Top Python Jobs in Toronto

The intern will research Physical AI, implement algorithms, write scientific papers, and analyze ML trends in AI. Collaboration with researchers is essential.

As a Senior Backend Software Engineer, you'll enhance the AI-driven contract management platform by collaborating with teams, optimizing code, and ensuring platform performance through API development and monitoring strategies.

As an Intern Researcher, you will develop AI agents powered by LLMs, prototype core capabilities, and explore new research directions while collaborating with experts.

The role involves designing and optimizing AI coding agents, integrating AI tools, and establishing evaluation systems for enhancing code generation accuracy.

The Senior MLOps Engineer will build and operate scalable infrastructure for AI solutions, collaborating on ML-driven features, troubleshooting production issues, and mentoring team members.

The AI Engineer will design, develop, and deploy machine learning models, integrating them with applications while conducting experiments to improve performance.

As a Python Developer, you'll design, develop, and support custom solutions, focusing on enhancing client experiences through innovative banking applications and data integration solutions.

The TDS Operations Analyst III will manage operations project migration, improve business strategies, collaborate with stakeholders, and ensure project completion within deadlines.

The AI Engineer will design, develop, and deploy AI-driven solutions to automate logistics workflows, focusing on building production AI agents and integrating MCP with Kubernetes.

The Data Engineer will design SQL pipelines, develop Python applications, implement RisingWave streaming, and optimize workflows using Apache Airflow on Google Cloud Platform. They will also mentor others and manage CI/CD deployments.

The Senior Application Architect designs and oversees software architecture, ensures application scalability and security, integrates systems, and leads project implementation.

The Senior Data Architect will design data architecture and integration workflows for PM2PA, focusing on optimizing collaboration and ensuring data quality within Oracle EBS and cloud environments.

The Senior Reporting Analyst will build and implement dashboards, optimize data management, and support Marketing Technology initiatives at TD Securities.

The Business Intelligence Specialist manages business activities, develops reports and dashboards, provides analytics expertise, and drives innovation in financial crime and risk management.

The Data Scientist II will create and deploy advanced analytics solutions, using large datasets to influence business strategies and optimize performance through technical expertise and collaboration with stakeholders.

The Full-Stack Software Engineer will design and maintain applications, integrate AI features, and ensure code quality while collaborating with teams.

Design and build scalable full stack applications, integrate AI-driven workflows, develop REST APIs, and mentor junior engineers while ensuring high engineering standards and system reliability.

The Senior Manager will oversee credit risk strategies, ensuring alignment with regulatory practices while providing analytical insights and influencing decision quality. Responsibilities include assessing credit proposals, conducting portfolio analytics, and mentoring team members.

The Associate will design technology solutions for investment decision-making, maintain data infrastructure, and provide advanced analytics for investment lifecycle support.

As a Machine Learning Developer, you'll create AI-powered platform frameworks, manage AI/ML pipelines, and enhance developer productivity using various tools and methodologies, directly contributing to product innovation at Priceline.

Lead the design of generative AI solutions and multi-cloud architectures, translating business use-cases into scalable systems for enterprise deployments.

As a Senior DevOps Developer, you will lead initiatives to design, implement, and maintain infrastructure for the data engineering and ML teams while ensuring reliable deployments and collaboratation with various technical teams.

The Deployment Engineer will manage AI inference clusters, optimizing deployment, capacity allocation, and ensuring reliability of pipeline operations across datacenters.

The role involves developing infrastructure for benchmarking AI inference performance, analyzing system behavior, designing telemetry systems, and collaborating with teams to improve feature performance.

The role involves building standardized training frameworks, profiling model performance, collaborating with teams, and improving related tooling.