At Lyft, our purpose is to serve and connect. To do this, we start with our own community by creating an open, inclusive, and diverse organization.
Our transportation network serves millions daily, relying on a map that reflects the constantly changing real world. Our systems leverage insights from driving locations, sensor data, and user feedback to provide the best possible service. This empowers us to optimize routes, recommend ideal transport modes, ensure safe drop-off locations, and much more.
To strengthen our efforts, we are hiring a Senior Software 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.

EXPERIENCE:

• BS/MS or equivalent degree in Computer Science, Machine Learning, or a related field.
• 5+ years of proven work experience in software engineering.
• Extensive experience with Python (including its data related batteries like numpy or pandas).
• Familiarity with cloud platforms such as AWS and/or GCP, including experience with cloud infrastructure.
• Excellent communication and collaboration skills with experience working in cross-functional teams.
• Excellent analytical and problem-solving skills with a passion for tackling complex challenges.
• Proven track record of proactively driving initiatives, taking ownership of projects, and independently identifying and implementing improvements.
• Advantageous would be:
• Experience with MLOps processes
• Familiarity with geospatial data processing, GIS frameworks, or mapping infrastructure
• Familiarity with Go

• Design, develop, deploy, monitor, operate and maintain scalable, robust, stable, reliable and performant systems to support map data pipelines that operate on large data sets.
• Provide technical leadership and direction to the team by defining the team’s roadmap, architecture, processes, and best practices, with a focus on scalability and robustness in data pipeline design and implementation for large geospatial datasets.
• Analyze our internal systems and processes, locate areas for improvement/automation, and build tools and dashboards to provide visibility.
• Write clean, testable, and maintainable code while implementing best practices for code reviews, CI/CD pipelines, and system observability.
• Help establish technical roadmaps and architectures based on technology and our business needs.
• Drive high-impact projects and innovate new solutions to provide the best mapping experience possible.
• Ship ML models at scale and low cost by focussing on systems / performance engineering.
• Create resilient and scalable infrastructure that enables rapid iteration of new pipelines and machine learning models.