At Lyft, our mission is to improve people’s lives with the world’s best transportation. To do this, we start with our own community by creating an open, inclusive, and diverse organization.

Lyft’s core mission depends on having a digital representation of the physical world - a map with all routing related (real-time) information - and the ability to use that map in order to provide the world’s best transportation. This is what makes Lyft different from many products: our products don’t just facilitate online interactions, they facilitate dynamic, real-world ones. These interactions range from finding the closest scooter, to being late and trying to choose between a train or a bike, to navigating through a congested city safely and swiftly, to a shared ride involving picking up two different passengers. Without mapping services, none of these real world interactions between people and transport can happen.

The Mapping organization at Lyft has spent the last few years building up Lyft’s mapping assets and capabilities by combining many internal and external data sources and services into an increasingly powerful and mission-critical technology stack. In doing so, we’ve also enabled new user experiences and features across all of Lyft’s products. We’re hiring a (Senior) Software Engineer to help drive our efforts to build machine learning based data pipelines to build new and powerful mapping experiences for Lyft’s users and services.

You'll collaborate with engineering, product, data science, analytics, and operations on programs that empower us to iterate quickly, delighting our passengers and drivers with real-time information about traffic, events, weather, etc.

 

Responsibilities:

  • Work on high-impact projects and innovate new solutions to provide the best mapping experience possible
  • Build and deploy mission-critical data pipelines that can serve thousands of requests per second
  • Help establish roadmap and architecture based on technology and our needs
  • Work on distributed systems that process and transform large quantities of data
  • 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 machine learning models
  • Build tools and dashboards to provide visibility to other teams

Experience:

  • 2+ years of professional software engineering experience
  • Extensive experience in one of Python / Go / C++
  • Hands-on experience with cloud computing using AWS, GCP or Azure
  • Experience with workflow orchestration tools such as Apache Airflow, Flyte
  • Strong verbal and written communication skills with proven ability to uplift others and work effectively with a diverse group of talented engineers in different locations (Munich, Minsk, Kyiv, Seattle, San Francisco)
  • Nice-to-have: Experience building distributed data pipelines
  • Nice-to-have: Experience building microservice-based architectures
  • Nice-to-have: Experience with containerization (e.g. Docker, Kubernetes)

Benefits:

  • Pension scheme with 4% employer contribution
  • Risk and Accidental Death & Dismemberment benefits
  • Mental health benefits 
  • 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
  • 30 days for paid time off

Lyft proudly pursues and hires a diverse workforce. Lyft believes that every person has a right to equal employment opportunities without discrimination because of race, ancestry, place of origin, colour, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, disability, pardoned record of offences, or any other basis protected by applicable law or by Company policy.  Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind.  Accommodation for persons with disabilities will be provided upon request in accordance with applicable law during the application and hiring process. Please contact your Recruiter if you wish to make such a request.

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