Top Python Jobs in Toronto

Design, implement, and operate cloud and Kubernetes detection and response controls across Azure and AWS. Develop detection-as-code, playbooks, and automations; perform threat hunting, incident triage, and collaborate with engineering and IT teams. Participate in on-call rotations and improve security posture for regulated environments.

Build and maintain BigQuery data pipelines, map warehouse schemas, and craft SQL to feed LLMs. Develop Claude Skills and Gemini Gems, collaborate on prompts, validate AI outputs, and design AI agents to automate eCommerce analytics and operational workflows.

Lead and manage a team of statisticians and data analysts to design and perform quantitative analyses for wage-and-hour matters, deliver timely client-facing reports, streamline processes, ensure data quality, manage project workflows and budgets, and train staff in statistical methods and automation.

The Applied AI Scientist will work on developing and deploying AI systems, collaborating across teams to improve product features and drive customer impact through machine learning models.

As a Machine Learning Scientist at Nucs AI, you will develop innovative ML methods for medical image analysis, collaborate with clinicians, and contribute to clinical validation studies, impacting cancer diagnostics.

As an Applied AI Developer, you will build AI-backed tools using Python, integrating LLM APIs, and automating workflows while ensuring reliability and quality evaluation of AI outputs.

The Senior Full Stack Engineer will design and build core infrastructure for a logistics platform, focusing on backend systems, high-scale CRUD APIs, and real-time, event-driven architectures in a startup environment.

The Data Engineer is responsible for designing and optimizing data pipelines, ensuring data integration, and collaborating with teams on AI-driven applications.

Design, develop, and deploy scalable machine learning solutions, integrate ML with data warehouses, and optimize model performance in production environments.

The Principal Platform Engineer will design and implement AI platforms, including distributed systems and orchestration frameworks, mentor engineers, and define best practices for LLM integration.

The Principal Platform Engineer will design and build scalable ML platforms, develop cloud-native infrastructure, and manage the model lifecycle in enterprise environments, focusing on MLOps capabilities and mentoring engineers.

The Senior Platform Engineer will build AI systems, develop APIs, support scalability, and integrate AI capabilities for financial services clients.

RAVL is seeking Senior ML Platform Engineers to build and scale machine learning platforms, develop ML pipelines, and support MLOps workflows in cloud environments.

As a Software Engineer in Data Infrastructure, you will build and maintain high-performance data storage systems for AI training, collaborate with experts, and optimize data processing.

The Senior Data Engineer designs, builds, and maintains data pipelines and ensures data quality controls while supporting data analytics and reporting needs.

The Procurement Manager develops centralized procurement strategies for vendor management, ensuring alignment with business objectives and overseeing project management audits. They manage vendor relationships and collaborate across teams to improve procurement processes.

The Full Stack Engineer will design, build, and maintain scalable web applications, impact customer onboarding and integrations, write and review code, and support technical improvements.

The Back-end Engineer will develop and maintain services and APIs, design data models, and contribute to system stability, collaborating with other engineers and product managers.

The Co-op Engineer will analyze source code, implement new features on demo apps for Android or HarmonyOS, and deploy AI models on Huawei devices, collaborating across teams.

The Senior IT Systems Specialist manages IT and OT systems, ensuring security and performance. Responsibilities include Azure administration, cybersecurity, automation, and end-user support.

The AI Specialist will integrate AI technologies into R&D processes, develop automation tools, collaborate with researchers, and maintain high-quality production code.

As an AI Specialist, you will drive AI initiatives using machine learning techniques, analyze R&D data, develop algorithms, and collaborate with teams to enhance research tools for quantum computing.

The Hydroinformatics Engineer develops algorithms for optimizing water systems, leverages data analytics, and communicates solutions to enhance urban watershed management.

The role focuses on architecting and owning the marketing technology stack by writing scripts and building integrations, attribution models, and testing frameworks to support growth and consumer engagement.

This role involves managing a team of AI and Applied Research professionals, driving the production of AI solutions, and collaborating with product leaders to shape an AI-driven roadmap.