Top Python Jobs in Toronto

The Client Solution Architect will lead complex implementations, drive client engagement, mentor teams, and establish standards within wealth management solutions.

The Consultant will conduct financial analyses and modelling, manage client relationships, oversee junior staff, and perform market research. Responsibilities include developing financial tools and ensuring quality control on deliverables.

As a Consultant, you will conduct due diligence, analyze financial statements, develop reports, create financial models, and manage client relationships, ensuring high-quality deliverables to clients.

Perform static timing analysis and timing signoff for FPGA/ASIC designs, debug and resolve timing violations, develop and validate timing constraints, collaborate with RTL/synthesis/physical design teams, and improve STA methodology and automation to optimize performance, power, and area.

The role involves collaborating with customers to solve engineering challenges using machine learning, develop solutions, train teams, and improve products based on feedback.

Lead discovery, prototyping, and commercialization of ML/AI and edge computing solutions. Build hands-on prototypes, collaborate with data scientists and engineers, engage customers and partners for co-innovation, influence product roadmaps, participate in standards/open-source, and evangelize thought leadership to advance productization and market adoption of intelligent networking capabilities.

As a Software Engineering Consultant, you will design, build and own the lifecycle of scalable software systems while collaborating with clients in various technical domains.

The Staff Data Scientist will lead data science projects, develop machine learning models, and align solutions with business goals while mentoring team members.

Lead evaluation, selection, implementation, and lifecycle management of enterprise applications with a focus on AI-driven automation and AIOps. Design and deploy LLM-based workflows, AI agents, observability and predictive monitoring, perform health checks and upgrades, troubleshoot cross-team incidents, define technical roadmaps, and mentor IT Applications team members while creating SOPs and documentation.

As a Software Engineer, you will create tools and pipelines for AI development, manage data solutions for ML teams, and ensure high-quality code.

As a Research Scientist in Neural Reconstruction, you will develop algorithms for 3D/4D scene reconstruction using real-world sensor data, collaborate on large-scale simulation systems, publish research and mentor junior scientists.

Develop algorithms for World Models focusing on large-scale modeling for dynamic 4D environments. Conduct research in generative and predictive modeling, collaborate with engineers, and mentor junior scientists.

Design and deliver full-stack features across notebook services, container runtimes, and UI (Go/Python backend, TypeScript/React frontend). Own medium-to-large projects end-to-end, improve runtime management, reproducibility, security/compliance, and observability, ensure reliability in regulated or air-gapped environments, participate in on-call rotation, and mentor junior engineers.

Define, implement, execute and maintain test plans and cases for ADAS controllers. Automate tests, develop and troubleshoot HIL bench tests, use Python and CAN/Ethernet tools (INCA, CANoe, CANalyzer, VSpy), produce reports, and apply calibration/validation and AI tools to improve test coverage and productivity.

As a Staff Backend Engineer, you'll design and evolve backend services, architect data models, mentor engineers, and influence architecture and product direction to enhance enterprise-grade performance.

As a Staff Backend Engineer, you will develop complex backend solutions, focusing on the Spark-based data platform while ensuring code quality and collaborating closely with teams.

Design, build, and ship end-to-end AI and data solutions using proprietary data infrastructure. Scope projects with business stakeholders, implement models, pipelines, and APIs (Python/SQL), deploy on Snowflake or BigQuery, and iterate post-launch. Enable non-technical teams, collaborate with Data Engineering and AI teams, and operationalize LLMs, embeddings, and predictive models into working internal products.

Mid–Senior Technical Artist responsible for bridging art and engineering: optimize pipelines, author shaders and Niagara effects, build performant terrain and procedural workflows in UE5, balance cutting-edge rendering (Lumen, Nanite) with cross-platform optimization, and act as technical liaison between art, design, and engineering.

Design, build, and operate production multi-agent AI systems and automation for Marketing Operations. Integrate LLMs with business systems (BigQuery, CRMs, Slack), implement RAG pipelines, observability, governance, and scalable serverless/containerized services. Partner with GTM teams to deliver measurable automation and self-service tooling.

Own and patch Chromium/Firefox C++ source to build an in-house stealth browser. Fix fingerprinting at the engine level (navigator, WebGL, canvas, fonts, Client Hints), eliminate CDP leaks, maintain per-OS fingerprint profiles, continuously rebase patches, build validation tooling, and debug detection issues to keep automation indistinguishable from real users.

Ship real open-source integrations and MCP servers to bring SearchApi to agent and automation frameworks. Create PRs, example apps, docs, and integration guides. Stay current with the agent ecosystem, pick high-leverage targets, and work independently to deliver production-ready integrations.

The GPU Cloud Platform Engineer designs and operates multi-cluster GPU infrastructures for AI workloads, ensuring performance and efficiency across cloud environments.

The Robot Data Operations Analyst will control robots, evaluate performance, provide quality assurance, and document observations safely in an R&D setting.

The Full Stack Engineer will develop and maintain scalable web applications, design system architecture, optimize performance, and collaborate with teams for code reviews in a hybrid work environment.

Build and operate core backend services, APIs, and platform components for enterprise AI; integrate LLMs, retrieval and agent workflows; ensure reliability, observability, testing, and scalability; collaborate with research, product, and design to productionize AI capabilities.