Jobs at Lyft

Owns indirect tax accounting, compliance, reporting, audit defense, tax research, and risk resolution across multiple jurisdictions. The role develops tax strategies, reviews reconciliations and returns, improves and automates workflows using Excel and Alteryx, coordinates with engineering and business teams, and mentors junior tax professionals.

Build and maintain backend systems, scalable data models, and large-scale pipelines supporting ad serving, campaign management, reporting, targeting, and measurement. Design reliable workflows using orchestration tools, integrate internal and third-party systems through APIs and batch feeds, and develop clean, testable code. Collaborate with product, analytics, data science, and operations teams on architecture, performance, observability, and reliability while developing expertise in distributed systems and data engineering.

Build and maintain backend features for Lyft’s Growth Platforms, including incentives and messaging systems. Responsibilities include designing distributed services, writing reliable and tested code, debugging production issues, improving system performance and observability, participating in code reviews and on-call rotations, and collaborating with product, design, data science, and engineering teams. The role requires 3–5 years of backend software engineering experience and familiarity with cloud infrastructure, databases, APIs, asynchronous processing, and CI/CD.

Own the vision, roadmap, and success metrics for Lyft’s base pricing systems. Lead pricing optimization across ride types, markets, and real-time dynamic pricing, while improving cost and impact models. Partner with engineering, data science, analysts, and market teams to define requirements, prioritize work, run experiments, and communicate decisions to executives. The role requires deep understanding of economic levers, marketplace dynamics, experimentation, SQL, and data-driven product development.

Own lifecycle growth marketing strategy, experimentation, channel prioritization, performance reporting, and creative strategy across email, push, SMS, and in-app messaging. Partner with Product, Engineering, Analytics, Data Science, and Marketing Operations to develop platform capabilities, optimize personalized customer journeys, and use behavioral science and incentives to drive engagement, retention, and usage.

Supports actuarial data pipelines, monitoring dashboards, modeling, reserving, pricing, financial reporting, and competitive analysis for auto insurance products. The role collaborates with Engineering, Data Science, Operations, Finance, Legal, and Public Policy teams, maintains accurate actuarial data, contributes to process improvements, and delivers insightful analysis. Strong SQL, insurance actuarial experience, and coding or automation skills are important, with support provided for FCAS exam development.

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.

Lead end-to-end product design for Lyft Mapping, including driver navigation, real-time feedback, voice AI, map styling, 3D views, and internal mapping tools. Partner with product, engineering, research, marketing, data science, and content teams to solve complex problems, build reusable design systems, maintain high quality standards, and guide experiences through implementation and launch.

Leads global customer-care workforce planning, forecasting, scheduling, capacity management, queue performance, workforce budgeting, and outsourced partner relationships. Owns staffing metrics, BPO contracts and billing, business continuity, site strategy, and investment cases. Partners with Finance, Product, Technology, and Support Operations to anticipate demand, improve productivity, manage costs, and prepare for launches and AI-driven changes. Builds and leads internal workforce teams while improving WFM tools, automation, reporting, and operational resilience.

Leads 6–8 engineers building and operating Lyft’s high-scale dynamic pricing and ride offer selection systems. Owns roadmap execution, architecture, model productionization, reliability, SLAs, incident escalation, technical debt, hiring, performance management, and team development. Partners with Product, Science, Analytics, and senior stakeholders to balance technical, product, and business priorities.

Designs and operates Lyft’s foundational networking infrastructure, including service mesh, routing, ingress and egress systems, and control planes on AWS and Kubernetes. The role focuses on scaling high-throughput distributed systems, improving observability and reliability, debugging complex production incidents across networking layers, and providing technical leadership through architecture reviews, incident response, and mentorship.

Analyze marketplace trends, financial and product levers, budgets, and competitive insights to support Lyft’s Rideshare growth strategy. The role develops forecasting, reporting, business reviews, recommendations, and execution plans while partnering with cross-functional stakeholders and leadership. It requires strong SQL, quantitative analysis, communication, attention to detail, and the ability to improve processes and operate effectively amid ambiguity and change.

Analyze spatial and product data to improve Lyft’s mapping, routing, and travel-time estimation products. The role designs online experiments, develops performance metrics and analytical frameworks, identifies growth and efficiency opportunities, and translates insights into product and business decisions. The Data Scientist partners with engineers, product managers, and operators while communicating recommendations to senior stakeholders. Responsibilities also include monitoring rider and driver experience and applying statistical analysis, programming, visualization, and machine learning techniques.

Supports finance technology applications across ERP, HCM, procurement, supply chain, and FP&A. Builds automation workflows using Workato and Python, writes SQL queries, validates data, prototypes AI solutions, configures Jira automation, develops reports, tests integrations, gathers requirements, and provides user support. The intern collaborates with finance, HR, IT, and engineering stakeholders while learning agile methods, systems integration, and finance transformation.

Own Salesforce enterprise architecture across multiple orgs, including acquired-company CRM consolidation, data migration, integration, and multi-org governance. Define scalable Salesforce solutions, data models, security, sharing, and integration patterns; guide engineering standards, CI/CD, testing, and platform adoption. Partner with Sales, RevOps, Marketing, Finance, Privacy, Legal, and Security on architecture, compliance, and GTM systems. Mentor teams and lead strategic programs involving middleware, identity resolution, data harmonization, and legacy-system decommissioning.

Support Lyft’s internal content system by developing information architecture, improving publishing workflows, and creating connected content experiences. Partner with design, research, engineering, marketing, and product teams on UX writing and learning design projects. Translate complex concepts into clear UI copy, notifications, errors, and educational materials while maintaining Lyft’s brand voice. Manage multiple projects, evaluate strategy and metrics, and contribute to content systems across the UI, learning center, and knowledge base.

Develop and maintain scalable, fault-tolerant software for Lyft’s Rider organization. Responsibilities include writing tested code, participating in code reviews and on-call support, debugging distributed systems, managing project deliverables, collaborating with product and engineering teams, improving processes, establishing architecture and roadmaps, and mentoring junior engineers.

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.

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.