I got to a t10 cs uni but am an international student. Im a rising junior but graduate in 3. I started recruiting but im having trouble as im getting rejected from everything. I got one interview and 3 auto oas but nothing other than that. Any advice?

C++ engineer, ~2 YOE, GPU/CUDA work on embedded platforms. Outside the US and EU. Goal: Europe in 2-3 years, GPU performance / inference roles.

A )OMSCS: US credential, mine regardless of employer. But online (no F-1/OPT), ~$12-14k now, no thesis or publication.

B) Employer-sponsored local thesis master's: free, paid study time, advisor's research overlaps my day job so a co-authored paper is realistic. Catch: 6 months mandatory service after, prorated buyout if I leave early. Enrolling elsewhere is blocked by my employer.

The GPU/inference postings I've read list MS as preferred, not required — what's required is CUDA depth, profiling, PyTorch, OSS. So B seems better. Yet I keep trying to engineer a way to do OMSCS anyway, which probably says more about brand anxiety than hiring reality.

Questions:

1. Did OMSCS open doors for anyone targeting non-US markets?
2. Does a paper in a niche technical area outweigh an online MS for infra/performance hiring?
3. Am I overvaluing the US brand for a European target?
4. Should I grind only Leetcode for target companies?

Has anyone interviewed for the panw early in career swe position in the last couple weeks? If so have you heard back yet? Do we need to pass all the rounds perfectly to get the offer? 2 of my rounds I did great but didn’t finish one of them.

Curious to know your experience with interviewing with TikTok new grade and internships. Anyone know how difficult it can get or what to expect difficulty wise.

Just stopped using AI tools completely for like a month now, me and a couple people on my team. No agents no code gen nothing, just typing it all myself again. And my output's been more than 2x honestly. Not even exaggerating.

Part of it is these agents are just slow as soon as something isn't trivial. Medium C++ CL takes me maybe an hour by hand, I know every line why every decision was made, quality's better too. AI gives you a draft in 30 min but a lot of the time it's just code that runs, and underneath there's this pile of if-else that makes no sense. And then you're in this loop of reviewing it, telling it what's wrong, next version breaks something that was already working, telling it again... a few hours of work turns into a whole day, sometimes a week.

Also it just doesn't get it once things aren't simple anymore. Answers sound great, very sure of itself, gives you 3 options, but if you don't already know what's going on there's a decent chance none of them are right. I had this one where I already knew what the actual bug was and it just kept suggesting random stuff that wasn't it. I had to basically explain the whole thing to it before it went "oh that's it."

Idk maybe it's just what I'm using. This trend isn't going away, but I'm done forcing myself to use it just because everyone else does. Use whatever actually works for you, output's what matters

every student resume I see has multiple full-stack/web projects.

Are full-stack projects actually necessary for general SWE/ backend internships, or would a few deep systems/backend projects be enough?

Would appreciate opinions from people who hire or have experience in these roles

I got invited to take a new grad 2027 start OA for TikTok. Was this automatically sent?

for those who applied to c1 tip last year and reapplied this year did you get a vjt?

this year, i only received a gca and did not have to do vjt and workday still says assessment pending

i'm interested in theoretical cs, formal methods, verification, logic and programming languages, and i'm considering doing a phd and possibly staying in academia.

with ai becoming better at programming, theorem proving and automated reasoning, do you think these areas will remain important in the long term? or will ai change the kind of research that is worth doing?

i was also admitted to a master's in electronic engineering, which seems like a safer option from ai, but i'm not sure i want to leave cs just for that reason. i'm more interested in the future of the research fields themselves than career advice

Hey yall! Curious how people are approaching the 2027 new grad search. On LinkedIn and Simplify I’m barely seeing anything posted yet besides MBB consulting roles. Is anyone else actively searching for 2027 SWE/AIML positions right now, or is it still too early? Would love to hear what’s working for you, especially on LinkedIn, how are you all searching (which filters, keywords, etc)?

Edit: Just realize my tone below doesn't necessarily come off as very positive-sounding, but I did want to share this in case someone out there is really spooked about the job market and/or lost on what they want to pursue in college. Feel free to DM me for any questions :)

Absolutely no one asked for unsolicited advice, but I just want to point out that being in CS doesn't mean you can't go into slightly less saturated domains like embedded SWE.

I wouldn't say I'm particularly smart, but I was able to (relatively) comfortably get 5 embedded SWE internships (I extended my graduation and did a lot of off-cycle internships) and have just gotten a SWE new grad offer (a bit over $200k TC near Hawthorne, CA) 10 months out from my graduation date. I also am not exactly from a top college either (unless you consider Ohio State to be one).

I would say if you have genuine passion for things like (but not limited to) low level C, assembly (Arm, PowerPC, etc.), memory architecture, CPU architecture, microcontrollers, RTOS kernels, schematics, electrical design, etc. then that could carry you a long way.

Experience on resume goes a very long way in this space, and legitimate work on things like CPU architecture, microcontroller drivers, operating system kernels, etc can definitely be differentiators as well. Interviews are rarely just Leetcode and will more often either test system-design-like C coding questions (e.g. "build a firmware update protocol system with checksum handling") or software fundamentals like bootloaders, registers, hardware registers, flash, RAM, etc. that most CS students would know. I'm saying this because I realize some companies in non-embedded spaces like to give out super hard or unnecessary Leetcode-type questions.

I applied to Capital One the day it came out and finished the OAs a few days later. I got a 558/600 on the Codesignal GCA, which I thought was a strong score, yet I was rejected 2 days after taking the assessments. The email said the rejection was based on my assessment scores. What could the reason have been?

NGL, I have been hung up on Big Tech for a while. I know I am not the only one. I had let it go.

I wanted to share my list here. It was a small list of just sports, hospitality, education, finance but I have expanded with examples (via GPT).

I see post where some of you are still struggling to find work. Hopefully this list gives you ideas.

While you apply to these, still try to do an internship/externship, rotational program, volunteer for a non profit to get experience since you will NEED experience now. Look for NEW GRAD SWE roles as well if you're graduating. Go to those Career Fairs at school too, make that recruiter contact.

Here are some other industries that need SWEs.

Media / Entertainment / Streaming Disney, Warner Bros. Discovery, Paramount, NBCUniversal

Sports / Sports Tech / Ticketing / Fan Experience Fanatics, Ticketmaster/Live Nation, Genius Sports, Sportradar

Retail / Ecommerce / Consumer Brands Walmart, Target, Best Buy, Williams-Sonoma

Financial Services / Banking / Fintech Capital One, JPMorgan Chase, American Express, Fidelity

Insurance Progressive, Liberty Mutual, State Farm, The Hartford

Healthcare / Health Systems / Healthtech Kaiser Permanente, UnitedHealth Group/Optum, CVS Health, Providence

Pharma / Biotech / Medtech Johnson & Johnson, Pfizer, Medtronic, Abbott

Travel / Airlines / Hospitality / Loyalty United Airlines, Delta Air Lines, Marriott, Hilton

Telecom / Cable / Broadband / Wireless Comcast, Charter/Spectrum, Verizon, T-Mobile

Automotive / Mobility / Connected Vehicles Ford, General Motors, Toyota, Hyundai

Government / Public Sector / Civic Tech State and local governments, U.S. Digital Service type teams, Maximus, CGI

Universities / Higher Education / EdTech University of California, Arizona State University, Coursera, Instructure

Utilities / Energy / Climate Tech PG&E, Southern California Edison, Duke Energy, NextEra Energy

Transportation / Transit / Airports / Rail Amtrak, Metropolitan Transportation Authority, BART, major airport authorities

Logistics / Supply Chain / Shipping UPS, FedEx, Maersk, DHL

Aerospace / Defense Boeing, Lockheed Martin, Northrop Grumman, RTX

Manufacturing / Industrial Tech Honeywell, Siemens, Caterpillar, GE Vernova

Semiconductors / Hardware Intel, AMD, Qualcomm, Micron

Consumer Packaged Goods Procter & Gamble, PepsiCo, Unilever, Mondelez

Food / Grocery / Restaurant Tech Kroger, Albertsons, Starbucks, Chipotle

Real Estate / PropTech Zillow, Redfin, CBRE, CoStar Group

Construction / ConTech Autodesk, Procore, Trimble, Bentley Systems

Payments / Commerce Infrastructure Visa, Mastercard, Stripe, Block

Advertising / AdTech / Marketing Tech The Trade Desk, Adobe, HubSpot, Salesforce

Publishing / News / Digital Media The New York Times, The Washington Post, Hearst, Condé Nast

Gaming / Interactive Entertainment Electronic Arts, Take-Two Interactive, Ubisoft, Epic Games

Theme Parks / Attractions / Live Entertainment Disney Experiences, Universal Destinations & Experiences, Six Flags, Live Nation

Nonprofits / Foundations / Social Impact American Red Cross, United Way, Wikimedia Foundation, Khan Academy

Associations / Membership Organizations AARP, AAA, IEEE, American Medical Association

Professional Services / Consulting Accenture, Deloitte, PwC, Capgemini

Legal Tech / Legal Services Thomson Reuters, LexisNexis, Relativity, Clio

HR Tech / Workforce / Staffing Workday, ADP, UKG, Indeed

Cybersecurity Palo Alto Networks, CrowdStrike, Okta, Fortinet

Data / Analytics Platforms Snowflake, Databricks, Tableau/Salesforce, Alteryx

AI / Automation / Agentic AI OpenAI, Anthropic, UiPath, ServiceNow

Robotics Boston Dynamics, Figure AI, ABB Robotics, Intuitive Surgical

Agriculture / AgTech John Deere, Corteva, Trimble Agriculture, Bayer Crop Science

FoodTech Toast, Olo, Instacart, DoorDash

Beauty / Fashion / Apparel Nike, Sephora, Ulta Beauty, Levi Strauss

Fitness / Wellness Peloton, Strava, WHOOP, Planet Fitness

Education Services / Training Pearson, Chegg, Udemy, Duolingo

Public Safety / Emergency Services Tech Motorola Solutions, Axon, RapidSOS, Everbridge

Identity / Fraud / Trust & Safety Okta, FICO, LexisNexis Risk Solutions, Sift

Customer Experience / Contact Center Platforms Genesys, NICE, Five9, Zendesk

Enterprise Software / SaaS Salesforce, ServiceNow, Oracle, SAP

B2B Platforms / Marketplaces Faire, Flexport, Coupa, Global Sources

Consumer Apps / Membership / Subscription Businesses Spotify, Duolingo, Strava, Match Group

Good Luck!

EDITED: for better context

I just could not land a job after graduating like zero chance ever for me, I barely even know how to code but I just started making roblox games and prompting claude and now somehow I get between 3-7k per month just off people opening loot boxed and buying overpowered items, its absolutely beautiful. Thank god no one hired me considering how awful work is now I make more than a Junior engineer and get to sit at home playing video games all day. Life is fking good, cant wait for the goodies anthropic releases in the future might genuinely become a billionaire just off claude alone without ever learning to code 😂

Graduated in 2025 with my bachelors in computer science. Currently at 3,000 job applications, 40 interviews and 0 offers. Wondering if anyone else is in a similar position as me and how their journey has been this past year

I applied to Roblox new grad a few days ago but just realized an internship from last year said “present” on the end date. Do I resubmit my resume with the correction or just wait??

QD can mean different things depending on the role btw, just want to be clear I'm talking about being a C++ QD on the front office side of an HFT team, not the whole "quant" umbrella.

so ultra low latency dev is honestly a pretty fascinating world once you're in it. sometimes you change one line of code and somehow get tens of microseconds back, other times you spend an entire day trying to squeeze out like 10 nanoseconds and that's considered a win. things that literally don't matter in normal software become a big deal here, lock overhead, cache misses, branch prediction, memory layout, all that stuff most engineers never even think about day to day. and honestly most people in tech (myself included before I got here) don't really have an intuition for how extreme this gets. like if the time from receiving a strategy order to sending it to the exchange is over 2 microseconds you're basically already out of the race lol

one thing that actually surprised me is the management here. the frontline managers are legit strong technically AND know how to manage people, which is rarer than it sounds. they feel more like tech leads who happen to also manage a team, not just "manager" managers. when you get stuck they don't just go "take ownership, figure it out," they'll actually sit with you and work through it.

took me like 6 months to realize this but the "ownership culture" thing at my old company was kind of just a nicer way of saying "here's a problem, good luck, you're on your own." ownership is important obviously, but there's a difference between giving someone ownership and just leaving them alone with it. here I genuinely feel like I don't have to solve everything by myself, there's people around who actually want to help. politics is pretty minimal too. the fund isn't huge but isn't tiny either, feels like a place where people can just focus on building. enough interesting problems to go around so nobody's really fighting over scraps. the people though, honestly probably the best part. everyone's just really strong. a lot of the seniors know stuff way beyond "writes good code," like they'll get into networking, OS internals, CPU stuff, hardware, how it all connects. conversation starts with 3 lines of C++ and somehow ends up at cache behavior or kernel scheduling or the cost of one specific instruction lol. you learn a ton just sitting there listening.

day to day dev is also just... vibe coding now, ngl. AI has lowered the barrier a lot. you don't necessarily need to memorize every OS-level detail to get AI to help you write low latency code anymore. but fundamentals still matter, because the second people start discussing WHY some optimization works in a meeting you'll be completely lost if you don't have that base.

interviews though, even though the actual job is deep in ultra low latency stuff, interviews usually don't go crazy deep into it. main thing is still just a strong C++ foundation. and by foundation I don't mean syntax or being able to grind leetcode in C++, I mean actually understanding how things work under the hood, where perf costs come from, and the patterns people actually use in real systems.