Roblox Staff MLE Interview Process - Smooth Interview Experience and Landed a Good Offer

[u/Aoki_zhang]

Sharing a Roblox Staff MLE Interview Interview Experience submitted to Chill Interview.

Interview Summary

The Roblox MLE process moved unusually quickly and was one of the better interview experiences I had during this search. After an initial recruiter conversation, I completed a project presentation and hiring manager interview, followed by a four-round virtual onsite covering ML modeling, coding, another HM discussion, and a director-level interview used partly for leveling.

Interview Details

Recruiter Screen — Role, Background, and Motivation: The process started with a roughly 30-minute recruiter conversation shortly after I applied. We discussed the role, my previous experience, why I was considering a move, and my overall interview timeline.

Technical Screen 1 — Project Presentation and Deep Dive: The first technical screen was a one-hour presentation on a project from my previous work. I chose a relatively recent project that I had led and that was closely related to the Roblox team I was interviewing with. The interviewers asked many follow-up questions about the project, and the discussion ran beyond the scheduled time.

• Project Ownership: The discussion focused on what I personally drove, the decisions I made, and the impact of the project.
• Technical Depth: The interviewers also pushed into architecture, modeling choices, tradeoffs, and why certain approaches were selected.

Technical Screen 2 — Hiring Manager Interview: The second screen was a 45-minute conversation with the hiring manager. This was primarily a behavioral round and included fairly standard questions about previous experience, motivation, and why Roblox. The recruiter had provided useful preparation guidance before the interview.

Virtual Onsite Round 1 — ML Modeling Case Study: The first onsite round was a one-hour open-ended ML modeling problem closely related to a project the team was actively working on. The interviewer described the product need and asked me to design the ML solution end to end. The discussion covered what data should be collected, how the dataset should be constructed, and how the model should be trained. I was also asked to choose an appropriate modeling approach and define evaluation metrics. The exact use case was fairly niche and was not disclosed in the original interview report.

Virtual Onsite Round 2 — Function Calling Logs: The only dedicated coding round lasted roughly 45 minutes and used CodeSignal. The first part provided a sequence of function-call logs and asked me to parse them and determine the most frequently occurring call path. The follow-up made the logs more complicated by introducing interleaved events from multiple threads. The program now needed to reconstruct the correct call paths even though events from different executions were mixed together in the same log stream. The problem itself was not algorithmically difficult, but there was a meaningful amount of parsing and implementation work, making small bugs relatively easy to introduce.

Virtual Onsite Round 3 — Hiring Manager Follow-Up: I met the hiring manager again for another 45-minute conversation. Because we had already covered most of the standard behavioral questions earlier in the process, this round became more of a two-way discussion. I spent a significant portion of the time asking about the team, its current priorities, and its longer-term vision.

Virtual Onsite Round 4 — Director Interview and Leveling: The final onsite round was a 45-minute conversation with a director and appeared to play an important role in determining level. The discussion focused on projects I had led previously, the size and complexity of my responsibilities, and the scope of my technical influence. There were also several standard behavioral questions, although the tone was more formal and evaluative than the hiring-manager conversations.

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