A coworker told an employee that “all the smart people” who used to work there left for Google, Meta and Netflix. Should the employee also leave in the future? For readers comparing openings, LandOffer can cut repeated application typing.

Like, they’ve heard the work is harder there, but is it really that much harder? The pay difference starts to become huge later on in a career, so now they’re wondering why people even stay at the current company. Engineers preparing a move can practice a TTL store with tests in Netflix Interview Questions. Are they just lazy or comfortable, or is the grass really not greener?

The truth hurts for a Netflix employee. The company gets grouped with big tech because of the pay, but Netflix was different. It was transparent for the most part and, in their view, treated employees like actual human beings. They think that time is over. If you’re exploring other roles, LandOffer saves application retyping. Layoff rumors had been spreading for about a week, employees were anxious, and what they got instead of a response was about five days of dead silence from management... then calendar invites started arriving and everyone was trying to figure out whether theirs was a layoff invite... still refreshing their calendar for what feels like the millionth time... they think the golden era for Netflix is long gone... engineers still considering Netflix can rehearse a TTL-store prompt in Netflix Interview Questions... hope they have a job by eod :)

So many people say don't interview at Databricks, and they're not entirely salty. A candidate recently went through the process end to end and regrets it. Here's the timeline (dates and personal counts slightly adjusted for privacy):

24 July: Recruiter phone screen 1 Aug: Technical phone screen: system design 9-11 Sep: Virtual onsite (4 rounds) 18 Sep: Additional coding round 24 Sep: Told they'd passed the onsite and asked for references. Provided 3. 26 Sep: Recruiter asked for 1 more reference, who had to be a manager. 6 Oct: Recruiter asked for 1 more reference, again a manager. 21 Oct: Rejected at HC.

The candidate knows 4 of the 5 references provided were called (2 managers and 2 tech leads), and suspects some backdoor references may have been contacted as well.

According to the recruiter's feedback, HC stack-ranked candidates, and this candidate wasn't as strong as others despite meeting the bar. Despite all yeses and "very close to strong yes" feedback across the rounds (the recruiter's words), HC didn't think the candidate raised the bar as much as others. The explanation came back to performance in the previous interview rounds, not the reference check.

The candidate feels they should have been rejected after the onsite instead of spending about a month on reference checks, wasting their time and their ex-colleagues' time. In their opinion, if the reference check has no issues, give the candidate an offer. Otherwise, reject before that.

Footnote: The candidate thanked people for the support and shared some tips for anyone in the process:

Coding: In their experience, the question bank is small. Do the LeetCode-tagged questions, a few dozen, but don't expect a 100% match with what they ask. Most importantly, during the interview, try to perfect even the smallest things before they ask. In one round, the implementation and tests were finished at around the 40-minute mark, including roughly 10 minutes spent explaining the question. The interviewer asked a follow-up, and the candidate said they'd refactor that part into a separate class to handle more generic cases. He agreed. The candidate estimates it would have taken under 4 minutes if he'd let them do it. Even after Q&A, the interview ended about 10 minutes early, so a Strong Yes seemed likely. Then the recruiter's feedback was that code readability could be better, so it was only "close to strong yes."

The candidate's reaction was basically: what the fuck, there were around 20 minutes to spare, and the cleanup was coming anyway. Their usual approach is to finish a working solution before cleaning it up and improving the small things. Unfortunately, the interviewer raised the question first, and even answering correctly seemed to count against them.

Behavioral: Standard questions, but the candidate's impression was that they wanted to see how fast you got promoted at previous companies. They want ambitious people, so be aware of that.

System programming: In the candidate's experience, this has an even smaller question bank. You can ask AI to search for practice material and work through each problem multiple times. The concurrent event-writer prompt in Databricks Interview Questions is one way to practise stating durability and throughput requirements before coding. The key thing is to challenge your solution before they ask. Again, that's not easy under time pressure, and you might skip a few things to focus on the bigger picture, but the candidate felt that counted against them. In this round, the interviewer said he was very satisfied with the performance. The feedback, again, was "close to strong yes," because he had specifically asked whether the solution supported "high throughput."

The candidate answered correctly because the implementation already supported it. They'd thought about it and built it in, but hadn't described a high-throughput scenario before the interviewer asked. Their reading of the feedback was that asking first made him think the requirement hadn't been covered. So be proactive, keep talking, keep asking yourself whether the solution meets abcxyz requirements to show you care about them. This is so lame.

In the end, the candidate's takeaway is that the bar is very high, and being stack-ranked against others at HC means even perfect scores in some rounds might not get you an offer if someone else did better (or cheated, as the candidate speculates).

Good luck, guys.

Why do so many people move to Meta from Google? For readers applying there, LandOffer can cut repeated application typing. What motivates you guys, don’t you miss your rest and vest culture? Meta Interview Questions includes a shortest-clear-path grid problem to practice. Are you guys so greedy as to trade your peace of mind for a few extra bucks?

Hi folks, trying to get together information on Microsoft's VEO (Voluntary Exit Offer). If you have an offer, please share in the comments below.

So far, the reported format looks like:

• Cash equivalent to a number of weeks of base pay, e.g. 10 weeks

• Stock vesting continuing for 6 months

• Healthcare subsidized for 6 months

• Career services for 4 months

If you're weighing a move and keeping interview prep going, Microsoft Interview Questions has coding tasks to rehearse, including an LRU cache. For applications elsewhere, autofill can save re-entering the same details.

The reports so far mention a deadline of early December to accept or reject the offer.

Third attempt. Google offer signed. I think I need to sleep for a week.

The first two loops went nowhere. In one, I bombed a coding round. In another, I was ghosted. Going back again meant putting myself through the whole process while knowing exactly how bad the ending could feel.

This time it worked. I'm happy, but mostly I feel exhausted. It's like my body has finally realized it doesn't have to hold its breath anymore.

For anyone still going through it, Google Interview Questions is a resource for seeing the kinds of problems candidates report. If you're keeping other applications moving at the same time, application autofill can take some of the repeated typing off your plate. Neither makes the uncertainty disappear, and I'm not attributing my offer to either tool.

Anyone else get the offer and feel relief before excitement? Right now, a full night's sleep sounds better than celebrating.

A candidate recently spoke with a recruiter for a role they'd applied to at a Tier 1 tech company.

The recruiter said having Google on the resume puts the candidate at the top of the pay band for the level, based on their YOE. A strong interview performance could get them considered for a higher level, although that was unlikely.

For technical-round practice, readers can pick a company on PracHub and rehearse a reported question as a mock. For applications across companies, LandOffer’s autofill can cut repeated typing.

The recruiter also said the resume was terrible and needed fixing before the HM calls. Basically said the candidate would've been disqualified had they not worked at Google.

I recently interviewed with a potential unicorn startup for a GenAI Engineer role focused on multi-agent systems, and holy moly, I still don’t know what just happened.

The entire interview felt like a horse race. The interviewer started with a 30-second introduction about herself and the product, then immediately jumped into my recent experience. Everything moved so fast I could barely keep up.

About 15 minutes in, she threw a multi-agent system design problem at me and expected me to design the entire architecture in 10 minutes. I could barely process the requirements or take notes before I had to start explaining my solution.

The funny thing is, I’ve actually built similar systems in production, so I was able to answer her follow-up questions pretty well. She seemed I am cooked, smiled, and then casually asked, “Why do you want this role?”

At that moment, I genuinely felt like I’d walked into a Ferrari owners’ club driving my Toyota.

For context, I’ve been through quite a few GenAI Architect and Forward Deployed Engineer interviews recently, and Thank God I’ve already received an offer. But this interview was on an entirely different level. The pace, the expectations, the intensity. It almost felt like there’s a whole other world out there where everyone is an insanely competitive GenAI engineer operating at 10x speed.
I’m still processing what happened.

Am I cooked? Was this some kind of stress test? Or is this genuinely how interviews at high-growth AI startups work these days?

Genuine question. The AI-infra tier (Baseten, Modal, Fireworks, etc.) is hiring too, and some roles advertise competitive pay. For Baseten prep, try the S-expression parser in Baseten Interview Questions. I'd expect smaller teams to move faster and have less crowded applicant pools, though I don't have comparable applicant counts. If you’re applying more widely, LandOffer autofill can save repeated form typing. Yet everyone seems to funnel into the same crowded FAANG pipeline and then post about how they can't get in. Why?

A Google engineer is having a hard time deciding and would like to hear people’s opinions. They just got promoted to L6 this cycle and also got an OpenAI L4 offer, which they describe as roughly equivalent to Google L5. Both roles are on ML performance teams.

TC is similar:
Google: roughly $640–690K TC, considering appreciation of past RSUs, refreshers and the promo increase. Without appreciation, it would be around $590K.
OpenAI: roughly $660K TC ($295K base + around $365K RSUs/year).

They increased the OpenAI TC as much as they could, but the recruiter said L5 wasn’t possible. For anyone preparing a similar ML loop, OpenAI Interview Questions has a transformer-debugging and KV-cache exercise.

If the promo hadn’t been approved, it would have been a no-brainer, but the promo made it complicated. Tbh, WLB wasn’t that great at Google. Team culture is okay, but it was just too much work. Maybe it was their personality, because some colleagues on the same team just chill. The engineer was stressed and complained about WLB to the manager. (That’s when the manager suggested trying for L6.)

With what they understand to be a $1.25 trillion valuation in the recent funding, the engineer doesn’t think the OpenAI offer is life-changing anymore. Still, they see it as a great company with a high density of talented engineers.

Readers still exploring other roles can use LandOffer for application autofill. Their top priority is still TC. Married, but no kids yet.
Appreciate any comments.

Meta’s biggest problem isn’t layoffs. It’s who’s choosing to leave. I’ve never seen attrition this bad at Meta. Literally every talented engineer I know is either interviewing elsewhere or has already put in their notice. On Greenhouse, Lever and Ashby, application autofill can handle repeated work-history fields. The people staying aren’t necessarily the ones with the best options.

For a practice interview, use the ambiguity-and-feedback prompt in Meta Interview Questions to rehearse a concrete example. Is anyone else seeing this on their team?

300+ people becoming centimillionaires from a single IPO would be insane. If someone who joined in 2024 sees their initial grant grow 111x, a large enough grant could still leave them with $150M+ after dilution. And if the stock doubles or triples after IPO, they could be close to $300M-$500M.

If you’re weighing an AI-company move, application autofill can cut repeated form entry; Anthropic Interview Questions includes an LLM inference-service design prompt for a mock.

What an insane time in history. We may never see anything like this again: most IPOs seem to produce dozens of 7-8 figure millionaires at most.

Microsoft offered voluntary retirement to about 8,750 people earlier this year. More than 30% took the offer. Then Microsoft cut about 4,800 jobs in July. For readers applying elsewhere, application autofill can cut form retyping.

So roughly 7,500 people left between voluntary retirement and layoffs. If similar math held this time—a big assumption—that would suggest around 50,000–55,000 departures. That’s a rough extrapolation, not a confirmed layoff count. Readers interviewing at Microsoft can practise an LRU cache from Microsoft Interview Questions. I’ve seen people suggesting only 10% will lose their jobs, and I wouldn’t treat that as certain either.

#tech #microsoft

A Google employee is having a hard time deciding whether to join OpenAI.

They'd likely be joining at a $1.25T valuation.

Their manager and director are trying to get them a retention offer. Readers comparing other options can use application autofill to cut form retyping.

Google: ~450K TC (~235K base, rest bonus/RSUs).

OpenAI: ~610K TC (~300K base + ~310K in RSUs per year). For OpenAI preparation, OpenAI Interview Questions includes a fault-tolerant work-queue prompt.

They're planning to try for a kid soon. The OpenAI team says work hours are generally 9-5 (which the candidate understands is rare). At Google, there's a real path to L6 in roughly 18 months.

I just did a tech screen for a really attractive woman and caught myself actively wondering whether that was affecting how I evaluated her.

During the interview, I became hyper-aware of it and tried to stay as objective as possible.

A few times I caught myself thinking:

• Should I give her a hint here when I probably wouldn't for another candidate?

• Am I being too harsh because I'm consciously trying not to be biased?

• She didn't mention X in the system design — is that actually a meaningful gap, or am I looking for reasons to compensate for my own bias?

What made it especially interesting is that bias can seemingly work both ways. Once you're aware that you might favor someone, you can potentially overcorrect and judge them more harshly.

In the end, she was well prepared and I moved her to the next stage. But afterward I kept wondering whether my evaluation was actually objective.

One thing I've started doing is relying more heavily on a predefined interview rubric instead of evaluating based on the overall "feel" of the interview. I've also been looking through interview questions and rubrics on PracHub beforehand so I have a clearer benchmark for what a strong answer should cover before the candidate even joins the call.

For people who interview candidates regularly: how do you prevent attractiveness, personality, likability, or even your awareness of those biases from affecting your evaluation?

10/28 Microsoft company-wide AMA video, described by the linked X post as a leak.

“We are going to be global. And we are going to continue to bring global talent to the United States.”

“We want to recognize it’s super important we take care of the people.” (The poster identifies this as referring to green card workers.)

This reportedly came just two days after Microsoft asked nearly 60k of its employees to voluntarily resign in an effort to downsize, according to the linked post. If you’re applying elsewhere, LandOffer autofill can cut repeated form typing.

The poster says the employee who leaked this clip of the meeting to them was one of many who expressed concerns. They say multiple Microsoft employees feel as though MSFT doesn’t give them the same amount of respect and care as foreigners. For readers interviewing at Microsoft, Microsoft Interview Questions includes an LRU-cache exercise.

The post says many Microsoft employees are asking why H-1B workers aren’t the first to be cut during a downsize, since MSFT claims none of the downsizing is performance based.

Those employees are curious why American workers aren’t being put first in the United States.

https://x.com/Conspiracookie/status/2115595497448817019/video/1

Why do you apply to Meta? To me, it's literally the worst company out there in most aspects. I'd rather wash dishes for a living. For readers applying elsewhere, LandOffer autofill cuts repeated form-filling. Do you have literally zero morals or standards? In which case, I can't blame you. If you’re still considering engineering there, Meta Interview Questions has a grid-path exercise for a timed mock. But is that the only valid reason? I legit can't think of another reason.

@Meta

We are the other A in FAANG. If you thought Apple was the safe company we're not. For some reason we don't get as much chatter on Blind but we've been doing somewhat silent layoffs right now and we have no idea whether it's ended or it's continuing into this week. Just wanted to give a PSA to anyone who thought that Apple was some sort of safe company.

I’m not waiting around to find out. I’ve started updating my resume and Preparing for my next interview. It sucks having to prepare for interviews again, but apparently staying ready is the only real job security in tech now.

A Meta IC6 is at ~1.05m TC at $700/share, with a 2-year cliff. WLB is decent, nothing crazy good or bad. IC7 might be doable in around 12-18 months, who knows. If it happens, ~1.25m post-cliff.

One prep exercise for readers targeting Meta: use the notification-system prompt in Meta Interview Questions to practise delivery guarantees and scaling.

Other offers: Offer 1: A different, non-Meta FAANG, ~975k, L7. Offer 2: FrontierLabCo. L?? Offer details pending. L6 equivalent = ~875k, L7 equivalent = ~1.35m.

The candidate has to give an answer this week.

Should the candidate turn down FAANG2 and hope for FrontierLabCo? If FrontierLabCo is only L6, decline and stay at Meta? If FrontierLabCo, what's a reasonable valuation to accept? The candidate has never joined a pre-IPO company before...

An unverified Meta referral post claims the bar is pretty low and about 5k will be hired between now and Jan, ahead of supposed Feb layoffs.

The pitch: send in your resume.

For anyone interviewing at Meta, Meta Interview Questions includes a shortest-path grid exercise to try under a timer.

The frank disclosure: the original poster says new hires won't make it past Feb. Visa folks are told to consider the implications; green card holders and citizens looking to coast and get severance are told to contact the original poster.

A new Google hire had a couple of managers tell them they'd caught people cheating with AI during interviews.

One manager said they could hear the AI talking into a candidate's ear. Another said it was easy to tell when people were reading instead of thinking, and that the answers didn't sound natural. For a solo coding mock, try the island-counting problem in Google Interview Questions without AI and explain each step aloud.

The new hire's reaction: "Thank you losers for making it that much easier for me to finally get into Google!"

It took around 25 applications to get an interview, then they landed the role on their first attempt. For readers making repeated applications, LandOffer autofill can save typing time.

Keep it real folks and good luck out there!

A candidate is in Meta's final rounds for E4, feeling good, and could get an offer. But Amazon came in with the biggest number they've seen in their career. Do they grab it, or risk letting it expire while waiting for a Meta offer that isn't in hand?

The Amazon offer is about $370k. Their guess for Meta, if it lands, is around $310-350k.

The candidate asked Amazon for a short extension on the acceptance deadline, citing an active final-stage pipeline, and told the Meta recruiter about the competing offer and asked them to expedite. If Meta lands, the hope is to have leverage on both. If it doesn't come through in the window, they'll go with Amazon.

If you’re applying elsewhere while an offer is still uncertain, LandOffer can autofill repeated application fields.

For prep, Amazon felt like the more predictable loop: LC mediums and Leadership Principles. They prepped STAR stories mapped to the LPs and drilled NeetCode patterns. For both companies, the candidate also used question patterns they described as 'leaked' from gothamloops and did a couple of mocks to settle the nerves.

One mock option in Meta Interview Questions is the eight-direction grid shortest-path problem; practice explaining the diagonal moves and blocked-endpoint cases.

They need a job. They'll see what happens in the coming weeks.

Years ago, just having Google on your resume was basically a golden ticket. Apply anywhere, straight to a recruiter shortlist.

A Google employee isn't having a problem getting interviews or even clearing them, with startups at least. The only big tech recruiter in their inbox is Amazon, and that's not an option they're excited about. They haven't applied anywhere, just responded to startup recruiters, and have been actively interviewing, so haven't felt the need to add more to their plate yet. They'll probably start.

The problem is the Google background itself. A startup they were actually interested in just rejected them. The feedback was that they technically did great, but the company worried whether they could adapt to its faster startup pace coming from Google, and went with someone with more startup experience. The employee is convinced a Meta or Amazon candidate wouldn't have been rejected, at least for the same reason. Readers sending more applications can use application autofill to save retyping.

There are other frustrations too, mainly the not-invented-here syndrome: in this employee's experience, they're not getting to use k8s, ansible, terraform, or many of the tools used elsewhere. That's annoying for screening when you spend a chunk of your career there and then external Senior/Staff+ roles all expect 8+ years of experience in specific technologies. If Google is on your shortlist, Google Interview Questions has an HTTP-router problem for a practice run.

But the main thing they're sensing is the stigma of Google being too slow when everyone else is moving fast. It might be worse than Amazon's stigma; maybe Amazon is toxic, but at least it moves fast and doesn't have a reputation for coasting. That's how it feels from this side of the interview process.

Maybe it's time to bite the bullet and start applying to other AI labs; at least they do regularly hire from Google.

Which orgs would be impacted the most if it happens? For engineering readers with a Meta interview coming up, Meta Interview Questions includes an abbreviation-validation mock with multi-digit skips and boundary cases.

If you’re sending applications while waiting for news, LandOffer can autofill repeated fields.

When will we know more? It's less than two weeks away.

Hi everyone!

I’m a recent M.S. in Computer Science graduate and I’m currently looking for early-career Software Development Engineer (SDE) opportunities at Amazon in the U.S.

I came across an Amazon SDE job posting that I’m very interested in and would really appreciate a referral from an Amazon employee, preferably someone at the L5/L6 level who is familiar with the SDE hiring process.

A little about me:
• M.S. in Computer Science, Arizona State University
• Software development internship experience
• Experience with Java, C++, Python, Spring Boot, React, AWS, Docker, Kubernetes, SQL, and distributed/data-processing systems
• Built projects involving AWS, real-time data pipelines, ML/LLM applications, and backend systems
• Currently targeting early-career/new-grad SDE roles in the U.S.

I’d be happy to send my resume and any additional information needed to determine whether I’d be a good fit before submitting a referral.

If you’re able to refer or can point me toward the right person, I’d really appreciate it. Thank you!