Meta Senior Machine Learning Engineer Interview Preparation Guide

Meta's Senior Machine Learning Engineer interview process consists of an initial recruiter screening, followed by two technical phone screens (one focused on coding and algorithms, one on ML fundamentals), and a comprehensive onsite loop with four rounds covering ML system design, advanced deep learning, coding under pressure, and behavioral assessment. The entire process evaluates candidates on technical depth, architectural thinking, problem-solving ability, communication skills, leadership potential, and cultural fit. Meta's evaluation focuses on engineers who can design scalable ML systems, own complex end-to-end projects, mentor team members, and demonstrate real-world impact. The process typically spans 4-6 weeks and includes assessment of proficiency with Meta's preferred frameworks (PyTorch), understanding of production ML infrastructure, and alignment with Meta's fast-paced, mission-driven culture.