Top Python Jobs in Toronto

As a Data Engineer, you will design and implement scalable data pipelines, support AI solutions, optimize performance, and collaborate with stakeholders for data provisioning.

Design, build, and scale data-driven platforms and systems, focusing on backend and frontend engineering, integrations, and AI capabilities.

The Senior Marketing Analyst will develop measurement frameworks for marketing campaigns, analyze media investment performance, and use advanced modeling techniques to optimize marketing strategies and reporting.

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

Manage AI compute clusters, monitor systems health, optimize resources, and troubleshoot technical issues, ensuring high performance for ML applications.

You will prototype and benchmark model innovations, develop automation for experiments, and work with teams on software/hardware integration.

As a Senior Software Engineer in Telematics, you will develop backend systems, lead projects, and enhance data insights for safety innovations at Lyft.

Design and maintain scalable data platforms and pipelines, optimizing workflows and ensuring data security while collaborating with stakeholders to deliver tailored solutions.

Support analytics and reporting by translating business questions into analytical requirements, analyzing data for trends and insights, building and maintaining dashboards and reports, documenting metrics, collaborating on data modeling, communicating findings, and improving reporting and data quality.

As a Senior Developer, you'll design, develop, and maintain software systems, mentor juniors, ensure code quality, and collaborate with teams for scalable solutions.

As a Staff Software Engineer, you will lead the development of backend systems for LLM applications, ensuring quality and scalability while collaborating closely with cross-functional teams.

Design and build complex web applications and scalable APIs across front-end and back-end. Implement UIs with modern frameworks, develop microservices, manage SQL/NoSQL databases, deploy containerized cloud solutions, and maintain automated testing and CI/CD pipelines while collaborating with clients and teams.

This role involves full-stack development, focusing on web products, architecture, and integrating AI. You'll work on product features and scalability in a collaborative environment.

Lead design and implementation of compliance control automation, conduct internal and external audits, manage risk and vendor assessments, create compliance metrics and reporting, collaborate with product and privacy teams, mentor junior staff, and support compliance readiness and monitoring.

The Sr. Manager will develop and implement risk reporting frameworks, ensure compliance with investment policies, provide in-depth risk analysis, and enhance data visualization tools to support risk discussions.

The Product Data Scientist will analyze user behavior, define product metrics, design experiments, and build dashboards to support data-driven product decisions.

Assist in designing AI conversation models for contact center agents, collaborating with various teams, and supporting project delivery.

As Payments Lead, you will drive technical direction and delivery of software solutions, oversee payments infrastructure, and ensure operational excellence.

The Product Analyst will support Product Managers by analyzing data to guide product decisions, improve user experience, and drive conversion and retention through strategic insights and recommendations.

As an Agile Test Engineer, you will design and execute testing strategies, leverage AI in testing processes, and collaborate with teams to ensure software quality across various applications.

The Data Solutions Consultant designs, builds, and applies data and machine learning solutions to support analytics and omnichannel initiatives, collaborating with multiple teams and delivering insights through data pipelines and model deployment.

The Machine Learning Engineer / Data Scientist will build and deploy machine learning solutions, working through the ML lifecycle from problem framing to production.

Lead the delivery of scalable kdb+ solutions for financial clients. Design robust architectures, mentor developers, and drive innovation in data management.

Develop and maintain kdb+ applications, analyze time-series data, mentor junior developers, and collaborate with teams to deliver solutions.

Lead development of web tools for autonomous driving, mentor engineers, and collaborate on technical architecture, focusing on responsive applications and cloud infrastructure.