Software Engineer, Telematics

Socket.dev; Toronto; Hybrid; CAD 108,000 - 135,000; Full time

Benefits offered by this job

Extended health and dental

Mental health benefits

Family building benefits

Child care and pet benefits

Health Savings Account

RRSP with company match

Flexible PTO

Paid parental leave

Commuter benefits

Ride credits

Job summary

Lyft is seeking a backend software engineer for its Toronto team on a hybrid schedule. The role focuses on Telematics data pipelines, scalable services, and risk features to inform driver safety and insurance strategy.

You will collaborate with data scientists, product managers and engineers to productionize models, reduce latency, and improve back-end and on-device predictions for real-time use cases in a large distributed system.

Qualifications

• 4+ years of software engineering experience.
• Backend development for large-scale distributed systems.
• Experience with Spark or large-scale batch processing.
• Experience with library development and ML model monitoring/serving.
• API schemas and microservices backend experience.
• Experience with S3, Spark, Presto, Parquet, Databricks.
• Excellent communication and cross-functional collaboration across geos.

Responsibilities

• Be a champion of safety and affordability mission, delivering risk insights across Lyft teams.

Skills

Backend development

Distributed systems

Python

AWS

Spark

SQL

Databricks

Presto

Parquet

Communication

Cross-functional collaboration

Tools

S3

Spark

Presto

Parquet

Databricks

Job description

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.

We are looking for an experienced backend software engineer to join our Road Safety & Telematics team. At Lyft, Telematics data is used to make Lyft safer by reducing the frequency and severity of accidents, which in turn also makes Lyft more affordable for riders and a better way to earn a living for drivers. The Telematics team acts as a platform team that processes petabytes of mobile sensor data — millisecond-level IMU, gyroscope, and GPS signals — through a series of DAG-based transformations and ML model inferences to detect harsh driving events and convert them into normalized risk features that other Lyft services consume.

Our technology stack runs on AWS, Kubernetes, Spark, and Apache Airflow. In this role, you'll work closely with data scientists, actuarial teams, other backend and data engineers, and product management — partnering across geos to build risk-aware products that rank and reward safe drivers, help off-board unsafe ones, notify drivers in real time, and give claims agents the tools to understand exactly what happened in a ride. You'll also be a key technical partner to our insurance team as they optimize coverage costs and provider relationships.

If you are a seasoned engineer with a passion for innovation, high-volume data pipelines, microservices, working in cross-disciplinary environments and possess the skills to ensure the ongoing maintenance and improvement of services, you will thrive on our team!

You can read about some of the products that Telematics powers in this blog post: https://www.lyft.com/blog/posts/lyfts-impact-on-road-safety

Responsibilities:

• Be a champion of the team's safety and affordability mission, serving as a reliable source of risk insights for teams across Lyft — from driver ranking and safety rewards to accident claims resolution and insurance strategy.
• Lead medium to large projects, ensuring end-to-end execution with a focus on high quality and reliability.
• Work cross-functionally with Data Scientists to productionize models that turn raw sensor signals into harsh-event detection and risk features, driving the team's industry-leading innovation in this space.
• Drive future work to reduce latency, simplify, and improve the accuracy of both our back-end and on-device models that predict accidents before they happen.
• Actively unblock and support team members, fostering a collaborative and efficient work environment.
• Take a lead role in the ongoing maintenance of our Telematics systems, reducing tech debt and operating costs through sensible, data-driven design decisions.
• Collaborate with product management and leadership across geos to define and execute ambitious roadmaps for Telematics.
• Apply the latest AI tools to boost engineering and business productivity, sharing what you learn with the team.
• Utilize your expertise in Python, AWS, Spark, SQL (Databricks/Presto), etc. to deliver robust and scalable solutions.
• Participate in our team's on-call rotations, respond to incidents, and support other teams in mitigating customer-impacting events.

Experience:

• 4+ years of software engineering industry experience
• Experience in backend software development of large-scale distributed systems
• Experience and/or interest in running large batch processing jobs with Spark or other large scale compute architectures
• Experience and/or interest in Library development
• Experience and/or interest in serving, versioning, monitoring ML models in production environments
• Experience defining API schemas and developing backend services in a microservices environment
• Experience with S3, Spark, Presto, Parquet, Databricks
• You're a great communicator, and can advocate for your proposals while also empathizing with your cross-functional teammates' goals and priorities
• You collaborate well with a geographically distributed team

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 with company match 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 and Lyft ride credits

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 $108,000 - CAD $135,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

Lyft may use artificial intelligence to screen applicants, however, Lyft employees make the ultimate selection and hiring decisions.

This job fills an existing vacancy.