Senior ML Software Engineer, Mapping

About the role

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The Mapping team is tasked with building a digital representation of the physical world - a map. We collect and serve the freshest and most accurate mapping data possible, along with algorithms, model's, platform services, and map-based user experiences that power Lyft's current and future transportation offerings. Mapping represents a huge opportunity for Lyft's business, but also a big challenge. We build and scale systems that deal with large data storage, real-time data processing, machine / deep learning pipelines, routing and ETA models, driver and passenger location tracking, and more. We have built beautiful and magical user experiences on top of all those services, and compete with companies that have been in the mapping business for decades.

We are hiring a Senior ML Engineer who will work end-to-end on creating and improving new capabilities to detect changes in the environment and reflect them in our Lyft map using a wide variety of input sources from the Lyft fleet. For this we are looking for someone who values software engineering best practices, loves the algorithmic and geospatial side of the challenge and is data-driven from start to end. Our technology stack ranges from basic machine learning models to large language models and running them at scale on millions of images. You will work with incredibly passionate and talented colleagues from machine learning, data science, and engineering on projects that delight our passengers and drivers - powered by an up to date map.

This role is based in San Francisco, CA and follows our standard engagement policies as outlined in our official sources.

What you'll do

• Analyze large and complex data sets from the Lyft fleet to identify mapping discrepancies and opportunities for improvement using statistical and machine learning techniques.
• Design and develop machine learning pipelines that ingest, process, and transform diverse data sources such as GPS traces, images, and sensor feeds into actionable map updates.
• Build and maintain scalable data processing systems using Golang and Python to support real-time and batch workflows across distributed infrastructure.
• Implement and optimize algorithms for change detection, object recognition, and map validation to ensure high precision and recall in dynamic urban environments.
• Collaborate with data scientists to prototype, evaluate, and iterate on models before translating them into production-grade services with strict latency and reliability requirements.
• Work with product managers to define success metrics and validate that machine learning initiatives are driving measurable improvements in mapping quality and user satisfaction.
• Partner with cross-functional engineering teams to integrate mapping models into Lyft's core services, including routing, ETA, and driver navigation experiences.
• Evaluate the performance and cost of machine learning systems in production, applying techniques such as A/B testing, monitoring, and root cause analysis to continuously improve outcomes.
• Champion software engineering best practices, including code review, testing, documentation, and modular design, to ensure long-term maintainability and scalability.
• Stay current with advances in machine learning, geospatial technology, and large language models, and proactively propose innovative solutions to complex mapping problems.

Requirements

• B.S., M.S., or Ph.D. in Computer Science or other quantitative fields or related work experience.
• 5+ years of Machine Learning experience.
• Passion for building impactful machine learning models leveraging expertise in one or multiple fields.
• Proficiency in Python, Golang, or other programming language.
• Excellent communication skills and fluency in English.
• Strong understanding of Machine Learning methodologies, including supervised learning, forecasting, recommendation systems, reinforcement learning, and multi-armed bandits.
• Ability to work effectively in a fast-paced, collaborative environment where priorities can shift based on business needs and technical constraints.
• Commitment to writing clean, efficient, and well-tested code that can scale to process millions of data points daily.

Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law. Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule - Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office options.