, ship high-quality software at scale, and support peer development through communication and knowledge sharing.

Lead Data Scientist analyzing global fraud data to identify patterns, develop predictive models, and prevent payment fraud. The role builds fraud-related products and services, extracts insights from large datasets, collaborates with stakeholders, and presents findings to management and clients. Required skills include Python, Spark, complex data queries, and advanced data analysis. Experience with agentic AI systems and Unix is preferred, along with payments or fraud expertise.

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.

Build and scale first-line risk control monitoring systems using statistical analysis, automated workflows, and reusable data science modules. Define risk metrics, investigate control performance, establish thresholds and guardrails, and translate analyses into monitoring applications. Partner with risk, compliance, product, and engineering teams to improve governance, identify monitoring gaps, and support decision-making. Lead ambiguous, cross-functional initiatives while communicating findings, limitations, and recommendations to technical and executive stakeholders.

Build and scale first-line risk control performance monitoring for financial products. Develop metrics, key risk indicators, statistical baselines, thresholds, automated workflows, and reusable analytical modules. Partner with risk, compliance, product, and engineering teams to improve governance, identify monitoring gaps, evaluate control effectiveness, and support decisions. Lead ambiguous initiatives from definition through adoption while communicating findings, limitations, and recommendations to technical and executive stakeholders.