Top Python Jobs in Toronto

Lead product analytics and experimentation: run proactive funnel and cohort analyses, design and analyze A/B/multivariate experiments, build KPIs, automated dashboards and models, and partner with product, marketing, data, and engineering to inform product releases and engagement strategies.

Build full-stack products that put generative AI into creators' hands: design delightful UIs, optimize backend systems, ship AI-first features, design APIs and data models, and iterate rapidly with user feedback while collaborating across teams.

Manage and optimize core SaaS infrastructure (Okta, Jira, Kandji), automate workflows with Okta Workflows and APIs, apply IaC for SaaS configs, analyze logs/ticket trends, enforce Zero Trust and lifecycle automation, and support vendor strategy and technical intake to translate business requirements into repeatable technical solutions.

Design, build, deploy, and maintain large-scale backend and distributed systems for Lyft's Incentives & Messaging Growth Platforms. Collaborate with product and ML teams, improve automation and reliability, and deliver well-tested, production-grade services.

Develop and deliver cloud-based computational design solutions using Rhino and Grasshopper. Build modular, scalable workflows, create custom Python and C# nodes/plugins, develop APIs for interoperability, handle sensitive client data, and collaborate with engineering and design teams to enhance the Generate platform.

Develop network automation software for TeraWave satellite communications, including designing flight software and implementing autonomous network routing.

The Principal Software Engineer will lead the development of autonomous systems for satellites, overseeing architecture and capabilities while mentoring engineers. Responsibilities include guiding algorithms for satellite operations and ensuring software integration across mission elements.

The Senior Payload Software Engineer will lead the design and development of software for TeraWave satellite communications, focusing on network automation and communication protocols while mentoring junior engineers.

Develop network automation software for TeraWave satellite communication systems, focusing on embedded software, network protocols, and real-time processing.

The Payload Software Engineer develops network automation software for TeraWave's satellite communications network, focusing on payload systems and real-time data processing algorithms.

Lead development of large-scale network simulation software for a multi-orbit satellite constellation. Model traffic, optical inter-satellite links, and QoS; evaluate resilience and security; integrate network capabilities with systems engineering; analyze performance, troubleshoot distributed systems, and lead technical networking discussions.

The Data Analytics and AI Architect will define and advance the organization's data and AI architecture, ensuring alignment with business strategy. Responsibilities include designing architectures, researching technologies, and managing compliance.

Design and scale the infrastructure for ML systems, enabling reliable trading system production, optimizing performance and ensuring correctness across complex environments.

Support Treasury operations including cash management, FX settlement, and risk management. Drive process improvements and develop metrics for operational excellence.

Lead a team of Support Engineers while actively participating in resolving complex technical issues, mentoring staff, and maintaining quality service standards.

As a Research Engineer in Sensor Simulation, you will develop multi-sensor rendering systems for self-driving technologies, collaborate with scientists and engineers, and work on innovative solutions using machine learning and neural rendering techniques.

The Design Verification Engineer will rigorously verify designs using UVM techniques, collaborating closely with digital and analog design experts, while defining DV methodologies and ensuring quality tapeouts.

The Technical Systems Manager will develop and maintain internal systems and integrations, enhance workflows, ensure security compliance, and document processes to support business needs.

Design, develop, and deploy scalable AI solutions including multi-agent workflows, integrate LLMs via APIs and microservices, build prototypes, perform prompt engineering, monitor model performance, mitigate hallucinations, and collaborate with data and engineering teams to align AI with business needs.

As a Data Scientist II, you'll develop data-driven solutions using machine learning, collaborate cross-departmentally, and maintain data mining tools to deliver actionable insights.

Lead post-silicon bring-up and optimization of wafer-scale engines: develop debug flows, HW-SW codesign optimizations, build large-scale test infrastructure, create self-checking metrics and instrumentation, and collaborate across silicon, performance, and software teams to improve production performance and release processes.

Design and implement system-level debugging, validation, and observability platforms. Build automated anomaly detection, visualization and analysis tools, and frameworks for failure classification and regression detection. Extend compilers, runtimes, and instrumentation for advanced profiling. Improve bring-up and low-level debug workflows, partner cross-functionally across hardware, firmware, compiler and runtime teams, lead high-impact initiatives, and support incident response and long-term corrective actions.

Lead post-silicon bring-up and performance optimizations for Cerebras Wafer Scale Engines. Develop/debug production-ready flows, instrumentation, and self-checking metrics. Build infrastructure for large-scale silicon workload testing, collaborate with silicon architects, performance and software teams, and streamline CI/CD and release workflows.

The Revenue Systems Engineer will manage and enhance GTM systems, implement integrations, maintain HubSpot, ensure data quality, and collaborate with various teams.

The Sales Engineer will manage technical relationships, design AI/ML solutions, deliver demos, train customers, and provide feedback to product teams.