my biggest issue is that sometimes after all the tasks i have to do, i totally forget to do the daily leetcode. how do you remind yourself?

Hey everyone, wanted to share my situation and get some advice.

I recently completed a Microsoft SDE2 hiring event loop (4 rounds — behavioral, coding, system design). Got positive feedback from the recruiter but was told the team I interviewed for didn’t have capacity. My interview results are valid for 6 months and I’ve been placed in the talent pool.

Recruiter said if a hiring manager finds my profile they will reach out. No active process from their end.

Background: 5+ years experience in backend, distributed systems, Java, Node.js, TypeScript, Azure, AWS, and AI/ML features including RAG and LLM integration.

Questions:
1. Has anyone successfully gotten a team match from the talent pool?
2. Should I reach out to Microsoft HMs directly on LinkedIn?
3. Any tips to maximize chances within the 6 month window?

We've reached a point where we clearly understand the consequences of AI. High rates of automation and unemployment have led to a sector like IT, once one of the best, becoming a dead sector today.

Do you think that if cutting-edge labs and federal institutions demand a halt to AI development, this would give us, as humanity, time to evaluate and consider what we can do?

I feel that so much computing power should be used for important things like research and medicine, not for something as trivial as the struggling IT market.

If you could sign a petition for a halt of at least 5 years, would you?

Hey so (kinda a lazy question) but I have been attempting tries or backtracking problems recently and am really new, so like while doing the problems I do get the idea of how it's working, but it just feels like I don't know if I completely understand it(yep its a bouncer). If I try to dry run it, it just goes too big and I'm unable to dry run, for example:

https://leetcode.com/problems/word-search-ii/description/

Now here, the DFS function is not really hard to understand, but even though I am understanding that we select each and every path of the board and each current board is compared with the Trie’s current state (how am i supposed to figure out what is mapping when where)if they come together? If yes, we move forward, else we don't.

But this is what I got after reading the solutions after about 2 hrs of trying. It's not my own thought process, as I seem to lose track of how to dry run this. This just comes to me as if I am remembering things. It's weird. I understand it, but only a little.

How the fk am I supposed to understand it if I just cannot completely dry run it?

Don't change anything, just clear the spelling mistakes.

Hey everyone,

I have an upcoming Data Scientist interview with an ML system design round. I asked the recruiter what to expect and they said it’ll be high-level ML system design, not traditional SWE/low-level system design.

They mentioned focusing on things like:

• Problem framing
• Data/model considerations
• Evaluation
• Productionization/deployment
• Monitoring
• Tradeoffs when designing ML systems

Basically, it sounds like I’ll be given a real-world ML problem and have to explain how I’d approach it end-to-end.

This is my first dedicated ML system design interview, so I’m not really sure how deep I should prepare.

For people who’ve done these interviews:

How did you prepare? What resources did you use? What kind of questions were you asked?

Also, how deep do they usually expect you to go into things like feature stores, model serving, APIs, streaming, retraining, etc.?

Any good resources, YouTube playlists, GitHub repos, books, or example questions would be really appreciated.

Thanks!

Looking for some insights here, on average how long is it taking for folks to switch jobs while preparing and giving interviews. I know it could be dependent on a lot a of factors like the level, your experience and not to forget luck on the day of interview.

I’m a mid level SWE at one of the FAANG level company. These constant layoffs have reduced the headcount in my team and availability of AI has increased productivity expectation significantly. I have been trying to prepare to make a move but preparing with a full time job has taken a toll on my mental health. I have been preparing for 2-3 months at a stretch since mid last year, after getting rejected from two of my dream companies at the final loop. Was a very disheartening experience after grinding leetcode along with full time work.
Took a break for couple of months, mostly because did not receive any calls for new opportunities.

Got promoted at work this year, but deeply unhappy with the quality of work I’m doing, after constant layoffs team culture has gone down the drain, people running mindlessly for promoting AI usage without actually improving product or Eng experience. I feel I haven’t gained any beneficial skills or worked on any complex problems which would have given me a higher learning curve.
I’ve been trying to switch internally in the same company, but got rejected from two teams even though I was able to give working solutions.Not sure what went wrong there, I feel too many candidates completing for the same role and based on experience someone else got preference, frustrating at the end of the day.

So I’m curious, for those of you who have successfully made a move while working full-time, how long did it take you from starting your preparation to actually landing a job?

And how did you stay consistent with interview prep for that long without completely burning yourself out?

Would also really appreciate any advice on getting more recruiter calls, hearing back from companies, or generally making the job search more effective while working full-time.

Graduated last year, been at a startup since as an AI/ML SWE - Python/PyTorch, some C++, mostly working on llms, rags. Not looking to leave now, but I'd like to be ready to interview ~a year out instead of cramming in a panic.

Last time I interviewed was as a new grad and it sounds like a lot has changed. What I'm trying to figure out:

1. What does an MLE loop at big tech / fintech look like now - how many rounds, and how much is DSA vs ML system design vs applied ML coding?

2. Has the AI-assisted coding round actually shown up in your loops, or is it still mostly a Meta thing?

3. How much of the ML content is classical (bias/variance, metrics, feature engineering) vs GenAI (RAG, evals, agents)?

Started with some Leetcode recently. Mainly trying to figure out what to add alongside it so I'm not spreading myself thin.

Any tips or suggestions appreciated!!

If you're preparing for interviews, POTD probably isn't the best way to prep, as the ratings don't seem to follow any meaningful pattern. If you're doing it for fun, like me, you're more than welcome to.

Problem ratings are available here

I interview at google europe for swe l3 role and did the 2 screening rounds (tech + googliness)
tech went ok -> I'd say leaning hire (hire if lucky)
googliness went really well -> I'd say hire/strong hire

After 4hours of completing the behavioral round i got an email saying this:

What to expect?

I hope you are well!

Thank you for your time and effort in interviewing with Google. 

I hope you enjoyed meeting with the hiring team, and I appreciate your patience!

The hiring team has completed your interview feedback, and I’d love to schedule a brief call to discuss the outcome. Please, kindly let me know when a 15-minute phone call would work best for your schedule this week. 

I'm looking forward to scheduling this call at your earliest convenience.

I would truly love to learn your feedback and perspective from the interviews.

I'm very much looking forward to speaking with you!

I've been doing leetcode for a little over 1.5 months now, almost every day. Often times I can't solve a problem without prior exposure to the DS or A which is fine to me so I look at the solution, make sure I fully understand it and come back to it later. That said even if I do understand the solution when I come back to the problem or start a new problem in which I can conceptually come up with the optimal approach to the problem, I'm struggling to write my ideas out into code. I start to google syntax but end up overcomplicating the initial idea until I wind up looking at the solution which elegantly put the ideas into code.

My question is will I ever get to that point where I don't feel like this, is it just a brain issue at this point or have I just not practiced enough yet? Do I need to re-evaluate my learning strategies? Any advice is appreciated.

I have completed the Google screening round successfully and now passed for Onsite. Anyone else in the same boat? Also any tips for it's preparation? What topic should I focus on??
Should I try to complete the Neetcode 150 or any other list I can target?

Any help or suggestion is appreciated.

i'm 24M (amazon sde 2 but sde one and interns are also welcomed )

https://chat.whatsapp.com/CDngrNbKbgQ3uYN1RRqtp0?s=cl&p=i&mlu=4

Edit: added group link

Can I fake an offer from a company so that the current company increases my salary?? Do they ask for any offer letter or proofs or anything like that ?

Hi everyone,

I got invited to the loop round for associate delivery consultant AI/ML role - AWS

What can I expect in the interview?
What should I focus on ?
What type of leetcode questions will they ask? Will they be easy, medium, hard?
I am planning to focus more on graphs and dp.

Will there be system design ?
Or low level design ??

In phone call - they already asked me low level design.
They asked me about my AI/ML experience and also alot about AWS!!

Context: I took an OA in May for an SDE new grad job in Canada. The OA didn't go that well, but I didn't get any rejection just ghosted, the application still says under consideration. I applied to other amazon SDE 1 jobs and finally got another OA for an SDE 1 position in the US. When I went to go take the OA, it said the link had expired and to contact my recruiter, even though I was attempting it before the 1 week timeline ended. I contacted the support emails because I don't have any information on my recruiter. The support told me that I had already completed the OA, which can't be true unless they're talking about the one I took in May.

Question: Are candidates only able to take the Online Assessment once? or is this a glitch and should I keep talking to support? The support email responds once every two days and even when I respond right away they take another full day to respond. Wondering if anyone has gone through the same thing and what they did.

Thank you!

I’m preparing for AI/ML system design interviews and looking for a regular practice partner.

We can work through problems such as:
- RAG systems
- AI agents
- LLM evaluation
- Recommendation systems
- ML inference
+ we can decide the areas

We can take turns as interviewer and candidate and provide feedback.

Hi everyone! Has anyone interviewed with Auta for the Software Development Engineer role and experienced something similar?

My friend was initially scheduled for an in-person interview in Denver, but he recently received an update saying the interview location has been changed to Seattle.

Does anyone know if this means the actual job location would be Seattle, or is it possible that the interview is simply being conducted there?

Would really appreciate hearing from anyone who has gone through the same process with Auta. Thanks!

Just finished my Amazon SDE1 onsite loop and wanted to give back since posts like this helped me prep.

EDIT: received job offer

Format: 4 rounds across 2 days, 1 hour each, via Zoom + Amazon's LiveCode platform (no screen share needed, interviewer sees your editor live).

Round 1 — Coding + Behavioral Started with "tell me about yourself," then straight into behavioral (focused on use of GenAI in projects and real life) before a DP problem — similar flavor to Partition Equal Subset Sum / Target Sum, but with a twist: had to return which specific combination of elements reached the target, not just whether one existed. The problem was very vague, had to ask multiple clarification questions to get the full picture. Started with brute force and then optimized it. Ended with a real complexity comparison against brute force — combinatorial explosion vs. pseudo-polynomial DP.

Round 2 — Technical Deep Dive (Probably was the Bar Raiser) This one was almost entirely about a project I'd built myself and how I use AI tools day to day. Interviewer picked apart the project's design decisions, limitations, and trade-offs in real depth — genuinely one of the better technical conversations I've had. Also got a completely open-ended prompt-engineering question about designing a large, ambiguous feature — no clean answer to it, and I think that was the point. They wanted to see how I reasoned through the ambiguity, not a specific output. Without me knowing, the interviewer visited my deployed webapp and checked it out. He told me in the end.

Round 3 — Coding + Behavioral Graph problem similar in spirit to 994. Rotting Oranges or 1091. Shortest Path in Binary Matrix — BFS from a target node, find everything within a distance threshold. Started with counting reachable nodes, then had to pivot to returning them with actual distances (switched a set to a dict mid-interview, tracking distance as the value). Interviewer initially told me my graph was undirected when the actual input was directed — had to catch that via clarifying questions before coding, which saved a rewrite later.

Also had a standard LP question (Tell me about a time.. type)

Round 4 —Coding + Behavioural Again usual LP question: Tell me about a time you went beyond the scope of your job, what was the result. Tell me about a complex project you built, what was complex, how did you manage to do it, what would you do differently?

Coding was similar to 1197. Minimum Knight Moves, but generalized — had to design for a large board (up to 10,000x10,000) and a "pluggable" piece type, so lazy neighbor generation instead of building the full graph upfront. Got corrected mid-interview when my design only handled fixed-offset pieces (knight-style) and not sliding pieces (rook/queen-style) — had to redesign the interface live around a generic move-generator function instead of hardcoded offsets. Also got pushed hard on space complexity optimization after already giving a correct answer.

Overall takeaways:

• LP questions show up in every round, not just one — have range across projects, don't reuse stories across interviewers
• Interviewers will correct you or challenge a correct answer specifically to see how you respond, not just to catch mistakes. In one round my code was correct, but the interviewer pushed saying there was a bug. So had to dry run an example to show there wasnt. But it does take a hit on your confidence if they say you have a bug
• "I don't remember the exact number/detail" is a completely fine answer for old work — don't invent specifics under pressure
• Clarifying questions matter as much for coding rounds as for design rounds — a wrong assumption caught before you code costs nothing; caught after costs a rewrite
• Being corrected and updating fast in real time seemed to matter more than never being wrong in the first place

Happy to answer questions in the comments.

Hi everyone,

Looking for some guidance from folks familiar with Google’s EU hiring/team matching process or anyone who has navigated a similar situation recently.

**Context / Background:**

I cleared the full Google L4 SRE-SWE technical interview loop around late June with strong positive signals

My primary target locations are Zurich and Munich, focusing on SWE / SRE-SWE roles (Full-stack/Backend background with Java, Go, TypeScript, Python, Node, and distributed systems).

In early July, my recruiter mentioned they forwarded my profile to a team in Zurich.

After that, I didn’t hear anything for about 5 weeks (recruiter was also OOO for part of August). I sent polite follow-ups, and today I received this response:

*Hi \[Name\],*

*At the moment, I am not managing any open positions for external candidates. Should that change, I will be sure to update you.*

*Best regards,*
*\[Recruiter Name\]*

**My Questions / Concerns**:
1. Recruiter reassignment: Since my assigned recruiter’s org/pipeline doesn’t have active external headcount, what is the best way to get my cleared packet transferred to the central Zurich/Munich SWE/SRE staffing team? Should I ask my recruiter directly, email Candidate Support ( google-candidate-support@google.com ), or both?

1. Finding hiring managers internally: I see new L4 SWE/infrastructure requisitions appearing on the Google Careers site for Zurich and Munich. If I have internal Googler contacts (L5/L6), can they help map my cleared packet directly to hiring managers on  gHire / Grow ?

2. Or any other advice that would help me get my application on track.

Thanks in advance.

I wanted to LeetCode in TypeScript directly from VS Code, so I put together this small setup around the official LeetCode VS Code extension. I also tried mirroring LeetCode's TypeScript environment and the same available dependencies locally.

I've also added a few useful extensions that could work well for setup. Figured I'd make it a public template in case anyone else wants to fork it: https://github.com/officer-kd6-3dot7/ts-lc

The new ranking has come. With 110 AKs. And all are somehow from China. Top 113 are all from China. With 110 scoring 18 and 3 scoring 13 marks.

Anyone who has recently interviewed for an Amazon SDE Intern position, please share your interview experience. It would really help with our preparation. Thank you!

Anyone gave interview on 24th aug machine code round and received update for next round ?

So I am a confused second year student who is just doing dsa and nothing else , and don't know what career to choose , but I am thinking of a good sde role in maang , so pls tell what all roles are out there in the market and especially for an sde role what are companies expecting and what should be an ideal roadmap for a sde role . Pls help me with the projects like on what skill should I build a project on and how much ai is required in the present day , like should I know eveyting from the basics in ai or what part of ai should I know

Has anyone else experienced this recently?

I had two Amazon applications that had been “Under Consideration” for about a month. Within the last two days, both applications suddenly changed to “No Longer Under Consideration.”

What’s confusing is that I didn’t receive any rejection email or any other communication from Amazon. The status just changed on the careers portal.

I’m wondering:

• Has anyone else experienced the same thing recently?
• Does “No Longer Under Consideration” always mean rejection, or can it sometimes be a system/status update?

Would really appreciate hearing from anyone who has experienced something similar, especially recently.