I recently completed the LinkedIn SDE Virtual Onsite , which lasted roughly 1 hour. The core of the interview focused on Coding + In-depth Project Discussion, with all questions at the LeetCode Medium difficulty level.
The real challenge wasn’t solving the problems themselves, but clearly explaining your thought process and supplementing optimization solutions.
This guide is perfect for anyone aiming for big tech roles, and the content is concise and to the point.
🧭 Core Interview Process
🔹 Self-Introduction (3–5 minutes)
Skip the generic templates! Focus on content that encourages the interviewer to ask follow-up questions:
- Mention your university, major, and research focus
- Pick 1 project or internship to elaborate on
- Clearly state the application scenario + your specific responsibilities
✅ Example: “I worked on an e-commerce recommendation project, where I handled feature engineering and solved the cold-start problem,”
instead of just “I did a machine learning project.”
🔹 In-depth Project Discussion (10 minutes)
Interviewers will dig into details, so be ready to answer these 4 key questions:
- What was the core goal of the project?
- Which specific technologies (frameworks/algorithms) did you use?
- How did you solve the biggest challenge (explain the steps, not just “I fixed it”)?
- What did you learn (e.g., technology selection, collaboration experience)?
🔹 Coding (30 minutes)
You’ll tackle 2 Medium-level questions.
Always explain your approach first before writing code, and be prepared to discuss optimization directions.
1. Locker Toggle Problem
There are ( N ) initially closed lockers. You toggle every locker in the 1st pass, every 2nd locker in the 2nd pass, and so on until the ( N )th pass. Which lockers remain open?
Key Insight:
The number of times a locker is toggled equals the number of its factors.
Only perfect squares have an odd number of factors, so the open lockers are all perfect squares ≤ N.
2. Nested Integer Weighted Sum
Calculate the sum of all integers in a nested list, where each integer is weighted by its depth.
Example:[1,[4,[6]]] → 1×1 + 4×2 + 6×3 = 27
Key Insight:
Use recursion for the basic solution; optimize with BFS level-order traversal to avoid stack overflow.
💬 Q&A Session: Avoid “Meaningless” Questions
Choose questions that show you care about role fit, such as:
- What AI tools are commonly used in this role to improve development efficiency?
- Does the team value an engineer’s design ability more than the number of code lines written?
- How do you align design decisions with product managers (PMs) during communication?
🚀 Prep Key: Smart Methods Beat Mindless Problem-Solving
I struggled with “unfocused self-practice” at first, but Programhelp’s support helped me avoid many detours.
For big tech VOs, “practicing with purpose” is more important than “solving more problems.”
Here’s what helped me the most:
- 🧑💻 Remote Mock Interviews: Rehearsed the full interview flow, smoothing out the rhythm from self-introduction to code explanation and avoiding on-the-spot blanking.
- 💡 Real-Time Thought Hints: When stuck (e.g., not realizing the locker problem relates to factor counts), real-time prompts guided me back to the right direction.
- 🧾 Answer Completion: After coding, they helped refine time/space complexity analyses and add comments—because big tech cares not just if code works, but if you can explain it clearly.
Programhelp has already helped many candidates land offers at companies like LinkedIn, Amazon, and Google.
If you’re stuck in unfocused practice or need targeted mock interview support, give it a try — it will save you a lot of prep time.
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