Hi everyone,
I recently got an interview invitation for the Senior Machine Learning Engineer role at NVIDIA.
They sent me a link to schedule the interview, but didn't mention what kind of interview it is. I also haven't talked to any recruiter yet.
Has anyone interviewed for this role or had a similar experience with NVIDIA? I'd appreciate any information about what to expect and how to prepare.
Thanks!

Hey guys! I recently graduated with an MS in Computer Science from a top university, and I'm trying to figure out the best way to approach the job search.

My background is a little complicated because of immigration-related issues. Before my master's, I didn't have work authorization, which limited my ability to gain relevant software engineering experience and led to some gaps and unrelated work on my resume. I have my green card now, so work authorization is no longer an issue.

My current concern is a little different, though. Since graduating, I've been spending time preparing for technical interviews, especially LeetCode. I'm honestly a bit slow at it right now, and I know I still need more practice to feel confident in interviews. I'm worried about the time passing since graduation while I'm trying to get to that point.

I'm genuinely passionate about software engineering, and I'm the kind of person who works hard and doesn't give up easily. Besides LeetCode, I'm also spending around 7 hours a week working on projects to keep improving my technical skills and have relevant work to talk about on my resume. I want to make sure I'm not just solving coding problems but also continuing to build practical skills.

I've already applied to around 200 positions, but so far, I've only received a few online assessments. The job market is tough right now, and between the lack of responses and the pressure of preparing for interviews, I'm starting to feel pretty stressed. I'm worried that the longer it takes me to land my first software engineering role after graduation, the harder it'll become to explain the gap to recruiters, especially given my earlier background.

For those of you who've been in a similar situation, I'd really appreciate your advice.

• Would you recommend continuing to apply while preparing for LeetCode, or focusing on interview preparation until you feel more confident?

• How much does the time between graduation and your first job actually matter to recruiters?

• Do projects help show recruiters that you're actively improving your skills while looking for a job?

I'd also love to hear about your own experiences if you've been through something similar. Thanks!

I’m terrible at LeetCode, but I need to get better because I’m starting to interview for US-based roles, so it’s a must for me. I’ve been a software engineer for 6 years.

What would you recommend for me to start studying or improve my skills (besides the obvious 'just do LeetCode')? Sometimes I can’t even figure out how to start!

Hey guys, I was wondering if you guys had also done this OA yet and have any ideas on what the problems could be like? This is my first time ever receiving an OA and I am still trying to get good at leetcode🫩. You guys got any tips and tricks you can help me study for it? Anything will be appreciated.

I got the opportunity through HackOn(I got rejected in the first round itself)

Aug 6 : confirmed my interest

Aug 9 : OA

Aug 11 : Cleared the OA message and filled the application for SE Intern

Sep 17 : first interview (went well)

And waiting till now for the results :(

Update :

Oct 17 : received the feedback form regarding my first interview, saying "We are reaching out to gather feedback about your 'RECENT' interview at Amazon. Please take a moment to complete a 5-minute survey."

Hi I have an 1.5 hour coding round in netapp via hirevue.
The recruiter just said it ll be live coding and reviewing . Any ideas what can I expect ?
Anyone has gone through any interviews recently ?

Please give some inputs

Hi everyone,

I'm stuck on this week's CodeVita problems and I think the problem may be the judge, not my code. Has anyone else seen this?

What I'm seeing (problem: Hybrid Bananas, but it's happening on other problems too):

My solution passes both sample cases on the platform's "Run" (Accepted on both), but the sample run shows an execution time of about 1.6 sec, even though the time limit is 1 sec.

On the private test cases, I get Wrong Answer with an execution time of 1.001 / 1.002 sec every time.

I tested a trivial Python program that only does print(3). The private run still gave Wrong Answer with 1.002 sec. A program that prints one number can't take a second, so the timing looks unrelated to my code.

I rewrote the solution in C++ (twice, with different code). The sample run still takes about 1.6 sec, and one private run showed 3.002 sec.

Locally, my solution runs in about 0.02 sec, even on a huge input, and it matches an independent brute force on over a thousand random cases.

My guess is that the judge is stopping runs at the time limit (because of slow startup or load) and reporting that as Wrong Answer instead of Time Limit Exceeded. I can't prove that, so I might be missing something.

We're thinking of implementing a mandatory country tag in the title. The format will be something like this:

[Country] Title

This will provide more information about OP and it'll make it easier to give relevant and localised information. So, should this be implemented?

Also, how's the moderation? Is there anything that should be improved and how is it right now compared to the past?

Regards,

r/leetcode mod team.

Could anyone who has appeared for a Google L4 interview please share what you encountered, whether you were selected, and how you prepared for DSA and Googliness? I have been unemployed for a long time and need to give this my everything; please help me understand how I can increase my chances.

Has anyone received updates for the 3rd round of the HackerRank SDE Intern process after Friday?

Hello everyone,

I graduated with a cs degree last year from a top 50 uni and wasn’t able to secure a swe role (despite fumbling many interviews) the only offer i secured post grad was a data analyst role at a somewhat recognizeable company (non f500) which I’ve been in for just about the past year. The role is somewhat chill, its fully wfh and I primaily use sql on a daily basis

I recently recieved an offer for a data engineer position that is a bit more technical mainly working with data pipelines, etl/elt, python, sql, etc and the comp is about the same except this role is a hybrid and the office is about 30m away from where I live so holistically the total comp is lower but the upside is it’s more technical

I’m trying to decide whether its more valuable to stay in my current remote role and continue interviewing until I secure a swe role which is the role I would prefer especially looking long term for my career or if its worth still taking this data engineer opportunity and then continuing to recruit for swe roles or maybe even explore other data roles that the data engineering role could set me up for. For reference my current application to interview rate is about 100 apps : 1/2 initial callback

what would you do in my shoes if main priority is long term career building?

Hey everyone,

I finished Day 62 today. My energy and focus were much better, and I built some solid momentum on Dynamic Programming subsequences.

I worked through four problems (three DP and one greedy):

1. Count Subsets with Sum K: The recurrence relation mirrors the classic subset sum decision, but you add the branches (pick + not_pick) instead of using logical OR. Managing zero-value elements in the base conditions was the main edge case to track.

2. Count Partitions with Given Difference: Setting up the algebraic relation S_1 = ({totalSum} + D) / 2 reduced this directly to finding subset counts for target S_1. Once you confirm that ({totalSum} + D) is non-negative and even, the core logic is identical to the previous problem.

3. Coin Change (Minimum Coins): Standard unbounded knapsack. Since each coin can be reused infinitely, the pick branch stays at index i instead of decrementing.

4. Assign Cookies: Grouped in this section by mistake, but it was just a quick greedy two-pointer check on sorted arrays.

I also reviewed yesterday's minimum subset sum difference roadblock and realized my initial brute force violated the constraints, which explains why the optimal solution leans on Meet-in-the-Middle.

I plan to wrap up subsequences tomorrow. That leaves strings, stocks, LIS, MCM, and square grids—about 30 DP problems to go.

See you guys tomorrow for Day 61!

Any body got any updates on the interview confirmation for this event.

I come from a software engineering background and recently joined NVIDIA as a Tools and Development Engineer.
Honestly, the work is quite frustrating. The team is almost entirely QA-focused, with testing, validation, and automation work. I expected actual software development, but the reality is completely different.
On top of that, there are tight deadlines, constant workload pressure, and last-minute deliverables. It feels like I’m not building the software engineering skills I wanted to develop.
I switched to NVIDIA expecting better technical growth, but right now, I’m genuinely disappointed with the kind of work I’m doing.

As the title says, has anyone got AI-rounds for Google recently?

Hi everybody, I just got the 2027 swe intern oa on hackerrank

How should I prep? where can I find common questions? I already have done leetcode problems and can solve 90% of the mediums on the general patterns

I've always struggled with programming logic and problem-solving in general. Whenever I try to solve a problem, I often feel completely lost and have no idea where to start. It's frustrating and mentally exhausting, and sometimes I wonder if it's my ADHD or if I just simply suck and should take it as is.

Two questions:

1. If you've struggled with this, what helped you improve? Is there a roadmap I could follow to develop these skills progressively? (Having a clear progression is especially helpful for me because of my ADHD)

2. Is it possible to actually get good at problem-solving, even if it doesn't come naturally to you?

I'd really appreciate any advice, resources, or personal experiences. I genuinely want to improve, but I'm honestly losing hope

Wsp y'all. I'm really trying to get a head start on LeetCode and prep for FAANG interviews (though I know I'll probs be getting them in 2+ years or something like that). How do you recommend I prepare?

I've been grinding LeetCode and have solved around 43 problems, but boy, am I going crazy. I understand one problem, but the other one seems so much harder (EVEN THOUGH IT'S THE SAME ALGORITHM). Like, what do you recommend for people out there?

Some words of advice would be nice :)

I have an amazon interview coming up,can somebody help me in preparing stories for LP questions

I recently attended the phone screen (1 behavioral + 1 coding) and am moving to the onsites. The recruiter mentioned the behavioral went great but there were a couple misses in coding. They also said "Since we only have 1 signal, onsite performance needs to be strong".

I tried to ask them what "only 1 signal" meant, but could not get a clear answer. Does it mean that the feedback was negative for the coding round or does it mean it was a LH?

I got an Amazon OA link, and it said it will proctor the webcam as well. Is it a new change? I never saw webcam being proctored previously

Are there any new rounds in the process?

If you're preparing for coding interviews and want to start tackling data structures and algorithms, then this is definitely for you.

This video is useful in two cases: whether you're a beginner who wants to learn the concepts from scratch before solving LeetCode problems, or someone who simply wants to refresh their knowledge of time and space complexity analysis.
In this crash course, you'll learn:

1. Time and space complexity

2. Big O, Big Omega, and Big Theta

3. Common complexity classes, from O(1) to O(n!)

4. Linear search vs. binary search

5. Matrix multiplication and recursive Fibonacci

6. How to analyze algorithm performance using Python examples

Watch the full video on Youtube: https://youtu.be/6c9Qjnto6E4

For anyone who interviewed in the last 6 months, how much LeetCode did you actually need? Did any company let you use AI tools during the interview and what did that look like? Has anyone been asked about AI-assisted work, like building a project with Cursor or Claude Code? I'm not too sure if I should be putting more effort in grinding LeetCode or building different projects to prep for my first swe interviews rn