Top Python Jobs in Toronto

Build scalable, high-performance front-end experiences using React/Next.js and Three.js, collaborate with product and design, own systems, integrate computer vision, and deliver polished UX for customers.

The role involves developing backend services using Python and Django, ensuring high availability and performance, and leveraging computer vision technology for 3D experiences in home decor.

As a Senior Full Stack Software Engineer at Doxel, you will design and develop applications for project management, focusing on complex data handling and intuitive UI. Your role involves collaborating across teams and providing technical leadership in software projects.

Lead and grow a senior game analytics team, define studio-wide data strategy, and own telemetry, pipelines and tooling. Deliver player insights for engagement, retention, progression and monetisation across multiple titles, run experiments (A/B), and partner with design, production and UX. Evolve the tech stack (Snowflake, dbt, Sigma, GitHub), introduce AI/ML methods, and communicate data-driven recommendations to stakeholders.

Consult on operations and supply chain projects for mid-market clients, delivering data-driven analysis, process improvements, and implementation support across demand planning, inventory, procurement, manufacturing, logistics, ERP/WMS/TMS/QMS deployments, and AI-enabled solutions. Lead client interactions, workshops, proposals, and engagement economics while driving measurable operational improvements.

Lead a research engineering team to deliver AI solutions from prototype to production. Manage cross-functional delivery with product and applied scientists, drive technical roadmap and infrastructure, mentor engineers, champion advanced engineering practices, and own rollout of business-critical, customer-facing features while balancing technical debt and scalability.

Support FRTB production by performing operational analyses, data validation, reconciliation, and reporting. Identify, track and resolve market risk issues, maintain controls and procedures, liaise with stakeholders, respond to audits and ad hoc requests, and assist on projects and improvements to risk infrastructure.

Execute hydrogeological modelling and field programs: build conceptual site models and 3D groundwater models, prepare technical reports and proposals, design and analyze aquifer tests and monitoring, mentor junior staff, liaise with clients/regulators, and ensure successful project delivery (scope, schedule, budget, QA/QC).

Lead technical direction and architecture for the Fable backend, own platform reliability (databases, CI/CD, queues, observability), run incident response and postmortems, mentor engineers, collaborate cross-functionally with product/design/ML, and build platform capabilities enabling faster, safer delivery.

Lead the product strategy for Scribd's internal developer and agentic platforms: unify AI workstreams, own internal app/plugin/agent runtimes, translate functional needs into platform requirements, drive cross-functional adoption and metrics, and run internal rollouts and evaluation to prove impact.

Lead analytics and operational insights for Customer Operations: define core metrics, build dashboards and forecasts, model churn/renewal risk, enable self-serve reporting, implement AI-enabled automation, and partner cross-functionally to drive retention, expansion, and support efficiency.

As a Software Engineer in Data Infrastructure, you will build and maintain high-performance data storage systems for AI training, collaborate with experts, and optimize data processing.

Build and ship full-stack features for North, develop autonomous agents that access sensitive enterprise data, productionize state-of-the-art models, write minimal, secure low-resource code, and collaborate with researchers to deploy performant RAG/agentic applications while prioritizing security and user experience.

Support vehicle profitability analysis by developing automated COP/CMP-I models, dashboards, and forecasts using Power BI, Excel, and data techniques (regression, scenario modeling). Translate analytics into pricing and incentive insights, partner with IT to improve data quality, and drive process automation and forecasting for budgeting and strategic initiatives.

The Staff Software Engineer will lead the technical strategy for AI platform development, architect foundational AI systems, ensure alignment between teams, and mentor engineers while driving organizational engineering standards.

The Applied AI Scientist will work on developing and deploying AI systems, collaborating across teams to improve product features and drive customer impact through machine learning models.

Build scalable ML data pipelines for Waabi's autonomous driving platform. Design, optimize, and manage datasets and training processes while collaborating with scientists and engineers.

Contribute to the development of Waabi World, improve simulation scalability, and design orchestration software for autonomous vehicle simulations.

As a Machine Learning Scientist at Nucs AI, you will develop innovative ML methods for medical image analysis, collaborate with clinicians, and contribute to clinical validation studies, impacting cancer diagnostics.

The Principal Platform Engineer will design and implement AI platforms, including distributed systems and orchestration frameworks, mentor engineers, and define best practices for LLM integration.

The Principal Platform Engineer will design and build scalable ML platforms, develop cloud-native infrastructure, and manage the model lifecycle in enterprise environments, focusing on MLOps capabilities and mentoring engineers.

The Senior Platform Engineer will build AI systems, develop APIs, support scalability, and integrate AI capabilities for financial services clients.

RAVL is seeking Senior ML Platform Engineers to build and scale machine learning platforms, develop ML pipelines, and support MLOps workflows in cloud environments.

Perform deep root-cause debugging across frontend-to-backend stacks, troubleshoot and read SDK source, support enterprise customers on architecture, and build agentic automation (LLM orchestration, MCP, internal APIs) to create deterministic autonomous support paths.

Lead instrument risk modelling for derivatives, hedge funds, liabilities and other securities. Build tools, validate models, collaborate with traders, finance and developers, and deliver risk reporting and advanced risk-management approaches.