Top Python Jobs in Toronto

Design, develop, test, document, and maintain integrations solutions. Collaborate with analysts, architects, engineers, and business stakeholders to align technical and business goals. Support daily operations of integration applications, research and recommend best practices, and keep up to date with company operations and insurance industry trends to improve integration processes.

As a Senior Analytics Developer in People Analytics, you'll design data pipelines, create employee records, and ensure data governance while collaborating with HR and Finance.

The Principal Machine Learning Architect will design and implement data-centric ML solutions, ensuring high-quality ML model development and deployment strategies for a leading ad tech company.

Senior Analyst supporting finance technology transformation: research and implement AI/ML and automation solutions, deliver technology projects, improve finance processes and compliance, support audit/SOX readiness, produce analysis and stakeholder communications, and collaborate across Finance, IT, and Operations to drive measurable efficiency and cost savings.

Manual-focused QA Engineer responsible for test planning and execution across web and mobile, identifying risks, writing structured test cases, validating UX against designs, running and extending web automation (Playwright), and helping evolve automation strategy and CI/CD quality processes.

Deliver production-ready voice AI solutions to enterprise customers: prototype to production, build full-stack integrations, lead deployments, translate field feedback into product improvements, and partner with sales while communicating technical concepts to non-technical stakeholders.

Coordonner et piloter la livraison de programmes et initiatives en cybersécurité de bout en bout, gérer dépendances et parties prenantes, conduire le changement, identifier et automatiser tâches répétitives (outils d'automatisation et IA), et soutenir l'équipe sécurité sur workflows, meilleures pratiques et adoption des outils.

Manage end-to-end delivery of security initiatives, coordinate cross-functional teams, drive change management, improve processes via automation and AI, and enable the security team through coaching and tooling improvements.

Design and prototype Databricks Lakehouse architectures and governance, lead technical discovery, advise on integration with cloud platforms, demonstrate data and ML/GenAI capabilities, and support sales through technical leadership and handoff to delivery teams.

Develop and deploy generative AI and LLM solutions end-to-end for e-commerce: research models, build ETL/data pipelines, run distributed training and experiments, collaborate with product and engineering to deliver production systems that improve recommendations, search, personalization, and customer interactions.

Lead BI initiatives by building and maintaining data pipelines, models, dashboards, and reports. Partner with product, sales, and operations to ensure data quality, run analyses and A/B tests, apply basic predictive modeling, and mentor colleagues to promote data-driven decisions.

Design, research, and productionalize large-scale deep learning models for The Trade Desk's real-time bidding platform. Work end-to-end from ideation to deployment and monitoring, addressing low-latency, high-QPS, sparse/noisy labels, and large output spaces while collaborating closely with engineering and product teams.

Lead design and delivery of end-to-end software architecture for machine HMI stacks. Provide technical and functional leadership, review code and architecture, mentor developers, make technology decisions (performance, safety, scalability), contribute hands-on in Angular, graphics, Python/C++, and system integration, and improve development processes and quality assurance.

Lead software developer responsible for technical and functional leadership: select technologies, design end-to-end architecture (HMI stacks), review code, mentor developers, collaborate with UX and systems teams, implement Angular front-ends and 2D/3D visualizations, and contribute hands-on in complex areas (Angular, graphics, Python/C++).

Build developer tooling, demos, and integrations to enable secure AI agent experiences; contribute to open source; lead architecture, documentation, and cross-functional work to ensure secure, resilient agent-to-service systems.

Develop and optimize FPGA placement algorithms within the compiler toolchain to improve timing, congestion, and resource utilization. Integrate placement capabilities with routing, synthesis, and timing teams, analyze placement quality and bottlenecks, and enhance performance, scalability, and QoR for large designs.

Lead the design, implementation, and operation of core developer infrastructure (build systems, CI, SCM, remote dev envs). Drive architecture, scalability, onboarding improvements, standardize CI/build patterns, mentor engineers, and improve engineering productivity and reliability at scale.

Partner with customers to architect, build, and deploy high-scale production AI applications. Translate ambiguous goals into reliable, observable services, implement end-to-end model deployment and monitoring, optimize ML projects, and own customer-facing technical delivery and product outcomes.

Lead design, build, and deployment of production-grade Databricks data platforms across AWS/Azure. Architect scalable ETL/ELT pipelines with Spark/PySpark, manage Delta Lake and Unity Catalog, implement CI/CD and IaC, provide client-facing technical leadership, and mentor engineering teams.

Design, build, and maintain reliable data pipelines and lakehouse assets for batch and streaming workloads. Implement ETL/ELT in Python and SQL, orchestration and monitoring (Airflow/Kubernetes), and retrieval/RAG/vector search pipelines for LLM and AI applications. Ensure data quality, lineage, versioning (Delta/Parquet/Iceberg), cost/performance optimization, and collaborate with MLOps and sports data teams.

Design, train, and evaluate computer vision models for sports video (detection, tracking, pose, event recognition, re-ID). Run experiments, error analysis, dataset and evaluation design, and collaborate to productionize models with attention to reproducibility and efficiency.

Lead development and refactor optimization algorithms in Python for pricing and supply‑chain problems. Design and implement predictive models and mathematical optimization solutions, collaborate with cross‑functional teams, coach data scientists, and translate business requirements into data‑driven pricing and replenishment strategies.

Build, test, and maintain software across full-stack, backend, infrastructure, data pipelines, and ML infrastructure to support autonomous trucking. Develop web interfaces, backend services, APIs, and tooling; improve reliability, observability, CI/CD, and deployment; participate in code reviews, debugging, and cross-team collaboration while learning new technologies.

Drive enterprise implementations by scoping technical solutions, architecting API-based integrations, managing stakeholder alignment (including C-suite), executing end-to-end testing and enablement, providing VOC to Product, troubleshooting integrations, and mentoring junior team members to ensure successful SaaS adoption and operational efficiency.

Develop and train conditioned policies and MARL systems to simulate realistic driving behaviors, implement safety-constrained RL algorithms, design rewards and evaluation metrics, optimize large-scale training pipelines, advance neural architectures for long-horizon planning and spatial reasoning, and integrate research models with production simulation and planning teams.