Top Tech Jobs & Startup Jobs in Toronto

Build backend infrastructure and APIs to integrate Lyft with emerging AI ecosystems and devices. Design scalable distributed systems, mentor engineers, drive high-impact projects, write and review maintainable code, participate in on-call rotation, and collaborate cross-functionally to deliver production-grade AI-enabled features.

Lead analytics for Safety & Customer Care by partnering cross-functionally to define metrics, build dashboards, design and analyze A/B tests, monitor KPIs, and deliver data-driven recommendations to improve customer support experience and inform senior leadership.

Serve as the bridge between People teams and engineering to architect AI-first HR/People solutions. Define roadmaps, design business processes, write requirements/user stories, and guide integrations across Workday, ATS, and boundary apps. Drive AI-enabled automation, responsible AI frameworks, ROI cases, data/privacy compliance, and support M&A People systems integration while influencing stakeholders and ensuring delivered solutions meet business objectives.

Lead a cross-functional engineering team spanning iOS, Android, and server platforms. Own the membership and rewards platform, including roadmap strategy, architecture, reliability, observability, technical debt, and on-call operations. Partner with Product, Design, Data Science, Partnerships, and Rider Pay to scale consumer loyalty products. Develop engineers through goal-setting, opportunity matching, and timely feedback.

Design and implement scalable, low-latency backend systems for Lyft Pricing. Lead multi-person projects, write maintainable and tested code, mentor teammates, participate in incident response, and collaborate with Product and Science on pricing solutions.

Own global support workforce forecasting, capacity, and scheduling models. Translate complex demand data into staffing plans, dashboards, reports, and leadership recommendations. Partner with BPO providers, execute day-to-day planning, maintain accurate reporting, identify operational improvements, and use SQL, Python, and AI tools to accelerate analysis and decision-making.

Build and scale backend systems for Lyft’s Recommendations team, including pipelines and services that use rider context and signals to surface relevant offers. Responsibilities include system design, coding, code reviews, on-call support, project delivery, engineering best practices, mentoring, and promoting AI-assisted development. The role requires Python and Go, cloud platforms, distributed systems, databases, and strong collaboration skills, with bonus experience in ML serving, recommendation systems, feature stores, or experimentation.

Lead technical integration of acquired companies into Lyft's IT environment, migrating SaaS and identity systems (Okta), automating workflows and APIs, writing runbooks, and partnering with IT, Security, and vendors to ensure smooth M&A platform consolidations.

Lead the RTB reporting sub-team to ensure accurate, reliable finance and compliance reports. Build repeatable processes, documentation, and automation; own stakeholder relationships; mentor juniors; and drive cross-functional reporting initiatives from definition through execution.

Operate, maintain, and improve Lyft's logging and metrics infrastructure. Build tooling to automate platform operations, define SLOs, monitor metrics, support incident response and on-call rotations, collaborate with engineering teams on observability, document processes, and automate repetitive tasks to improve reliability and scalability of distributed systems.