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Senior Machine Learning Engineer, Rider Applied AI

LyftToronto, Canada
Full-timeSenior
👁️ 16 views📝 0 applicationsPosted 6/23/2026Expires 9/7/2026
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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. With a billion rides per year and counting, Lyft is solving hard problems in a rapidly growing domain with a lot of data and creative solutions in Rider, Marketplace, Growth, and beyond. While traditional approaches to optimization and problem decomposition are sufficient to disrupt transportation, building a next-generation platform for low-cost, ultra-immersive transportation to improve people's lives warrants modern ML utilizing peta-byte scale data. Our highly motivated Machine Learning Engineers work on these challenging problems and define solutions to directly impact various aspects of our core business. If you are a critical thinker with experience in machine learning workflows and LLMs, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you. We are seeking a Senior Machine Learning Engineer to join the Rider Applied AI team and lead the design, development, and deployment of state-of-the-art machine learning and artificial intelligence systems. This role requires a strategic thinker who can balance high-level system architecture with hands-on technical implementation. You will collaborate across teams to shape the future of ride-sharing by leveraging AI, Machine learning and Data science. Responsibilities: Model Development: Design, build, train, and deploy machine learning models for real-time applications. System Design: Architect scalable, reliable, and maintainable machine learning pipelines, integrating seamlessly with existing backend systems. Collaboration: Work closely with machine learning engineers, product managers, data scientists, and software

Required Skills

AWSCross-functional CollaborationData ScienceDockerGCPHadoopKubernetesLeadershipLife InsuranceMachine LearningNext.jsPyTorchSparkTensorFlow

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