Machine Learning Engineer, Fulfillment

Overview In this role you join Lyft’s Fulfillment team to shape how offers are generated and rider–driver matching with ML at scale. You will design and deploy real-time ML models, build feature pipelines, and maintain serving infrastructure on Lyft’s ML platform. Your work will be judged against business KPIs and you’ll run experiments to continuously improve models. You will collaborate with product managers, data scientists, and engineers to align ML initiatives with company goals and leverage data-driven insights to influence strategy. This is a hands-on role that combines system design with practical implementation to impact ride-sharing at scale. Compensation / Benefitsmedical, dental, and vision insurancemental health benefitsfamily building benefitspaid time offpaid parental leave401(k) plan with company match ResponsibilitiesDesign, build, and deploy real-time ML models and production-ready solutionsCreate feature pipelines, training workflows, and serving infrastructureEvaluate model performance against business KPIs, run experiments, and iterateCollaborate with ML engineers, data scientists, product managers, and software engineers to align ML work with business goalsLeverage data-driven insights to refine ML strategies and outcomesWrite production-level code and participate in code reviews to share knowledge Key requirementsBS in Computer Science or related field; MS preferred2+ years of ML modeling experienceExperience with deep learning for recommendation systems (TensorFlow, PyTorch or similar)Understanding of statistics (hypothesis testing, regression, metrics)Experience translating research into production systemsProficiency in Python, Golang, or other programming languagesProven ability to tackle ambiguous problems and deliver scalable solutionsStrong communication and cross-functional collaboration skillsstrong communicationcross-functional collaborationproblem-solving in ambiguityTensorFlowPyTorchPython