Google PhD Early Career AI/ML Full Loop: Sparse Set, Attribute Groups, and Harmful Content

Role: Machine Learning Engineer / SWE, PhD Early Career
Result: Rejected after six technical/behavioral rounds
Report time: July 2025
Application: Applied online

Timeline

A recruiter contacted the candidate in January after an online application. The process then included a phone screen, recruiter briefing, free mock interview, four-round virtual onsite, two additional coding rounds, and final feedback over roughly 117 days.

Phone screen: constant-time sparse set

Use two arrays to model low-level storage supporting O(1) insertion and deletion at arbitrary positions, similar to a sparse set.

Practice: Sparse Set With Constant-Time Updates

Virtual onsite coding 1: group attribute-connected entries

Given triplet-like entries, construct a graph and use DFS to merge entries connected through shared attributes.

Practice: Group Attribute-Connected Triplets

Virtual onsite coding 2

The second question required topological sorting. The candidate had not yet studied that topic, proposed only a cubic brute force, and did not implement code. The source no longer preserves the graph or objective.

ML design: harmful-content classification

Design a simplified harmful-content detection or classification system, starting from data preparation. The interviewer asked detailed questions but did not require production-scale millions or billions of records.

Practice: Design a Harmful-Content Classification Service

Behavioral and additional rounds

The behavioral round went well using five or six reusable STAR stories. Google later requested two additional coding interviews; the candidate completed their problems but no longer remembered the exact prompts.

Final feedback praised ML fundamentals, leadership examples, and Googleyness. Coding feedback asked for better real-time adaptation to hints, testing, pacing, and fewer interviewer prompts. The candidate felt the ML and behavioral signals were strong but coding was not strong enough to recover from one unsolved onsite round.