Top Python Jobs in Toronto

Design, build, and maintain Python-based, cloud-native (AWS) data pipelines and file delivery systems (CSV, Parquet, JSON). Implement monitoring, validation, CI/CD, and migrate legacy feeds to scalable, reliable architectures; contribute to web-based feed monitoring and production support.

The role involves leading financial analysis for technology spend, designing data models, developing visualizations, and ensuring data quality, while collaborating with internal stakeholders across the company.

Lead full-stack design and development for Capital One's travel portal across front-end and back-end. Own architecture, apply HLD methodology, establish engineering best practices, mentor junior engineers, and improve developer experience while working through the SDLC on fault-tolerant, multi-platform systems.

Lead backend development for Capital One's travel portal across the full SDLC. Own technical design and architecture, drive engineering best practices, improve developer experience and internal tooling, mentor junior engineers, and deliver fault-tolerant, cross-platform services using cloud-native technologies.

Manage financial analysis, oversee annual budget and forecasting, provide insights for decision-making, and lead a team of junior analysts.

Design, build, and operate enterprise identity and endpoint security systems. Implement lifecycle automation, SSO/SCIM provisioning, phishing-resistant MFA, conditional access, endpoint hardening and EDR operations. Build automation and AI agents to reduce manual work, run the enterprise security program, monitor metrics, and partner on telemetry and incident response.

The Data Scientist will design and build machine learning solutions, optimize for business value, and guide customer success through technical expertise and collaboration.

Graduate research co-op focused on building Customer World Models and proactive intelligence: designing representation learning, foundation-model, reinforcement learning, and agentic systems; running experiments, publishing, and deploying research into production to improve long-horizon decision-making and customer-facing automation.

Lead design, automation, and maintenance of secure, scalable IT infrastructure across SaaS, cloud, and endpoints. Administer core platforms, manage cloud touchpoints, build scripting and IaC automation, run onboarding/offboarding lifecycles, troubleshoot networks, lead IT projects, mentor junior engineers, and partner with Security and business units to align IT with compliance and risk posture.

Lead a team to design, deploy, and maintain Industrial IoT and cloud-connected smart factory solutions. Build AWS-based, AI-enabled workflows, manage IaC (Terraform), CI/CD, monitoring, and collaborate with cross-functional teams to improve manufacturing performance.

Design, develop, and deploy scalable LLM-based solutions (RAG, agentic workflows, PEFT). Lead architecture, implement cloud and DevOps best practices (AWS, Azure, Databricks, Terraform, Docker, Kubernetes), build prompt/response guardrails, collaborate cross-functionally, and manage full SDLC and production deployments.

Design, implement, and scale production ML components and data pipelines using robust software engineering practices. Collaborate with customers and product teams to generalize use cases into platform features, deploy ML models to production, and maintain infrastructure (Kubernetes, Airflow, Terraform) and data services (BigQuery). Mentor teammates, write well-tested type-hinted code, and support successful customer implementations.

Contribute to modernization and technical-debt reduction efforts, implement and test features, participate in code reviews, follow CI/CD and Agile practices, and collaborate with senior engineers while learning cloud and security practices.

Implement deep-learning, computer vision, and inverse-procedural modeling algorithms in Python to convert large 2D/3D and geospatial datasets into high-fidelity 3D content. Apply state-of-the-art ML and graphics research, deploy and test code on remote machines, and collaborate with founders to translate product vision into technical milestones while maintaining code via Git.

The role focuses on extracting, cleaning data, building and maintaining machine learning models, and optimizing business strategies using data science methodologies.

The Applied Scientist will develop quantitative models to improve pricing, demand forecasting, and risk management, collaborating with cross-functional teams to implement solutions.

As an Applied Scientist, you will push the limits of AI/ML in home valuation, tackling diverse ML challenges and optimizing decision-making with data.

The Senior Data Engineer will develop and maintain data platforms on Google Cloud, optimize data pipelines, and support Data Science teams in model training and analytics, collaborating closely across departments.

This role involves collaborating with clients to define use cases, implement data integrations, improve ML architecture, and ensure customer success in using BrazeAI.

Lead and deliver large, complex platform engineering programs across sensor, cloud, and research teams. Provide hands-on program leadership, drive cross-team schedules, resolve architectural and infrastructure dependencies, and escalate critical issues. Build AI-powered dashboards, automated reporting, and integrations between Jira, GitLab, monitoring and build systems to surface program risks and automate routine PM tasks. Coach distributed teams, communicate status to executives, and align engineering work with strategic objectives.

The Engineering Manager leads Data Engineering teams, developing scalable data solutions and collaborating with stakeholders to drive McCain's digital transformation.

Design, build, and tune cloud-native detection and response capabilities in Microsoft Azure. Develop Sentinel analytics, KQL queries, SOAR/Logic Apps playbooks, integrate security tooling across Azure and M365, translate threat intelligence into detections, and collaborate with an MDR partner and internal teams to improve SOC processes and automated response workflows.

Graduate research internship to own end-to-end research on Customer World Models and proactive intelligence: design representations, develop methods (foundation models, RL, causal reasoning, agentic systems), run experiments, publish, and help ship ML systems that anticipate and act on customer needs.

Lead a small team and contribute hands-on to design, develop, deploy, and iterate AML and crypto risk detection machine learning models. Own technical roadmap, collaborate with Product and Engineering, ensure model quality, explainability, documentation, and governance, and drive production performance and outcomes across the model lifecycle.

Drive post-silicon productization of bitcoin mining ASICs from bring-up to mass production. Lead characterization, test strategy, ATE program development, wafer sort and final test screening, DOE and yield optimization, data analysis across CP/FT/bench/system platforms, vendor/foundry engagement, and KPI/dashboard development to improve power, performance, yield, and product quality.