Top Python Jobs in Toronto

Lead architecture, build, and scale a Databricks lakehouse: design batch/streaming pipelines, enforce governance with Unity Catalog, optimize Spark workloads, operationalize ML (MLflow), manage cloud/IaC, mentor engineers, and partner with stakeholders on roadmap and security/compliance.

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

As a Lead Business Analyst I, you'll architect scalable data models, refactor legacy systems, and perform advanced data analyses, primarily using dbt and Python, to support Go-To-Market operations at Braze.

The Senior Data Scientist will build models and analyses, design experiments, integrate datasets, and leverage AI for improved workflows and insights in data science.

As a Senior Software Engineer, you will lead backend development, design scalable services, and mentor team members while focusing on AI-driven product enhancements.

Lead QA efforts to design and maintain automated end-to-end tests across internal and external systems, build evaluation frameworks for AI/LLM features, embed testing into CI/CD pipelines, foster a shift-left quality culture, and transform manual testing into automation while collaborating with engineers and product managers.

As a Machine Learning Engineer II at Affirm, you'll develop AI systems for automating customer operations and collaborate on building models while ensuring high-quality code production.

Design, build, and operate production ML decision systems to detect and prevent payment fraud, account takeover, scams, and other abuse. Integrate diverse signals into low-latency serving and batch scoring, own feature pipelines and model lifecycle, develop AI-assisted triage and feedback loops, and partner cross-functionally to balance fraud reduction with legitimate customer access.

Design, build, and operate production ML systems that generate trusted signals for ranking, retrieval, recommendations, propensity/churn/LTV, and next-best-action decisioning. Define signal/data contracts, own feature and candidate generation through serving, experimentation, monitoring, and feedback loops, and evaluate long-term business impact, trust, fairness, and compliance. Partner across product, data, modeling, risk, and compliance and apply AI/agents to accelerate engineering and operations.

As a Senior Software Engineer, you'll develop core infrastructure for multi-agent systems, designing backend services and APIs for orchestration, collaborating across teams, and driving technical decisions in a dynamic environment.

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.

Independently validate and monitor machine learning models used for credit underwriting, credit risk, and fraud detection. Identify weaknesses, recommend improvements, and collaborate with model owners to remediate findings. Partner cross-functionally to implement and maintain the Model Risk Management framework and support audit, compliance, and regulatory requests.

Lead end-to-end personalization ML initiatives: build scalable ML pipelines, design CI/CD for models, monitor production performance, implement retraining and drift detection, partner with cross-functional teams, and mentor engineers.

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.

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.

As a Manager Research Analyst, you'll conduct quantitative and qualitative analysis on funds and investment vehicles, providing insights and ratings for investors while collaborating with a team dedicated to high-quality research.

Lead architecture and scaling of finance systems across Oracle Fusion and integrations. Drive AI-assisted development, design data models, build integrations (SQL/PLSQL, REST/SOAP), automate financial workflows, and translate accounting requirements into scalable technical solutions while partnering with business and data teams.

The Senior Infrastructure Software Engineer will build and manage a scalable, in-house search platform, ensuring seamless user experiences and expanding capabilities for a global user base.

Perform real-time incident detection and response across Windows, Mac, and Linux; conduct malware and forensic analysis; develop detection and remediation processes; produce clear communications and thought leadership; mentor teams and interact with customers.

The Staff Software Engineer - Applied AI will develop and integrate AI-powered systems and tools, driving innovation through experimentation and collaboration with cross-functional teams to deliver impactful solutions.

The Staff Analytics Engineer will develop and manage the Financial Subledger Data Platform using dbt and Snowflake, ensuring data quality, building models, automating workflows, and coaching an Analytics Engineer.

The role involves researching and developing large language models (LLMs) with a focus on transformer architecture, data curation, distributed training, and optimization. Responsibilities include conducting experiments, collaborating with teams, and staying updated on deep learning advancements.

Lead design, automation, and maintenance of cloud-based database infrastructure (primarily SQL Server and MySQL). Improve reliability with monitoring, HA/DR, automation, troubleshooting, on-call support, and mentoring of junior engineers while collaborating across teams.

Develop, launch, and maintain backend systems for card issuing and transaction processing. Break down projects, collaborate with product/design/analytics, write clear well-tested code, support operations and on-call duties, create/monitor metrics, perform code reviews, and participate in hiring and team growth activities.

Support transaction and sanctions monitoring programs by tuning alerts, designing analytical features, and optimizing data analysis processes to prevent financial crime.