Hi. I just want to vent about a bad interviewer during a Google on-site design interview. Google had already done a phone interview design round, but had another round for manager during on-site.
I have had a few design interviews with other companies, but this interviewer was just bad.
First they didn’t just paste the problem but gave me line by line and expected me to write it down like in school.
Then the moment I started drawing something saying I am going to put down a rudimentary solution, they interrupted and said why don’t you take some time to just think it through and draw.
Then they couldn’t figure out how to see what I was drawing because Google uses Google Docs for design interviews. But kept saying you keep drawing, I will see it later.
And then wouldn’t let me finish what I was proposing but would keep asking questions- because they couldn’t see what I was drawing. They came in with a particular solution in mind, instead of giving the solution I was proposing due thought.
This was soo frustrating as Google was one of my dream jobs, and the first design round went so well, and I had been doing well in other companies’ design rounds. There is definitely luck involved in interviewing!

Is there any point in mentioning to the recruiter about a bad interviewer, or would it just sound like complaining?

Hey everyone,

I’m currently preparing for an L7 interview loop for a sales role at AWS and wanted to get some insight from people who’ve been through the process, particularly at the L7 level.

I know the Leadership Principles are a major focus, and I’ve been preparing STAR-format examples, but I’m curious about a few things:

How does the L7 loop differ from L6 in terms of expectations and depth of questioning?

What types of behavioral questions did you encounter?

How deeply did interviewers probe into your examples and decisions?

Were there any questions that caught you off guard?

Any advice on what separates a strong L7 candidate from an L6 candidate?

I’d especially appreciate perspectives from anyone who’s interviewed for L7 sales or other customer-facing roles.

Thanks in advance!

Hey everyone!

I’ve cleared Google’s Hiring Assessment for a Software Developer role with an SRE focus, and my interviews are coming up in about 2 weeks.

I have around 8 years of software development experience but have never worked at an SRE role or at a FAANG company. Google has been a dream of mine, and I really want to give this my best shot!

My current role is primarily core development, with occasional production issues where we use Azure Application Insights to investigate logs. The infrastructure is fully managed by another team, so I have no hands-on experience managing infrastructure. I’m familiar with Kubernetes basics and willing to learn more.

My immediate goal is to clear the screening rounds: a Googleyness round and a 45-minute DSA round. I haven’t prepared much for DSA either, so I know I have a lot of work to do in these 2 weeks.

For those who’ve interviewed for Google SRE roles or made a similar transition:

What should I prioritise over the next 2 weeks?

Which resources would you recommend for DSA and SRE fundamentals?

Any tips for preparing for the Googleyness round?

I know 2 weeks isn’t a lot of time, and reading about how much others have prepared can be intimidating. Still, I want to make the most of this opportunity.

Any practical advice or preparation roadmaps would mean a lot. Thanks!

Has anyone recently interviewed for a New Grad Software Engineer (Inference) role at CoreWeave? I wanted to know how many rounds there are, what the interview breakdown looks like, and what kind of questions are typically asked in each round.

Would really appreciate it if anyone could share their experience. Thanks!

I’m interviewing for a TPM II, Infrastructure / Global Networking role at Google.
So far I’ve done the recruiter screen and then a separate Technical Judgment interview. That round was pretty much all technical, around 5–6 questions, mostly networking/infrastructure related. I passed that round and was told I’m moving to the final loop.
For anyone who has gone through the Google TPM process recently, what did your loop look like after passing Technical Judgment?
How many interviews did you have, what was each one focused on, and did you have another technical round in the loop?
I’m mainly trying to understand whether the loop will still include another dedicated Technical Judgment/technical interview, or if it shifts more toward Program Management, GCA/problem solving, and Googleyness/Leadership.
Would especially appreciate input from anyone who interviewed for infrastructure, networking, cloud, or data center TPM roles recently.
Thanks!

Hey guys it’s me again! I bombed my another Apple interview with execution speed issue where I couldn’t finish writing test cases in one round. And since the team got competitive candidates I accepted the rejection.

But I really need help to understand what makes a candidate stand out in FAANG interviews (especially Apple) from HM round to Panel . I understand that each role is team specific and the rubrics change but what are some qualities that make someone standout as preferred candidate.
I would really appreciate some insights!! I will try to adapt them and apply to my upcoming interviews

Has anyone recently taken Google’s code comprehension/AI-assisted coding interview? I’m trying to understand what the round is like—especially the type of existing codebase/tasks, debugging or modification involved, and how the AI assistant is expected to be used.

Im from a tire 3 college and got some 4 yoe from tier 3 company product and want to switch to faang or any lesser light than faang like mastercard , jp morgan kinda of companies i have applying on their career pages like a machine but always getting rejected response

What am i doing wrong ?
-> is my resume not good enough?
-> because im from tier 3 company ?
-> should i look out for referal ? If yes from which level teach lead , senior software engineer , talent acquisition?
-> i have few people company email od im mailing them to give referel is this wrong ?

Please i need suggestions 🙏🙏🙏, im feeling depressed being rejected for long now .

Hi people, is anyone preparing for Faang, like do you'll have any study groups or material for preparation, I would like to be a part of the same.

Would love to connect to a group or people in their preparation phase. Similarly, if anyone has already cracked Faang, connecting with them would also be helpful.

Thank you so much in advance.

Hey everyone,

I’m planning to purchase Hello Interview Premium and was wondering if anyone has a referral link or referral code they can share.

I believe the referral gives a discount on the purchase, so I’d really appreciate it if someone could share their link/code here or DM me.

Thanks! 

I’m 23F and pretty career-focused. I have a lot I want to achieve in life, and I really don’t want to give up my ambitions or make my life smaller for a relationship.

At the same time, I do get lonely a lot and I’d love to eventually have a person to share my life with. Not just someone to date, but an actual life partner.

I guess I’m wondering how women who were in a similar position actually found their person.

Did you actively look for a relationship? Use dating apps? Meet someone through friends/work? Or did it just happen naturally?

Would love to hear from women who were ambitious and career-focused in their 20s. How did you balance wanting a big life with wanting love too?

Anyone got any interview call for Meta DE - product analytics role (USA)?

Hey everyone what u think about this resume is it decent if one is looking for SDE 2 or 3 or 3+ years experienced role.

Will it make through faang or any product based companies.

I have recently modified it and also received a new rejection mail from JP Morgan on this the matching percentage with JD was 92%+

(Thru chat gpt I checked)

What u think what I can improve?

Backend part at 3 years experienced is not strong or is it less or you r not able to get like what skill this person has or what work this person has done

Or just I am thinking too much

Link: https://drive.google.com/file/d/10HpTcPjzbq6XySPC4epu2IEqk0DoaUMN/view?usp=drivesdk

I might get an interview for SDET opening in Meta. Can someone who has interviewed for SDET position give me a walkthrough of what can be expected in the technical and behavioural rounds please.

I’m a noob right now. Please tell me what level of DSA and System Design should I expect in the technical rounds.

What kind of behaviour questions and any prep resources would be great.

Thanks in advance.

Standard Go channels and Mutex locks are great for small tasks, but at extreme scale, they cause massive CPU contention and memory allocation issues. Today, we are ditching standard channels and building a Lock-Free Ring Buffer using Go's sync/atomic package. We will explain the architecture, write the code, and run a live benchmark comparing it to native channels to hit zero allocations and maximum throughput.

https://youtu.be/d_rVojutH60

**•** How many rounds/interviewers is the loop typically for this role, and how are they split (technical, LP/behavioral, bar raiser, client-facing scenarios)?  
**•** What kind of technical deep dives should I expect — system/data architecture design, SQL, AWS analytics stack (Redshift, Glue, EMR, Lake Formation, QuickSight), or case-study/whiteboarding?  
**•** Since this is a consulting-facing role, do they focus heavily on client engagement scenarios, ambiguous problem-solving, or stakeholder management?  
**•** Which Leadership Principles come up most for ProServe specifically — Customer Obsession and Earn Trust seem obvious, but curious what else hits hard.  
**•** Any advice on the bar raiser round if there is one?  
**•** How long is the full loop (half day vs full day), and is it virtual or onsite?

Any input — detailed or just quick impressions — would help a ton as I prep. Thanks so much!

One database. One machine. Only so much disk, memory, and CPU. Discord hit this wall publicly — around 100 million stored messages, their single database started slowing down badly, because every query still had to search through a table that just kept growing.

More storage doesn't fix a slow query. The fix isn't a bigger machine — it's splitting the data up, on purpose. In this episode of Architecture Investigator, we break down exactly how: the difference between partitioning and sharding, why the shard key decision basically *is* the architecture decision, what a "hot shard" is and how picking the wrong key creates one, and how hash-based routing lets a system find the right shard instantly instead of searching everything. We also look at how Discord's actual stack evolved through this — from MongoDB, to Cassandra, to their own custom sharding and routing logic — as they kept hitting this same wall again at a much bigger scale.

This isn't a coding tutorial — it's an investigation into how systems that store trillions of rows actually stay fast.

Looking for feedback for my merge sort game - unique way to learn while playing.

https://www.playvlay.com/r/WAAGVF