Jobs at Lyft

Develop and launch backend software supporting Lyft’s airport operations and real-time communications. Responsibilities include designing and maintaining tested code, leading features from concept through deployment, participating in code reviews and on-call rotations, troubleshooting production issues, explaining technical tradeoffs, and managing project priorities and deliverables in a collaborative cross-functional environment.

Own Lyft Ads’ programmatic and audience extension go-to-market strategy, including positioning, packaging, pricing, deal structures, and measurement. Manage DSP, SSP, clean room, ad network, and measurement partners; lead negotiations, QBRs, joint business plans, and revenue accountability. Collaborate with Product, Engineering, Data Science, Sales, Finance, and external partners to build scalable advertising solutions, identify demand sources, monitor market trends, and drive programmatic revenue growth.

Develop and maintain foundational iOS infrastructure, networking, architecture, UI frameworks, and shared components used by Lyft mobile engineers. Collaborate across engineering and design teams to define mobile architecture, improve developer productivity, reduce development friction, support iOS engineers, and contribute to open-source projects. The role emphasizes scalable, reliable Swift code, clean APIs, mentoring, documentation, and leading projects from concept through completion.

Leads the technical direction, architecture, and development of scalable claims-management systems for Lyft’s insurance platform. Builds AI automation using multimodal LLMs, RAG pipelines, and agentic workflows to improve claims operations. Partners with Engineering, Data Science, Product, Claim Operations, and insurance providers; drives roadmap decisions, integrations, reliability, testing, code reviews, incident response, and engineering best practices.

Backend software engineering internship focused on owning projects, writing reliable and tested code, participating in code reviews, refactoring, and supporting continuous integration and deployment. Interns collaborate with experienced engineers and contribute to user-facing Lyft products. The role requires strong computer science fundamentals, database experience, familiarity with real-time technology and mobile development, and availability for a Summer 2027 hybrid internship in San Francisco.

Lead and grow a firmware engineering team developing embedded systems for e-bikes, scooters, batteries, docks, and charging infrastructure. Set technical direction for IoT, powertrain, battery management, OTA updates, diagnostics, safety, and fleet operations. Manage roadmaps, staffing, releases, hiring, and performance. Partner cross-functionally on product development, regulatory certification, reliability, and sustaining engineering while establishing CI/CD, HIL testing, code review, and incident response practices.

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

Designs, builds, and integrates ride-experience platforms and microservices. Develops and improves APIs, performance, monitoring, testing, validation, and documentation. Troubleshoots application and platform issues, contributes to architecture and technology roadmaps, and manages project priorities, deadlines, and deliverables.

Lead strategic sourcing and end-to-end procurement across indirect technology categories. Manage supplier relationships, negotiate complex contracts, deliver cost savings, develop category strategies, and improve sourcing processes through technology and data analytics. Responsibilities include market analysis, RFx development, supplier evaluation, stakeholder management, contract negotiation, and overseeing multiple projects.

Owner of pricing, yield, and sales compensation for Lyft Ads and Lyft Business. Set CPM floors, rate cards, and margin targets; oversee Audience Extension vendor performance; design and administer commission plans; build commission modeling infrastructure; coordinate adtech systems across Finance, Analytics, Sales, and Accounting.

Leads global B2B marketing strategy, operating model, martech systems, vertical go-to-market, demand generation, measurement, compliance, and executive partnerships across Lyft and partner brands. Builds unified pipeline, spend, ROI, and reporting infrastructure; directs multichannel campaigns, ABM, thought leadership, agencies, and co-marketing programs. Leads a matrixed international marketing team and establishes scalable governance across markets and brands.

Build and maintain Android mobile build, release, and developer productivity infrastructure for hundreds of mobile engineers. Lead projects and architectural reviews, improve automation and CI performance, develop tooling and AI agent workflows, maintain Android and dependencies, debug issues, write tested code, and mentor engineers. Collaborate across teams while supporting large-scale applications and open-source technologies.

Leads the systems, tooling, and technical roadmap supporting Lyft Ads and Lyft Business. Manages Billing Operations teams, prioritizes cross-business backlogs, partners with CRM Engineering and Sales Technology, and owns Salesforce, billing, quote-to-cash, RevOps, ad tech, acquisition, and new-market integrations. The role translates commercial requirements into product specifications, drives delivery, improves platform administration and data integrity, and oversees access governance and billing capacity decisions.

Manage enterprise customer relationships for Lyft Business, partnering with Fortune 500 organizations to design, sell, and implement transportation solutions. Drive account growth through upsells and cross-sells, maintain sales pipelines and forecasts, conduct business reviews, and develop account strategies. Collaborate cross-functionally with Product, Engineering, Marketing, Legal, and Sales Operations while representing customer needs and promoting Lyft Business products.

Lead Lyft's AI transformation for developer productivity by owning roadmap, prioritizing work, and delivering AI-native tooling and agentic workflows. Run cross-functional programs end-to-end, define success metrics and adoption goals, gather customer requirements, manage risks and stakeholders, and support engineering teams with technical judgment and on-call release duties.

Lead Lyft's M&A legal function, managing complex buy/sell-side and cross-border transactions, integrations, divestitures, financings, and joint ventures. Mentor and run an in-house M&A team, partner with Corporate Development, Treasury, and cross-functional stakeholders, draft and negotiate transaction documents, and scale legal processes and playbooks to support corporate strategy.

The Analytics Lead will analyze rideshare market trends, drive business strategies, and collaborate with cross-functional teams to identify growth opportunities.

Design, implement, and deploy machine learning models and systems for recommendations and related problems. Collaborate with engineers, data scientists, and product partners to analyze data, build proofs-of-concept, develop ML/optimization models, write production-quality code, and evaluate models against business goals.

Lead go-to-market strategy for Lyft's first-party audience data and measurement products. Translate backend signals, attribution models, and reporting into buyer-facing solutions; define pricing and packaging; drive adoption of attribution and reporting tools; and originate bespoke data partnerships. Collaborate cross-functionally with Product, Data Science, Engineering, Sales, Legal, and Finance to commercialize data, manage measurement partner relationships, and deliver ROI clarity for brands and agencies.

Develop and deploy production-grade ML and optimization models for pricing and ETA decisions. Partner with cross-functional teams to frame problems, build proofs-of-concept, productionize scalable pipelines, evaluate model performance against business metrics, and monitor system health. Drive collaboration to ensure robust, impactful solutions.