Top Python Jobs in Toronto

The Azure CloudAI Ops Engineer supports health outcomes by maintaining reliable SaaS services on Azure, automating operations, and collaborating with dev teams to improve healthcare technology.

As a Site Reliability Engineer, you will enhance system reliability, drive incident responses, design tools for automation, and participate in on-call rotations.

The Data Reporting Lead Analyst will analyze project data, develop reports and dashboards, ensure data integrity, and support PMO decision-making processes.

The Java Full Stack Developer leads applications systems analysis, resolves complex problems, develops standards for coding, and coaches mid-level developers while ensuring compliance and risk assessment.

Lead the design and implementation of application systems, provide technical expertise, mentor developers, and ensure compliance with standards and regulations.

As a Senior Software Engineer, you will design, implement, and maintain backend systems that integrate identity and authorization capabilities into AI workflows, ensuring security and reliability at scale.

As a Senior Software Engineer, you will develop and maintain software for healthcare applications, utilizing big data technologies and programming languages, ensuring high-quality code and system performance.

As a Fullstack Software Engineer, you'll collaborate with multi-functional teams to enhance AI-driven solutions, participate in software development best practices, and take ownership of various platform functional areas.

As a Fullstack Software Engineer, you'll enhance Evisort's AI-driven contract management platform by collaborating with cross-functional teams and taking ownership of multiple functional areas from development to production.

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.

As a Photonics Test Engineer, you will characterize active optical devices, develop test procedures, and interface with various technical teams to align testing strategies with development.

The Data Scientist will design and maintain predictive models for customer growth, collaborating with various teams to ensure actionable insights and model performance.

The Lead Data Engineer will architect and develop reporting solutions, integrate AI, analyze complex datasets, and mentor team members to enhance data-driven decision-making.

Design, build, and deploy GenAI and agent-based systems for Wealth Management. Lead end-to-end solution development, integrate AI with existing platforms, enforce MLOps, model governance, security, and regulatory compliance, and collaborate with cross-functional teams to drive production-grade, scalable AI products.

Develop full-stack features with an emphasis on video frontend (React/TypeScript) while supporting backend services (C#/Java/Python, SQL). Collaborate cross-functionally, write and review code, use AI-assisted tools to generate tests and documentation, contribute to system design, and participate in on-call rotation as needed.

Design, train, and deploy ML models for fraud detection, synthetic identity, and deepfake detection. Build evaluation pipelines, labeled datasets, benchmarks, and monitoring. Productionize models with backend engineering for latency, throughput, and reliability. Research adversarial approaches, multimodal fusion, and active-learning; partner with product and threat intelligence to convert fraud patterns into trainable signals.

Build and own end-to-end full-stack features that surface fraud, deepfake, and identity signals. Design backend APIs and services, develop responsive React/TypeScript UIs, contribute to data pipelines and ATS integrations, and partner with design, product, and ML teams to ship high-quality enterprise recruiting workflows.

Develop and optimize quantum compilation and Quantum Error Correction software to bridge high-level logical abstractions and hardware control. Translate QEC research into production-grade Python and C++ implementations, integrate with compilation IRs and control system APIs, collaborate across hardware and research teams, and maintain high standards for testing, documentation, and CI/CD.

Lead design, implementation, and operation of enterprise IT infrastructure with a security-first focus on identity and access management across GCP, AWS, and GitHub. Build Okta-driven provisioning and workflows, integrate business-critical systems, automate processes (Workato/Okta Workflows), mature identity governance and PAM, support IT teams as a senior technical escalator, and ensure compliance through policy, audit trails, and documentation.

Lead design, build, and maintain high-availability CI/CD infrastructure. Advise developers/testers on DevOps toolchains, research emerging tools, optimize build and release processes, perform code reviews and security analysis, manage Microsoft Power Platform, and collaborate across the SDLC to deploy and tune cloud/PaaS solutions.

Lead a small actuarial team to produce five-year P&C loss ratio forecasts, budgets and reserve projections; build reporting on claims frequency/severity and monthly financials; implement governance and controls; support valuations, FCT/ECAP modeling; present results to executives and develop staff.

The Machine Learning Platform Engineer will build and scale AI infrastructure, develop MLOps pipelines, automate workflows, and ensure model deployment in production environments.

Build LLM-powered applications and agents (copilots, workflow automation, natural language interfaces), design RAG pipelines and vector search, integrate LLMs into a SaaS platform, implement evaluation/safety frameworks, and collaborate across product, engineering, and MLOps to deploy scalable, auditable AI features.

The Machine Learning/AI Tech Lead at PureFacts will guide ML and AI engineers, oversee product vision, and drive automation, model development, and cross-functional collaboration to enhance client outcomes.

Design, implement, and scale event-driven, distributed backend systems in Python on AWS to process and enrich large-scale document and media datasets. Lead technical projects, mentor engineers, integrate ML/LLM components, optimize performance, maintain observability, and collaborate with Data Science, ML Engineering, and Product to deliver reliable high-throughput content processing services.