Lyft Machine Learning Engineer Interview Preparation Guide - Entry Level

Lyft's Machine Learning Engineer interview process for entry-level candidates consists of 7 rounds conducted over approximately 4-6 weeks. The process begins with a recruiter screen, followed by two technical phone interviews covering coding and machine learning fundamentals, and concludes with four onsite rounds evaluating system design, computer science fundamentals, practical ML problem-solving, and cultural fit. The interview emphasizes practical machine learning implementation, real-time data processing, scalable model deployment, and collaboration with cross-functional teams to solve Lyft's transportation challenges.