Machine Learning Engineer, Fulfillment

<p>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.</p> <p>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, Driver, Marketplace, 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 petabyte-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.</p> <p>The Fulfillment group, within the Marketplace at Lyft, is responsible for determining what inventory can be reliably offered for a given rider session and fulfilling rider requests. The group comprises several sub-teams that generate feasible offers for riders, match rider requests with drivers, and maintain a distributed state machine to track rides and drivers from request through completion.</p> <p>We are seeking a Machine Learning Engineer to join the Fulfillment team and lead the design, development, and deployment of state-of-the-art machine learning 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 machine learning and data science.</p> <h2><strong>Responsibilities:</strong></h2> <ul> <li>Design, build, and deploy machine learning models for real-time applications, including translating state-of-the-art research into production-ready solutions</li> <li>Design and implement feature pipelines, model training workflows, and serving infrastructure using Lyft's ML platform</li> <li>Evaluate ML system performance against business KPIs, run experiments, and drive continuous model improvement</li> <li>Partner with ML engineers, product managers, data scientists, and software engineers to align ML initiatives with business goals</li> <li>Leverage data-driven insights to inform and refine ML strategies and solutions</li> <li>Write production-level code and participate in code reviews to ensure quality and share knowledge across the team</li> </ul> <h2><strong>Experience:</strong></h2> <ul> <li>BS/MS in Computer Science, or a related field</li> <li>2+ years of experience in machine learning modeling or related fields</li> <li>Experience with deep learning technologies for recommendation systems, including TensorFlow, PyTorch, or similar frameworks</li> <li>Understa