Top Python Jobs in Toronto

Own and maintain data platform infrastructure: provision Snowflake via Terraform, build CI/CD for dbt, implement data quality and observability, extend the OpenMetadata catalog, create developer tooling and reproducible environments, and ensure secure, production-ready data pipelines.

Lead cross-functional teams to define, build, and deliver production-grade AI/ML solutions. Translate business objectives into technically feasible architectures, drive roadmaps, enforce MLOps and engineering standards, ensure governance and model risk controls, and measure business value from models. Mentor colleagues and coordinate cloud-native deployment, monitoring, and lifecycle management of AI systems.

Design, develop and maintain data controls and governance for Financial Crime & Risk Management systems. Lead complex data initiatives, perform data profiling, root cause analysis, troubleshoot data pipelines, automate processes, integrate databases with analytics platforms, and collaborate globally to ensure data integrity for payments and transaction monitoring.

As a Data Architect, you'll design scalable data solutions, collaborate with teams to drive AI and data science projects, and communicate insights effectively.

As a Product Engineer, you'll design and deploy scalable software solutions for a global SaaS platform, collaborating with teams, ensuring code quality, and resolving technical issues in an Agile environment.

The Applied Researcher will develop and deploy ML models and data pipelines for search relevance and query understanding, collaborating with teams to drive innovations in NLP and deep learning.

The Systems Engineer will manage and optimize Axway Managed File Transfer services, lead migrations to Kubernetes, and ensure security compliance while automating processes with scripting and IaC principles.

As a Principal Automation Engineer, lead infrastructure automation, define IaC strategies using Ansible and Terraform, and integrate AI into automation. Act as a technical consultant and mentor to teams, ensuring architectural governance and enhancing systems' reliability and speed to market.

The Engineering Manager will lead teams across North America and Europe, focusing on developing software, people management, and fostering collaboration within a distributed environment.

Master-level internship to design and deploy agentic workflows and RAG/search pipelines, select and integrate LLMs via APIs/MCP, engineer prompts and evaluations, connect models to data sources, and validate AI-generated outputs within cross-functional teams.

Build and maintain integrations and data pipelines connecting client databases, APIs, and SaaS tools. Extract, clean, transform, and move messy real-world data to feed retrieval and agentic AI systems, apply security and privacy best practices, and document reproducible integrations.

Lead product ownership for PricingCenter's pricing engines and rate execution. Define and deliver deployment, versioning, testing, validation, integrations, governance, and scalability capabilities. Work closely with engineering, UX, actuarial SMEs, services, and customers to prioritize, deliver, and measure outcomes for enterprise insurer customers.

Lead and grow a Data Engineering team to modernize enterprise data platforms (Snowflake/Databricks), deliver secure scalable batch and real-time pipelines, enable DataOps/MLOps, establish CI/CD and IaC practices, monitor platform health, and drive strategic platform migrations and performance optimizations with cross-functional stakeholders.

Lead the development and delivery of AI-driven product capabilities, transforming data into actionable insights while mentoring a high-performing team of data scientists and engineers.

As a Data Engineer, you will design and implement scalable data pipelines and solutions, collaborate with teams, and apply new technologies in an Agile environment.

The Cloud and DevOps Developer will provide cloud infrastructure builds, implement DevOps best practices, and participate in Agile project delivery.

The Data Engineer will design scalable data pipelines, manage data solutions, collaborate with teams, and ensure project delivery on time while applying new technologies.

The Cloud and DevOps Developer will implement DevOps best practices, design cloud solutions, collaborate with teams, and manage infrastructure projects.

As a Research Engineer, you will integrate ML models into planning stacks, develop testing interfaces, and collaborate with teams to enhance autonomous truck capabilities.

As a Research Engineer, you will develop algorithms for world models focusing on generative and predictive modeling within complex environments, optimizing model deployment, and collaborating with research teams.

Collaborate to scale self-driving systems, build training frameworks, profile model performance, and evaluate emerging technologies for training and inference.

As a Research Scientist, you will design AI technologies for motion planning in self-driving trucks, focusing on deep learning and seamless integration into production systems.

As a Senior Perception Engineer, you will develop and deploy perception algorithms for self-driving vehicles, ensuring quality and collaboration within a multidisciplinary team, while publishing research findings.

As a Research Engineer, you will develop and enhance AI algorithms for self-driving vehicles, collaborating with scientists to advance technology and support deployment in production systems.

The Software Engineer will validate and verify flight control systems software, perform testing in alignment with DO-178C standards, and contribute to process improvements.