Software Engineer, Telematics

Lyft · Toronto, Canadamid

In short

▸Ingeniero backend que procesa datos de sensores de móvil a gran escala para mejorar la seguridad vial.
▸Días típicos: construir pipelines de datos, trabajar con científicos de datos en modelos ML y mantener sistemas críticos en producción.
▸Destacado: impacto directo en la reducción de accidentes y costos de seguros a través de datos en tiempo real.

Proficiency in English is required for collaboration across global teams.

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What they ask for

✓4+ años de experiencia en ingeniería de software.
✓Experiencia en sistemas distribuidos a gran escala.
✓Conocimiento en Spark o arquitecturas de procesamiento masivo.
✓Interés o experiencia en desarrollo de bibliotecas.
✓Experiencia en despliegue, versionado y monitoreo de modelos ML en producción.
✓Capacidad para definir esquemas de API y desarrollar servicios backend.

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AWSKubernetesSparkApache AirflowPythonSQLDatabricksPrestoML model inferencemicroservices

Who should you write to at Lyft?

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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 back

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