Real, anonymous reports from people who interviewed for Mobile Engineer at PayPal, newest first and distilled into what to expect across the loop.
I started with the usual recruiter handoff and then moved into a Karat coding stage where the format was fairly straightforward but the overall bar felt high. After that, my path became a multi-round loop: there was a mix of coding and systems-style thinking plus behavioral, with interviewers who stayed professional and would clarify anything that wasn’t clear from my explanations.
After a recruiter intro call, I got routed to Karat for the first technical step. That screen was about an hour and felt tightly structured: there was an iOS-focused fundamentals portion covering things like Swift basics, memory management, and closures, followed by hands-on coding questions inside the platform editor. I remember being asked to build a SwiftUI view based on a description, then explain what a provided SwiftUI snippet was doing and fix visual issues, and finally review an existing SwiftUI screen and correct multiple bugs across both presentation and logic.
The interview process begins with a recruiter call followed by a structured technical screen conducted by Karat, focusing on iOS fundamentals and coding tasks related to Swift and SwiftUI.
Candidates typically experience a multi-round interview loop that includes data structures and algorithms, systems design, behavioral assessments, and role specialization discussions, often emphasizing collaboration and problem-solving.
Behavioral interviews are conducted with a focus on leadership qualities and overall fit, often taking a conversational tone to assess candidates' alignment with company values.
Candidates report significant delays and lack of communication following interviews, leading to feelings of uncertainty and frustration due to insufficient feedback on their performance and application status.
The difficulty of technical challenges can vary significantly, with some candidates experiencing a sharp increase in complexity during later rounds, particularly in data structures and algorithms.
Overall, candidates describe the interview environment as professional and respectful, though some encountered issues with the technical setup that affected their performance, such as tool compatibility problems.