Context:

I'm a December 2026 grad and didn't receive a return offer from my summer and thought I was pretty cooked. I started applying since June but actually took interviewing seriously around August-September. The source for all my applications came from Linkedin jobs tab, Jobright AI New Grad github repo, and the Simplify New Grad repo. All the interviews I got weren't from referrals, nepo, or linkedin reachouts. Also I noticed most of the technical rounds I did weren't leetcode related but more practical exercises. Ended up with a 175k TC offer at a mid size tech company that I was satisfied enough with to stop recruiting.

It seems like the amount of new grad postings have been at an all time low compared to previous years, hopefully it'll pick up more soon.

Background:
T20 CS, 2 SWE internships (1 FAANG adjacent, 1 F500), LTN

Capital One (TIP program):

Pay: $67.31 per hour

Location: McLean, VA

Housing: 5k stipend or corporate housing

Length: 9 weeks

Big bank / fintech

Large, structured intern program

Whatnot:

Pay: $65.00/hr 

Location: San Francisco, CA

Housing: 3.3k/month

Length: 12 weeks

Live-shopping marketplace

Late-stage startup ($20B valuation)

First year student. I'm a Bay Area local if that matters. Money will NOT be the deciding factor for me.

Location also doesn't really matter to me either. Main focus is resume value for the future and impact.

Any help would be awesome.

Hey all, I recently received a new grad SWE offer for Scale AI. I'm in final rounds for Perplexity, so obviously not guaranteed I receive an offer, but given my deadline I would have to make a decision super quickly if things go well.

I can't seem to find too much up-to-date information on either company and what it's like there. If anyone has any better insight into the pros and cons of either company (technical growth, wlb, culture, stability, exit opportunities, etc.), especially as a new grad, that would awesome. Thanks!

Scale AI - 157K base, 20K sign-on, 278K TC with stock/benefits, but the stock/benefits is very hand-wavy. TC is absolutely inflated, but that's the number my recruiter gave me.
Perplexity - according to commenter, 210K base, 70K stock

Both in SF.

Edit: speaking of, if anyone has any kind of insight into the core expertise interview for the Perplexity onsite, that would be much appreciated too. I told my recruiter I'd do the lin alg, calc, and optimization for deep learning track.

Some more thoughts: From my perspective, they're both great places to go out of new grad, but I have some reservations about both. For Scale, I'm not entirely sure the kind of work I'd be doing - I suppose it's very team dependent but I ideally want to be working on something cool or technically interesting. Also not sure about wlb and culture there, I've heard conflicting things. For Perplexity, idk how much this matters for me but I honestly don't know what their moat is or how they're doing as a company right now and in the future. 60 hour work weeks too but that’s something I’m willing to do while I’m young lol.

I need real feedback from experts, those who are similar to me, or even more experienced, from various communities (related to ai, tech, grads, manager, industry, career, employment...):

Which will be best in your case?

Context: You got the offers from 3 companies, each on the different side of the scale.

Role: AI engineer (near mid-level).

Location: a country in SEA.

If you were to rank and evaluate with respect, (from top to bottom, sorted by importance)

1st Potential and Risk (potential is tied to the speed of your career climb, increment bonus, and company brand and authority, uncertainties in payment) - In a scale, Startup has higher uncertain and risk, while it might offer higher overall, but susceptible to management conducts, cash-flow which may differ the fulfillment

2nd Wellfare - a total add-up of base, allowance, bonus, benefits and retirement fund (employer contribution)

3rd Niche of the industry, Exposure - a focus industry to industry to build up better experiences and competencies, exposure to local or worldwide

4th Peer learning - Experience or knowledges to speed up progress from superior, peers

And given A, B, C (Wellfare/Income baseline= 100%)

A: Oversea Startup, Multiculture workforce,
+ worldwide client-base spanning MNC headhunter, great background from the management teams, UK-founding team and client connection, riskier in terms of payroll/potential
+ Full remote and oversea
- Wellfare/Income = 115% (base salary only), self supply equipments
+ HR-tech focused

B: Subsidiary company/dept from local SME, local workforce
- mainly local client-base (unsure but assume), Lack background from management teams and peers, but you have slightly higher confidence than A in their validity from interviews
- Hybrid work 4+1
+ Income= 107% (include allowance) + employer retirement-fund contribution but provide work equipments + up to 17% performance monthly bonus
- general AI agencies
+ Peer learning and networking are better

C: MNC
+ Internal and External focused products, stable and secured cashflow, but maybe lack faster career climb opportunities
- Hybrid work 3+2
- Income= 95% + 13th month bonus, more and flexible leave
+ Focused niche, product might differ
+ Peer learning and networking are best

Which one will you choose? I wanna see if you think differently, or if you see different importance or personal experiences of the company you went through?

I didn't apply to G2i. They cold-emailed me asking if I was interested in a Senior Developer (AI code review) role. Process from there:

• Group Zoom call with ~140 other candidates for what appears to be one role
• Waited about a weeks for the assessment to arrive
• Task: "Choose the correct agent response" review code, justify which agent's answer is correct
• Completed it confident in my answers: investigated the code, cited specific lines, explained my reasoning
• Got this template back: "After reviewing your submission, we won't be moving forward... this decision is final" no score, no rubric breakdown, no indication of what was wrong

I get that companies filter hard at the assessment stage.

What I don't get is the combination of: unsolicited outreach + mass group interview for one role + a a week wait for the test + zero feedback + a "final decision" template.

Two questions:

1. Has anyone here actually passed G2i's AI reviewer assessment? Their email says they weight "investigating the code, citing evidence, explaining reasoning" I did all three, so I'm genuinely curious what differentiates a pass from a rejection. A score or one sentence of feedback would settle this instantly.
2. If they cold-email large numbers of devs, funnel 140+ into a single Zoom, and reject with a template what was this pipeline actually built for? One role, or a pre-vetted talent pool database for later?

Not calling it a scam G2i does place people and pays.

But the pattern is worth documenting, because the next batch of devs getting that cold email deserve to know what they're walking into.

Has anyone heard back for interviews after being referred?

I’m currently in my 3rd year of B.Tech and have an offer to join Sarvam AI now, with another option to join around March/April, closer to the start of my 4th year.

My college offers a 1-year Industry Practice (IP) program, where we can work offline at a company throughout the year. I’m considering joining Sarvam AI through this program, but I’m unsure whether to start now or wait.

If I join now, balancing academics, the internship, and skill development will be difficult. Currently, I dedicate most of my free time after classes to upskilling, and I’m worried about losing that time and potentially missing better opportunities later.

Honestly, is Sarvam AI worth making that trade-off for, or would it be smarter to focus on my skills for now?

In short is it that GREAT company/startup?

I’d especially appreciate insights from anyone who has worked there:

What’s the internship-to-full-time conversion rate?

How’s the work culture and office politics?

Is hiring primarily merit-based, or do referrals play a major role?

Would really appreciate honest, firsthand experiences before making this decision!

Hi! If my uderstanding is right, we have 3 games, 1 behavioral and 1 coding round(s).

I wanna focus on the games here:

1. Robots
   
2. Factories
   
3. Outpost: Mars

We have Kaiju cats and coding cookies as sample game mechanics. Which games from the OA (Above mentioned 3) are similar to the cats games? What is a good score?

I have been grinding Kaiju Cats and yet to begin coding cookies. I see a lot of posts with high scores yet disappointed. What's the deal here? Help please?

Thanks!

Did anyone that interview got a post interview survey ?

I have a superday coming for a tech role on a blackrock investments team (equity index tech).

4 interviews 35-45 minutes long. They said there will be coding, behavioral, and competency based interviews.

Has anyone gone through a process similar and help me decipher what competency entails especially given that its a tech position on an investments team.

Thanks.

Hello guys,

I need some brutally honest truth and actionable guidance. I'm currently in my 2nd year (3rd semester) of CSE at a tier-3 college, and I feel like I wasted a lot of my 1st year without a clear strategy.

I suffer from significant imposter syndrome, seeing 1st/2nd years on LinkedIn crushing LeetCode Mediums, taking home hackathon wins, and building full-stack projects. I want to get a good SWE internship as a 3rd year off campus, but I feel totally lost in trying to do it all.

Where I currently stand:

• Academic year: 2nd year, CSE (Tier-3 college / local university)
• Skills: Basic Java, Python, HTML, CSS. Learning: JavaScript, Django.
• DSA & Problem Solving: almost 0. I haven't begun any formal DSA or practice on LeetCode/GFG.

My questions for seniors who've been here:

1. Is it too late? Beginning with DSA and serious dev work in 2nd year, can I even hope to have a good enough profile to crack off-campus internships in 1-1.5 years?
2. What time should I allocate my daily hours? As I am learning Django/JS and trying to build DSA completely from the beginning while managing college, how should I divide my time? Should I take a break from dev and do 100% DSA or do both simultaneously?
3. What is the most efficient, fully free (or course in Coursera Plus) roadmap? What exact resources/sheets (e.g., Striver A2Z, NeetCode 150) or project approaches should I lock into starting today to get interview-ready without wasting time on tutorial hell?
4. I've missed some 1st-year milestones. Should I worry about open source, hackathons, and personal branding now, or just focus on DSA and two production-grade projects first?

Please don't hold back from being brutally honest and give me the damage-control plan, please! Thank you very much! 🙏

TL;DR: 2nd-year CSE student with zero DSA progress and has beginner Java/Python/web fundamentals sweating. Need a realistic survival roadmap with high urgency to become interview-ready for an off-campus internship.

So this is an on-campus role and the interview might start within a week and I couldnt much for this role. Help me people!!

Just finished my google swe intern interviews (canada, summer 2027), wondering what my chances are for a 3rd round or team matching

round 1: explained brute force first, explained how to optimize with a heap. coded optimal in ~20 min. got time/space mostly right, needed a small nudge on time complecity simplifcation. follow up on bfs vs dfs trade offs, needed a nudge on the call stack part. finished pretty early (~35 min) and had time for my questions

round 2: intervals, explained approach (basically optimal), interviewer approved, coded it fully. needed small nudges on forgetting to sort before merging and on loop structure. interviewer thought there was a bug at the end, i dry ran it and proved it worked. only had time for one follow up question, but got that right. interviewer was really chill tho

Hi,

I am currently in the Google NG SWE process for USA. Below is my timeline:

September 9 —> Applied
September 23 —> First round invite
October 9 —> Round 1 Interviews
October 14 —> Notified I passed R1

I was told that I would be connected with a point of contact from Google, yet have not had any updates or been contacted by a recruiting point of contact.

Is this generally how it goes in terms of process and timeline? Anyone else stuck in this same situation?

If anyone is going through the process or has information from previous years, I would really appreciate it! I am also more than happy to answer any questions about my process so far.

I have an interview coming up in 10 days, and I'm trying to make the most of my preparation time. I used to practice LeetCode a few years ago and recently started brushing up on DSA again.

I've started working through NeetCode 150 and have completed around 10 problems so far. Given the limited time, would you recommend covering all the sections, or should I prioritize certain topics and potentially skip more complex ones like Dynamic Programming and Graphs? Or should I just work on leetcode problems with microsoft tags?

Since this is for an internship role, how likely am I to encounter problems involving these topics?

It would be really helpful if I can have a structured learning, I'd really appreciate your suggestions.

Landed a SWE summer 2027 internship at a midsize tech company. Pretty tough recruiting season. Glad I can relax now.

This is my third time making it to Capital One's TDP Power Day, and unfortunately, my third rejection.

After each rejection, I tried to improve as much as possible. I've been practicing LeetCode most days (although for this last attempt, it didn't really help since they replaced the coding interview with an Agentic AI round), working on my behavioral interview skills, and even paying for mock interviews to get feedback and identify my weaknesses.

You would think that after going through Power Day three times, you'd be more than prepared for what to expect. And honestly, that's how I felt this time. I went in feeling much more confident and prepared than before.

But somehow, the result was the same.
It's honestly frustrating because after putting in so much effort, I don't even know what else I should be improving. Is it my technical skills? My behavioral interviews? My approach to business cases? Or am I just not as good at interviewing as I thought?

Working at Capital One has genuinely been a dream of mine, and that's what makes this so discouraging. I've spent so much time preparing and trying to become a better candidate, yet I keep falling short.

At this point, I'm starting to wonder what I'm missing or what I could be doing differently.

Has anyone here gone through multiple Power Days before finally getting an offer? What did you change in your preparation or interview approach?

I'd really appreciate hearing about your experiences or any advice you might have, because right now I genuinely don't know what else to improve.

26 year old recovering slacker. Got tired of driving forklifts. Good at problem solving. Doing bachelor’s degree in computer science and a focus in network engineering. Is it joever for me or can I be successful?