Jobs at Lyft

Build and maintain frontend services and components for Lyft's micromobility operations tooling. Define roadmap and architecture, write well-tested maintainable code, lead projects, participate in code reviews and incident response, collaborate with cross-functional teams, and evangelize engineering best practices to improve operator workflows and platform performance.

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.

Develop and maintain scalable Swift-based iOS applications used by millions of users. The role involves establishing architecture and technical roadmaps, writing tested and maintainable code, conducting code reviews, documenting designs, mentoring junior engineers, participating in hiring, and collaborating with designers and product managers.

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 Lyft Product Language (LPL) design system strategy, team, and execution across mobile, web, and brand. Manage and develop design systems designers and illustrators, ensure cross-platform coherence, accessibility (WCAG), localization, and quality. Partner with engineering and product to own component contribution, review, and release processes, and drive AI-enabled tooling and adoption.

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.

Manage execution of airport-focused programs and product configurations, support compliance workflows, assist launches and QA, monitor performance with analytics, own assigned projects end-to-end, troubleshoot issues, and drive process improvements in coordination with Engineering, Product, and cross-functional partners.

Owner of forecasting and capacity models for global customer support; translate complex data into actionable staffing plans, maintain dashboards and reports, leverage AI tools to accelerate analysis, and partner with operations leadership to align resourcing and improve planning processes.

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.

Support driver earnings and marketplace teams with SQL-driven analysis, reporting, and financial reconciliation. Provide insights, track product performance, support experiments, prepare leadership business reviews, and develop processes and playbooks to improve earnings products and reduce errors.

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.

The Technical Learning Manager at Lyft will oversee technical learning programs, ensure integration with HR functions, and enhance ongoing education for engineering and tech teams, while fostering relationships across departments.

Lead Planning & Central Operations for Customer Care, overseeing forecasting, workforce management, vendor relationships, readiness for product launches, financial discipline, and cross-functional integrations. Build staffing and capacity models, drive investment cases and OKRs, manage BPO governance and SLAs, and hire and develop teams to scale support operations and AI-driven transformation.

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.

Manage and mentor a growing team of engineers, prioritize projects, ensure high-quality deliverables, and foster an inclusive work environment.

Lead design and ownership of the Salesforce-based Ads CRM and connected commercial systems. Scope and deliver integrations (OMS, ad server, billing), maintain platform reliability and SOX-compliant order-to-cash, drive AI best practices, mentor engineers, and partner with Ads, Finance, Legal, and Ops on roadmap and delivery.

Build and lead mapping-focused features using Lyft's in-house navigation system. Design, implement, test, and operate scalable, fault-tolerant distributed systems in cloud environments. Collaborate with product, data science, analytics, operations, and AI/ML teams; own features from design through launch; participate in code reviews and on-call rotations; share knowledge via talks and mentoring.

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.

Perform financial analysis, budgeting, forecasting, reporting, and variance analysis to support business decisions. Partner with cross-functional teams, build models and dashboards, and communicate insights to stakeholders to inform strategy and operational improvements.