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An established industry player is seeking a Staff Software Engineer to join a dynamic Mapping team. This role focuses on enhancing the Lyft map, crucial for navigation and ensuring seamless pickups. You will leverage your expertise in microservices, cloud computing, and big-data processing to build scalable solutions. Collaborate with passionate colleagues from diverse fields to create exceptional rideshare experiences. Enjoy a hybrid work environment with flexibility and a range of generous benefits, including comprehensive health coverage and flexible paid time off. Join us in shaping the future of mapping technology!
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.
We are seeking a Staff Software Engineer to join our Mapping Pickup XP team. The Lyft map serves as the backbone of Lyft's navigation system, supporting millions of rides by furnishing precise details about the road network. Our focus is on ensuring safe, seamless and convenient pickups, offering differentiated value additions that set us apart. We own and support critical infrastructure like geocoder, rev-geocoder, generating algorithmic pick-up and drop-off locations. The objective is to provide safe and convenient pickup and dropoff locations that will later be used for optimal route planning in terms of speed, cost-effectiveness, and safety. This involves processing a vast volume of ride data, road network data, and real-time events to facilitate timely and precise access to essential information.
We are looking for an engineer with proven expertise in system architecture, microservices, and big-data processing and experience in building scalable solutions in the cloud environments.
Our technology stack runs on AWS, Kubernetes, Spark and Apache Airflow. In this role, you will work with incredibly passionate and talented colleagues from software engineering, machine learning and data science on building rideshare experiences that delight millions of riders and drivers.
If you are a seasoned engineer with a passion for innovation, microservices, and possess the skills to ensure the ongoing maintenance and improvement of services, we invite you to join our dynamic team. Apply now to be part of an exciting journey in the world of mapping technology.
Lyft is committed to creating an inclusive workforce that fosters belonging. 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.
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 at least 3 days per week, including 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 perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid
The expected base pay range for this position in the Toronto area is CAD $172,000 - $215,000. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Range is not inclusive of potential equity offering, bonus or benefits. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.