The interview process consisted of an initial recruiter screen followed by a technical phone interview focused on data structures and problem-solving in Python. The onsite loop included 4 rounds: one coding round (medium LeetCode-style problem), one system design round focused on building a scalable ML data processing pipeline, one backend/API design round, and one behavioral round. Interviewers emphasized real-world problem solving, tradeoffs, and communication. Overall, the process was structured and aligned with large-scale distributed systems and ML infrastructure.