Real, anonymous reports from people who interviewed for Machine Learning Engineer at Meta, newest first and distilled into what to expect across the loop.
My process dragged out longer than I expected—closer to weeks at the start, and in total it ended up feeling very drawn-out. It kicked off with early technical stages: I went through screenings that tested core ML knowledge like attention and variants, and then the later phases shifted into more high-pressure technical execution.
My experience was shaped less by the technical rounds and more by timing and process friction. I had a recruiter screen that felt friendly and detailed, with plenty of discussion and what seemed like an emphasis on matching role expectations. After that, I progressed into the technical interview part where the format was relatively familiar—LeetCode-style coding questions with screen-sharing.
The interview process begins with a recruiter screen that focuses on background, fit, and role expectations, often leading to a technical screening that tests core ML knowledge through LeetCode-style problems. Candidates should prepare to discuss their experience and clarify their preferences regarding teams and timelines.
Candidates can expect multiple coding interviews that typically involve solving medium to hard LeetCode-style problems while explaining their thought process. It's crucial to practice coding under time constraints and to be prepared for questions that probe edge cases and complexity analysis.
The onsite includes a system design round that often requires candidates to design ML systems, such as recommendation engines, and discuss real-world considerations like data usage and model evaluation. Prepare to articulate both ML-specific and broader system-level design principles.
Behavioral rounds focus on past experiences, handling ambiguity, and alignment with company values, often using the STAR method for responses. Candidates should reflect on their leadership experiences and how they manage team dynamics and conflict.
The overall interview process can be lengthy, with significant waiting periods between rounds, leading to a feeling of unpredictability. Candidates should be prepared for potential delays and ensure they follow up for updates to avoid confusion about their status.
The interview environment can vary, with some candidates experiencing professionalism and structure, while others may encounter unprofessional behavior from interviewers. It's important to remain focused and adaptable, regardless of the interview dynamics.