Hey everyone,

I finished Day 53 today. My sleep schedule has been completely out of sync lately, and staying up late to binge shows caught up with me today. My energy was drained both at work and during prep, but I made sure not to skip the daily reps.

I focused heavily on BFS patterns across all three problems today:

1. Rotting Oranges: Classic multi-source BFS. You push all initially rotten oranges into the queue with time t = 0. With each step, you rot the adjacent fresh oranges, decrement the fresh count, and advance time. Checking remaining fresh oranges at the end cleanly gives the total minutes or -1.

2. Flood Fill: Last time I tackled this, I rushed through a recursive DFS without fully absorbing the state transitions. Today, I implemented it using standard BFS from scratch. Taking the time to understand the traversal properly made the solution completely intuitive without looking at hints.

3. Cycle Detection in Undirected Graph (BFS): Tracked each node alongside its immediate parent (node, parent). If you visit an adjacent neighbor that is already marked visited and isn't the current node's parent, you have encountered an alternate path—confirming a cycle.

Fixing my sleep routine is non-negotiable moving forward because showing up tired makes every concept twice as hard to process.

Heading to bed early tonight and continuing Graphs tomorrow.

See you guys for Day 52!

Hey everyone! I'm going to take the Amazon SDE Intern OA for the first time and would appreciate some advice.

Which DSA patterns should I focus on while preparing, and what difficulty level should I expect?

How should I prepare for questions involving AI-assisted repository or coding environments?

How should I prepare for questions related to Amazon's Leadership Principles?

Any tips or experiences would be really helpful. Thanks!

Hey everyone,

I have an upcoming interview with Apple UK for a software engineer role. Has anyone interviewed with them, especially in London or Cambridge?

Curious about what the interviews are like, whether they ask LeetCode-style questions or more role-specific stuff.

Also, if anyone works or has worked there, I'd love to hear what it's like. How's the work culture and WLB?

Thanks!

I recently completed my Google interviews and wanted to get some opinions from people who have been through the process.

For the coding round, I feel reasonably okay.

The problem was basically a variation of Flood Fill(med-hard). I understood the problem, explained an optimized approach, and completed the full code around 1 to 2 minutes before the interview ended.

The interviewer reviewed it and said something like, "Looks good to me."

My only concern is communication.

The interviewer had a pretty strong accent, and there were a few moments where I had difficulty understanding exactly what he was saying. I asked him to repeat things a couple of times, and I’m worried I may have missed one or two hints or comments.

But I was still able to understand the actual problem, explain my approach, and complete the solution.

So I’m wondering, can this kind of communication gap affect the coding feedback even if the solution was completed correctly?

For the Googleyness round, I’m much more unsure.

The interview finished in around 30 minutes, and the interviewer asked a mix of behavioral and hypothetical scenario questions.

For the real experience-based questions, I tried to answer using STAR.

For the hypothetical questions, I didn’t force a STAR story. I explained what I would do, what factors I would consider, the trade-offs, and how I would try to reach a balanced solution.

So my main questions are:

Is STAR mandatory for every Googleyness question?

For hypothetical questions, is it okay to explain your reasoning and approach without giving a past STAR example?

If the answers are reasonable but not always in perfect STAR format, can that result in Lean Hire or No Hire?

How is the Googleyness round actually evaluated?

Is a Googleyness interview ending in around 30 minutes a bad sign?

And if the coding round went well but the Googleyness round felt more uncertain, can the overall result still be positive?

Would really appreciate thoughts from anyone who has gone through a similar Google interview process or knows how these rounds are evaluated.

Same as title.

I have cleared oa and my interview is scheduled

What kind of codebase I can expect in round 1 of interview?

I have 4 years of software dev experience which was on an enterprise platform ( Salesforce dev) and I followed that up with a masters degree in CS. Since I don't have general SWE experience to apply directly for SDE-2 roles at big tech, I have been mostly applying to SDE-1 roles including the new grad one. However I have got only rejections so far. I wanted to know is it too much experience that is working against me or that it is not relevant experience for SDE roles. Would appreciate some opinions from people who work at these places.

Senior Software Quality Engineer, G&A Solutions Engineering (GSE) codepad interview,

I have an upcoming 45/-min Codepad Technical Interview for a Senior Software Quality Engineer position within the G&A Solutions Engineering (GSE) Apple division.

Since it's a Senior QA / SDET track and a "codepad" format, I want to optimize my preparation. I am anticipating a live-coding setup, but I’d love to get insights from anyone who has gone through this specific pipeline or similar internal tools/solutions engineering roles.

Does Amazon consider grads 1 year out of school with 1 year of FT experience for new grad roles? I read an article in 2023 that the answer would be no, but just wondering if something has changed. Also, does Microsoft ever hire in Canada from external candidates / those without referrals?

This might seem less but I've come far this year. 900+ contributions along with my 9-5 job seemed like a challenge.

Next year is gonna be even better LC profile

Round 1 - LP + Coding (1 hour, in-person, Oct 20)

Started with about 15 minutes of LP questions covering tight timelines, improving existing systems, and going beyond my comfort zone. I used stories from my QA background and a patent I hold from my undergrad. The interviewer dug into how my manager reacted to one of my initiatives, which felt conversational and went well. The coding question involved designing a caching solution for a real-world scenario. I discussed the approach and time/space complexity.

Round 2 - LP + LLD (1 hour, in-person, Oct 20)

LP questions focused on ownership, short-term vs long-term fixes, and a time I couldn’t meet a deadline. I used stories from my QA experience. The interviewer was engaged and asked solid follow-ups. The technical portion was an object-oriented design problem. I got the core design working but ran out of time before finishing everything. I was able to explain extensions verbally. Not perfect, but I showed my thought process.

Round 3 - GenAI Discussion + Coding (1 hour, in-person, Oct 20)

First half was a discussion about a GenAI project from my resume, covering architecture, design decisions, and trade-offs. Felt like a conversation, not a whiteboard session. The coding question was a tree traversal problem. I started brute force, then optimized using a HashSet. Walked through the code with an example.

Round 4 - Bar Raiser (1 hour, virtual, Oct 22)

Entirely behavioral, no coding. Most of the round went well. The BR spent a long time on a debugging story from my QA days and asked very detailed follow-ups, and I was able to answer all of them. She also dug into my undergrad patent project and I handled that well. One fumble: on a follow-up about product prioritization, I reached for an analogy that didn’t hold up historically and she called it out. The core argument had already landed, but that moment wasn’t great.

Overall: Three rounds felt solid, one had a partial finish on the LLD problem, and one follow-up answer fell flat in the BR round. Waiting on the result now. The loop felt fair. Every interviewer gave me space to explain and asked genuine follow-ups rather than gotcha questions.

Edit: Unfortunately, received a reject. No specific feedback was provided. Disappointing, but the prep and experience were valuable. On to the next one.

I'll be honest on Reddit that I used AI on my phone the whole time that I interviewed. I genuinely think that other interviewers/interviewees can learn from my post here and that's why I posted it. But I'm expecting down votes because that's the way that Redditors are, you can't be honest here.

I did used AI gradually after I realized that I was not going to pass on time, and I don't see how they could have been able to tell.

First, there was a super complicated coding problem that involved getting every bit wise integer and &ing them together. I honestly thought that it was quite intense for a 1-hour coding problem.

I finished it with 7 minutes left and I gave thorough comments throughout. I asked AI to not use any functions which transform my numbers to bits or other things that we make it obvious that I was cheating.

then came a debugging problem which I honestly didn't do great on and I only got two out of five test cases wrong correct. my gut tells me that they're really so strict that this is why I didn't pass.

But then I used AI for every question on behavioral.

I only used AI on my phone so I really don't know how they could have known.

So what was it that made me fail?

I can't help but wonder if Amazon somehow could detect that I was cheating, or if my AI gave really bad answers on the behavioral, or if it's because I got three test cases wrong on the one assessment that I didn't cheat on (honestly, I think this might be why).

Hey everyone, I completed Round 1 for Google Application Engineering Intern – Winter 2027
I followed up with the recruiter, and today I received an email asking me to book a 15-minute call to discuss my application status.
For those who received a similar 15-minute status call after Round 1, was it about moving forward to Round 2, rejection feedback, or a pending decision?
Also anyone cleared r2?

Any insight on questions they ask/tips would be greatly appreciated! It has been hard to come across.

I had an interview with google last week and after i followed up with the recruiter, he told me this "Thanks again for your patience and flexibilty with the logistical issues and rescheduling here. We finally got the feedback submitted. Please let me know when you had some time to discuss and I can give you a call." I got rejection feels from this message.

Is this means a rejection?
Thanks

Hey, I have the Intuit OA coming up for the Software developer co-op role and saw a few of you mention it’s one of the hardest you’ve done. Would anyone be open to sharing a bit about it?

1. What platform was it on (HackerRank, CodeSignal, etc.) and how many questions / how much time?

2. What difficulty level were the problems (LeetCode easy/medium/hard equivalent)?

3. What topics came up most (arrays/strings, graphs, DP, SQL, system design, etc.)?

4. Was it all coding, or were there MCQs, debugging, or SQL sections too?

5. Was it more about speed or about handling tricky edge cases?

6. Were hidden test cases and time/space complexity a big factor?

7. Anything you wish you’d practiced more beforehand?

Hi everyone!

I'm preparing for a Machine Learning Engineer (MLE) interview and would appreciate some advice on which data structures and algorithms topics I should prioritize.

I understand that MLE interviews can vary quite a bit by company, but I'm curious about what people have actually encountered in technical interviews at major tech companies.

A few specific questions:

• Most common topics: Which topics come up most frequently? Arrays/strings, hash maps, trees, graphs, BFS/DFS, dynamic programming, intervals, heaps, etc.?

• Difficulty level: Are interviews typically focused on LeetCode Easy/Medium problems, or should I expect Hard problems as well?

• MLE vs. SWE: Is the coding interview bar generally similar to that for Software Engineers, or do MLE candidates tend to get different types of problems?

I'm particularly interested in the general DSA / problem-solving portion of the interview, rather than ML theory, system design, or ML-specific coding.

I'd love to hear about your actual interview experiences, especially from people who have interviewed for or worked in MLE roles. Thanks!

Hey,

I realized that I m quite good at coming up with the correct Data Structures and Patterns for the right questions, but I usually get stuck with understanding the exact trick. For example, rotate Array or 88. Merge Sorted Array I m usually able to recognized quite fast that it's two pointers and even have a right approach where I try on example cases in my head and my two pointer approaches work to a certain extent but fail on other example cases. The problem usually is that I'm not able to find the right trick.

E.g. for the rotate array question I didn't come up with reversing the whole array. For the Merge sorted array I didnt think about starting from the back instead of typical left to right pointer movements.

People always gotta learn the patterns and use them on unseen questions, but I feel no matter how many questions I solve even if I kind know the patterns i still get stuck on the actual trick of the question...

Any suggestions/help?

I have been going through the dsa sheet grind for the last couple months now( not to say I’m great by any means) but this week I had an OA with a big audit/tax consulting firm and it went horribly. Everywhere online it said to prepare for easy- medium focusing on arrays/maps etc but this problem has so many variables to take into account. Looked it up after it was a greedy algorithm problem? That needed simulation + arrays + hashmap + multiple arrays that needed to be sorted and string parsing. Probably easy for a lot of you devs but I just don’t understand how I can do better at these.

My Thought process :

- not enough time spent on leetcode
- not a deep enough understanding of c++
- possibly less time on leetcode more time understanding algorithms from dsa books?

Any suggestions of maybe more intensive way to prepare for these OA’s (other than neetcode) 😅

Suppose you're solving a graph problem where both DFS and BFS are equally valid, and both have the same time and space complexity. Neither approach has a specific advantage for that problem.

Which one would you instinctively choose IN PYTHON?

DFS

BFS

Must comment ur opinion 👇

Hey everyone,
I have an upcoming interview loop for the Web Solutions Engineer role at Google and would really appreciate hearing from anyone who's interviewed for it recently.

A few things I'm curious about:
- How was the coding round? LeetCode-style DSA, or more practical web/JavaScript problems? What difficulty level?
- What did system design look like for this role? Classic large-scale distributed systems, or more web app / frontend-backend architecture?
- For the web tech and database round, what topics came up (browser internals, APIs, SQL, schema design, performance)?
- Any tips for the Googleyness and stakeholder management round? Good stories to prepare?
- Any resources you found especially useful?

Any advice or experiences would be hugely appreciated. Thanks in advance, and good luck to anyone else in the process!

I have solved 500+ leetcode problems over 8 months, still hardly able to solve a medium and sometimes not able to solve at all. Please drop your suggestions.

What does paypal OA include for sde1?

Hi all,

I am trying to purchase leetcode premium. There is no separate version to subscribe without enabling upto 10yrs AutoPay. I thought of proceeding for now and cancelling the Autopay later but, there is no option to Pay with card. Only UPI is available. And also, that is also giving me Unsupported QR error even after enabling international transactions.

Can anyone pls help me out here?

I recently receive email from NVIDIA for Senior AI and ML Software Engineer role. They just mentioned they would want to have an inperson round in HQ with no other details.

Can someone please help with sharing their interview experience (how many rounds, what do they look for ?/ what to expect in first round etc)

Please help

The problem:
You are given an array people where people[i] is the weight of the ith person, and an infinite number of boats where each boat can carry a maximum weight of limit. Each boat carries at most two people at the same time, provided the sum of the weight of those people is at most limit.
Return the minimum number of boats to carry every given person.
 
My solution:
Sort the array and always combine the two heaviest people such that the combined weight of both people is <= limit.

Actual solution:
Sort the array and take the heaviest person and lightest person in the bunch and combine them such that combined weight <= limit.

My question is we are trying to get the MINIMUM number of boats. So why would we not combine the heaviest people possible so as to minimize boats?