Software Engineer · Full Journey · Multiple Types

Google — Software Engineer ✅ Passed

Level: Mid-Level

Round: Full Journey · Type: Multiple Types · Difficulty: 4/10 · Duration: 120 min · Interviewer: Neutral

Topics: Breadth-First Search, Graph Algorithms, Sampling, AI Research, Reinforcement Learning

Location: Mountain View, CA

Interview date: 2025-12-08

Summary

Round 1: Coding

Question: I was asked a classic Breadth-First Search (BFS) problem. I needed to use a dictionary to establish graph relationships and then use BFS to search. I completed it in about 15 minutes, followed by two or three follow-up questions. The interviewer was very friendly and did not try to make things difficult for me.

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Round 2: Applied Programming

Question: I was asked a practical application question, specifically to write a sampling program. Due to spending a significant portion of the time discussing my research with the interviewer (who was familiar with my PhD school), I had limited time and used pseudocode to outline the solution before fleshing it out. The interviewer was very friendly and did not try to make things difficult for me.

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Team Match Round 1: Ads AI

Question: Interview with the Ads AI team (NYC). The host described the team as consisting of research scientists and research engineers. The project involved RL-related research, with the goal of publishing papers or technical reports. After the interview, I felt my skills might not be up to par, given the impressive backgrounds of the team members. However, I was selected, possibly due to my genuine enthusiasm.

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Team Match Round 2: GCP

Question: Interview with a GCP team (Kirkland). The location was appealing, but the team focused on infrastructure, which didn't align with my background. The project involved developing an agent to assist programmers with debugging.

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Details

Preparation Tips & Key Takeaways

What I Learned

• The importance of quickly establishing a good rapport with the interviewer, especially if they have a background similar to yours.
• Being honest about my skills and interests during the team matching process.

Recommended Preparation

Coding Practice

• Practice graph traversal algorithms, particularly BFS.
• Familiarize yourself with dictionary-based graph representations.

Applied Programming

• Practice implementing sampling algorithms and writing pseudocode efficiently.

Team Matching

• Research the teams you're interviewing with to understand their projects and the required skill sets.
• Prepare thoughtful questions to demonstrate your interest and assess the alignment between your background and the team's work.

Resources I Recommend

• Reviewing fundamental graph algorithms and data structures.
• Practicing implementing sampling techniques in your preferred programming language.

Common Pitfalls to Avoid

• Spending too much time on introductory conversation and not enough on the coding question (manage time efficiently).
• Underestimating the importance of aligning your interests and skills with the team's projects during the team match phase.