Top Tech Jobs & Startup Jobs in Toronto

Owns end-to-end AV partner audits across multiple markets, coordinating evidence collection, compliance readiness, mitigation, corrective actions, and audit closeout. The role manages cross-functional stakeholders, improves audit tracking systems, develops repeatable playbooks, prepares teams for reviews, and reports risks and timelines to leadership. Candidates need program management or audit experience in regulated or standards-driven environments, strong documentation discipline, and familiarity with safety-critical industries such as autonomous vehicles, automotive, or aviation.

Architects and deploys AI agents, intelligent workflows, and enterprise integrations across business functions. Partners with stakeholders to identify AI opportunities, build ROI-focused business cases, and implement scalable solutions. Develops reusable frameworks, monitors workflow performance, leads training and enablement, builds an AI community of practice, and evangelizes agentic AI best practices. Requires extensive integration, automation, cloud, API, enterprise SaaS, LLM, RAG, and agent-framework experience.

Own domain datasets, data pipelines, business metrics, and quality checks that support Lyft’s marketplace decisions. Build reliable analysis-ready data, deliver metrics to stakeholders, and partner with product managers, engineers, and operators to translate data into action. Communicate analytical findings clearly and maintain trusted data products with executive visibility.

Build and maintain Lyft’s identity and account security systems, including login, signup, MFA, 2FA, email verification, SSO, session management, OAuth provisioning, device validation, RBAC, authorization, and multi-user management. Develop scalable microservices, prevent fraud and unauthorized account access, address social engineering and recycled-phone abuse, and balance verification security with user experience. Collaborate cross-functionally, document designs, promote engineering best practices, and mentor teammates.

Contribute to designing, training, testing, and deploying machine learning models and production pipelines. Collaborate with product managers, data scientists, and ML engineers to solve business problems, analyze data, communicate findings, and participate in code and specification reviews. The intern will apply research papers in working code, build efficient ML workflows, and develop high-quality software in a collaborative environment.

Conduct qualitative and quantitative UX research for Lyft drivers and riders using interviews, usability testing, field research, surveys, diary studies, and other methods. Analyze research data, develop actionable insights, and communicate recommendations that guide product and design improvements. Collaborate with Design, Product Management, Analytics, Engineering, and senior researchers while gaining mentorship and contributing to user-facing products.

Backend software engineering intern responsible for owning projects, writing and improving code, testing for reliability, participating in code reviews, and supporting continuous integration and deployment. The role requires strong computer science fundamentals, database experience, real-time technology problem-solving, and potential mobile development experience. The internship is based in Toronto during Summer 2027 with a hybrid in-office schedule.

Data Engineer Intern supporting large-scale data projects at Lyft. Responsibilities include owning an internship project, improving code quality, writing tests, participating in code reviews, and contributing to continuous integration and deployment. The role requires database experience, SQL and data modeling knowledge, strong computer science fundamentals, and effective communication. This hybrid Toronto internship is available during Summer 2027.

Software Engineer Intern working on full-stack, user-facing Lyft products. Responsibilities include developing and refactoring code, writing unit, integration, and load tests, participating in code reviews, and supporting continuous integration and deployment. Candidates should have web development experience with Python, JavaScript, React, TypeScript, databases, testing tools, browser technologies, and Git. The internship is based in Toronto during Summer 2027 on a hybrid schedule.

Data Science interns develop optimization, machine learning, and statistical models for Lyft’s transportation marketplace. Responsibilities include exploratory data analysis, production modeling code, algorithm implementation, simulated and live experiments, analysis of experimental and observational data, and communicating findings to cross-functional partners. Interns collaborate with engineering and product teams to support launch decisions.