Top Tech Jobs & Startup Jobs in Toronto

Investigate and mitigate third-party fraud by developing detection strategies, real-time rules, dashboards, and customer-friendly policies. Collaborate with product, data science, engineering, and operations to prioritize, implement, and measure fraud prevention while balancing user experience.

As a Data Analyst in People Analytics at Lyft, you'll manage data requests, build ThoughtSpot dashboards, and enhance insights using AI capabilities. You'll collaborate with HR to craft metrics and translate findings into actionable insights for leadership.

Lead backend and cross-functional projects for Lyft's Pickup, Places and Search mapping team. Design, build, and operate fault-tolerant, large-scale distributed systems, own components end-to-end, write well-tested code, conduct architecture reviews, mentor engineers, and collaborate with product, data science, and analytics to improve rider and driver pickup/dropoff experiences.

Lead multiple managers and staff engineers across iOS, Android, and server teams to define technical vision and deliver Rider Loyalty, Partnerships, and Rider Pay products. Coach managers and engineers, collaborate cross-functionally with Product, Design, Data Science, and Analytics, hire diverse talent, and drive scalable consumer-facing solutions to production while ensuring high product quality and business impact.

As a Senior Analyst, you will leverage data for Lyft's global expansion strategy, collaborating on product enhancements and growth opportunities, while analyzing impacts on users and markets.

Design, build, and maintain core data pipelines and models for Lyft's Safety and Customer Care platform. Scale processing, tune Spark/SQL/MapReduce jobs, implement data quality systems, enable self-service ETL tooling, and collaborate with product, engineering, and analytics teams to deliver reliable reporting and insights.

Lead design and implementation of AI-driven data analytics platforms and pipelines for Lyft's Marketplace. Define architecture and roadmap, build backend microservices and APIs, drive AI innovation (agentic workflows, model evaluation, causal models, anomaly detection), collaborate with product and data teams, resolve incidents, and mentor engineers to improve business operations and metrics governance.

Design, build, and deploy production ML systems across pricing, marketplace optimization, fraud and behavior detection, and agentic LLM applications. Own models end-to-end, implement feature pipelines and serving infrastructure, evaluate performance against KPIs, run experiments, and collaborate with data scientists and engineers to scale ML solutions for Lyft Business.

The Software Engineer at Lyft will innovate user solutions, lead features, and collaborate with cross-functional teams to improve ride and driver experiences using Python, Golang, and AWS.