Top Python Jobs in Toronto

Leads Gore Mutual’s data science function, managing teams that develop, deploy, validate, and govern predictive, generative AI, LLM, and agentic solutions. Sets the analytics and AI strategy, oversees production ML infrastructure and model monitoring, ensures regulatory, ethical, privacy, and risk compliance, and identifies opportunities to improve underwriting, fraud detection, pricing, operations, and business growth. Partners with executives and cross-functional teams to translate analytical findings into strategic outcomes while fostering innovation, experimentation, and advanced data science capabilities.

Develop and maintain behavior-planning systems for autonomous vehicles operating in structured, low-speed airport environments. Responsibilities include designing planning algorithms, implementing scalable C++ and Python software, modeling multi-agent interactions, testing in simulation and real-world scenarios, optimizing performance and latency, documenting system designs, and collaborating with autonomy and engineering teams.

Own end-to-end data science and machine learning projects, including problem definition, statistical analysis, predictive modeling, deployment, monitoring, and production data pipelines. Translate business questions into measurable KPIs and actionable insights for Product, Sales, Marketing, Finance, and HR. Build maintainable code and communicate findings to technical and non-technical stakeholders while contributing to code reviews, shared tooling, documentation, and team mentorship.

Lead presales architecture engagements spanning Azure infrastructure and networking, Microsoft AI, Fabric, data modernization, security, and managed services. Run discovery workshops, design and scope solutions, build proposals, estimates, pricing models, SOWs, proofs of concept, and executive presentations. Partner with sales, SMEs, and delivery teams to advance opportunities, ensure feasible handoffs, support RFPs, and develop reusable assets. Advise clients on cloud strategy, AI adoption, governance, responsible AI, and production readiness.

Build and operate production AI systems for go-to-market teams, including account segmentation, scoring, enrichment, buying-signal detection, agentic workflows, prospect research, outbound personalization, call summarization, and CRM hygiene. Own solutions end to end from design through deployment, while optimizing quality, latency, cost, reliability, evaluation, monitoring, and guardrails. Collaborate closely with Marketing, Sales, RevOps, and system users to deliver measurable commercial impact.

Leads enterprise AI and data architecture strategy, defining target architectures, standards, governance, roadmaps, and infrastructure requirements. Designs end-to-end AI solutions spanning data pipelines, model training, deployment, and monitoring. Advises business and technology stakeholders, evaluates emerging technologies, ensures regulatory and architectural compliance, manages risks, presents recommendations to leadership, and mentors technical teams. Requires extensive experience in AI/ML architecture, data engineering, cloud platforms, MLOps, and enterprise technology strategy.

Executes hardware verification testing for pre-production products, develops automated test systems using Python and SCPI, evaluates communication signals and environmental performance, modifies prototype hardware, supports schematic and PCB layout, performs SMT assembly, and documents results. Collaborates with design, firmware, manufacturing, and test-fixture teams to identify root causes, communicate risks, and improve product reliability and regulatory readiness.

Lead end-to-end client analytics projects, analyzing large datasets with SQL and Python, developing dashboards in Power BI and Tableau, applying advanced statistical and machine learning techniques, and translating findings into actionable marketing, customer, and loyalty strategy recommendations. Present insights to technical and non-technical stakeholders, collaborate with consultants and managers, and support junior analysts.

Leads client analytics engagements, owns analytics roadmaps, manages project scope and quality, and presents actionable insights to senior stakeholders. Develops advanced models including customer lifetime value, segmentation, propensity, forecasting, and attribution. Manages and mentors analysts and consultants, supports business development and account growth, and oversees reporting, performance monitoring, resourcing, and utilization.

Develop and maintain cloud-based IoT applications for manufacturing. Design secure, scalable full-stack solutions, APIs, data integrations and pipelines. Collaborate with architects, product owners, developers, and stakeholders; follow DevOps and agile practices; mentor team members and troubleshoot production issues.

Design, build, and manage Canadian sovereign and global cloud infrastructure using code. Automate provisioning (Terraform, Crossplane), develop services in Go/Python, onboard services, operate Kubernetes, use Puppet/Ansible, and collaborate with SRE, networking, and system administration to ensure secure, scalable environments.

The Senior Developer Experience Engineer will own CI/CD infrastructure and internal tools, improve developer productivity, and foster team collaboration through effective tooling and automation.

Lead a backend and cloud platform engineering team responsible for Node.js/NestJS services on AWS. Own APIs, event-driven processing, file ingestion, data synchronization, CI/CD, infrastructure, observability, incident response, and production operations. Drive vendor-to-internal support transition through knowledge transfer, runbooks, on-call practices, and operational readiness. Mentor engineers, prioritize work, conduct technical reviews, collaborate with stakeholders, and improve system reliability, security, and recoverability.

Build AI-powered 3D character and motion creation tools across React and TypeScript frontends, Go and Gin backend APIs, and Python or TypeScript asset-processing services. Responsibilities include developing, testing, deploying, and debugging APIs and interfaces; integrating asset conversion, rendering, and video-processing workers; and supporting authentication, API security, storage, and asynchronous workflows.

Design, develop, test, deploy, and support scalable full-stack web applications and platform capabilities using Python, Django, TypeScript, and React. Build APIs, integrations, AI-enabled features, and reusable application components across AWS and Azure. Own software from design through production support, contributing to CI/CD, observability, security, modernization, and reliability. Collaborate with Product, Architecture, Data & AI, Security, and Platform Reliability teams while mentoring engineers and maintaining high-quality production systems.

Own the technical direction and roadmap for Robinhood’s Developer Infrastructure organization. Lead Bazel-based monorepo and remote build infrastructure, large-scale CI/CD, test environments, developer platforms, and tooling across multiple languages. Drive AI and agentic systems throughout the software development lifecycle, establish technical standards, and unify four engineering teams around a long-term vision. Mentor senior engineers and influence company-wide engineering strategy.

Build and deploy enterprise automation and AI solutions across business systems, data platforms, and IT environments. Analyze business processes, identify automation opportunities, integrate platforms and APIs, test and monitor production solutions, and support adoption through documentation and training. The role requires hands-on coding, AI workflow experience, process analysis, and the ability to translate business needs into secure, practical technical solutions.

Lead design, development, testing, implementation and support of data and AI products. Translate business requirements, provide technical direction, mentor developers, build automation and frameworks, improve delivery processes, and perform data analysis, profiling and regression testing.

Build AI-driven security scanners and automation for vulnerability discovery, triage, validation, and remediation. Red team internal AI systems through jailbreak, prompt injection, and tool abuse testing. Partner with engineering teams to remediate vulnerabilities, verify fixes, and improve bug bounty and incident response workflows. Mentor junior security engineers on AI-augmented offensive security practices.

Leads engineering excellence across Citi’s global technology organization by championing engineering culture, operationalizing DORA metrics, driving software delivery improvements, and managing large-scale technical and cultural change. The role remains hands-on through code reviews, design discussions, and prototyping, while integrating AI into engineering practices, coordinating concurrent initiatives, and communicating technical strategies to senior stakeholders.

Build and operate Block’s data platform, including warehousing, orchestration, business intelligence, governance, and agentic workflows. Develop reliable Python services, developer tools, and Terraform infrastructure for petabyte-scale data. Partner with data practitioners and product teams, establish engineering standards, provide technical direction, and mentor engineers while ensuring security, reliability, observability, usability, and data governance.

Own domain datasets, data pipelines, business metrics, and quality checks that support Lyft’s marketplace decisions. Build reliable analysis-ready data, deliver metrics to stakeholders, and partner with product managers, engineers, and operators to translate data into action. Communicate analytical findings clearly and maintain trusted data products with executive visibility.

Research and reverse-engineer web anti-automation systems, including browser detection, challenge flows, fingerprinting, and obfuscated JavaScript. Build and deploy browser automation, diagnostic, and monitoring infrastructure that improves scraping reliability across a large crawling fleet. Measure scrape success, investigate regressions, and ship production fixes quickly while collaborating with platform engineers.

Leads digital water projects involving data management, collection, processing, analytics, modeling, visualization, GIS, and custom application development. Supports software selection, procurement, planning, design, and operational activities for water and wastewater utilities. Collaborates with technical teams and clients, communicates analytical results, and stays current with digital water technologies.

Build and operate a scalable data platform supporting warehousing, orchestration, business intelligence, governance, and agentic workflows. Develop Python services, Terraform infrastructure, and developer tools for petabyte-scale data. Partner with data practitioners and product teams, establish security and reliability patterns, set technical direction, improve engineering standards, and mentor engineers.