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Lyft

Software Engineer, Growth Platforms (Backend)

Job Posted 15 Days Ago Reposted 15 Days Ago
Toronto, ON
Junior
Toronto, ON
Junior
As a Software Engineer at Lyft, you will design, develop, and maintain backend systems for growth platforms, utilizing distributed computing and machine learning to enhance user experiences.
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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.

Marketplace teams are at the heart of our products and decision-making. We’re looking for passionate, driven engineers to build systems that empower our users (both Drivers and Riders) to make the most effective use of Lyft’s products and experiences by making them more predictive, personalized, and adaptive. We’re looking for someone who is passionate about solving problems with distributed computing, ML, data alongside building reliable systems, and is excited about working in a fast-paced, innovative, and collegial environment.

As a Software Engineer, with your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance the platform offerings. Your work will have a major impact on several areas of the business.
We are looking for candidates who are self starters and have a proven track record of delivering software solutions that can solve critical business needs. The candidate should be able to dive deep into any problems with lots of ambiguity and build a technical solution to solve it. They should be willing to take ownership of a project or a feature and be able to drive it from design to implementation.

The Growth Platforms team owns both the Incentives & Messaging systems for Lyft. These systems determine & send the right messaging and/or incentives to the right user at the right time. We work with lyft-wide engineering teams including rider & driver side, marketing, and product management to adapt our services and the platform offerings to be able to enable growth across Lyft. You will gain comprehensive knowledge of Lyft's internal services and operations and adapt them to meet the growth needs. You will have the opportunity to improve the quality and efficiency by having optimizations via machine learning models to perform decisions at various critical aspects of the platform.

Responsibilities:

  • Design, develop, deploy, monitor, operate and maintain existing or new elements of our systems and infrastructure
  • Collaborate with engineers and partners in science & product to drive projects from inception, specification, execution, or to launch
  • Build and operate large-scale distributed systems
  • Help establish roadmap and architecture based on technology and our needs
  • Analyze our internal systems and processes and locate areas for improvement / automation
  • Write well-crafted, well-tested, readable, maintainable code
  • Unblock, support and communicate with internal partners to achieve results
  • Share your knowledge by giving brown bags, tech talks, and evangelizing appropriate tech and engineering best practices

Experience:

  • 2+ years of software engineering industry experience
  • BS/MS or equivalent in Computer Engineering, Computer Science, or related field or relevant work experience
  • Experience in backend software development of large-scale distributed systems, and/or experience with data infrastructure
  • Understanding of distributed systems concepts and principles (consistency and availability, liveness and safety, durability, reliability, fault-tolerance, consensus algorithms, etc)
  • Experience working with kubernetes and container technologies (e.g. Docker, cri-o, etc)
  • Familiar with using Python and cloud-based environments such as AWS/GCP/Azure

Benefits:

  • Extended health and dental coverage options, along with life insurance and disability benefits
  • Mental health benefits
  • Family building benefits
  • Child care and pet benefits
  • Access to a Lyft funded Health Care Savings Account
  • RRSP plan to help save for your future
  • In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy. The policy allows team members to take off as much time as they need (with manager approval). Hourly team members get 15 days paid time off, with an additional day for each year of service 
  • Lyft is proud to support new parents with 18 weeks of paid time off, designed as a top-up plan to complement provincial programs. Biological, adoptive, and foster parents are all eligible.
  • Subsidized commuter benefits

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 now if you wish to make such a request.

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. 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 $108,000 - CAD $148,000. 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.

Top Skills

AWS
Azure
Docker
GCP
Kubernetes
Python

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