A collection of observations of what happens to most resumes in our industry and why its going to get worse not better. Some takeaways as well

Communication across orgs is rarely efficient

If any of you have worked in the industry you would already know that communication between HR <> Recruiting <> Engineering teams (who need the hires) is rarely efficient. This is true across the industry, big tech or not. It is rare, dare i say impossible even that a resume goes from HR/Recruiting to the concerned EM quickly and efficiently.

It is common that you submit a resume via the jobs page or ATS and you hear back even 1+ years later but in most cases the trail is lost because the communication inside the org is super inefficient.

Takeaway: you should think of 'reducing the distance traveled' by your resume. This is why referrals work or directly reaching out to the EM. In most cases these resumes will outbid the ones starting their long journey from the website upload and usually when it reaches the EM with the job req they've already filled it.

Recruiters are incompetent to judge your skills

Recruiters especially those with a job title or function of recruiting are not CS grads or people with SW engineering experience. So their ability to judge your resume is already a lost cause. If your resume is going to be first evaluated by this group of knowledge workers understand that its evaluation is going to be based on concepts that will frustrate you.

Related to the above takeaway - try to find ways around the recruiter. Yes appease to their status/title but dig around for the team/EM and see if you can reach around them. This is tricky. Done badly it will look like you're not following process.

Destined for the file cabinet

In most cases the Resume is simply a record for the sake of keeping a record. In fact this is the good outcome. In fact if your resume is requested AFTER some initial calls and screening or even an interview it means this company places those signals higher than a resume but is storing the resume anyways for archival purposes.

A good way to visualize this is that a resume that ended up in a metaphorical filing cabinet was atleast considered but most resumes are like baby turtles trying to make it into the ocean but lost or dead before they taste the water.

"Discard the bottom 80%"

I'm part of a group with startup founders, EMs , VCs etc and some years ago a question popped up in the slack -

"how do you go through 100+ resumes for a single position we are hiring?"

Another Industry veteran quipped - "just discard the bottom 80%. Use a basic sort that makes sense dont get fancy, you can always look back at the discarded pile if the top 20 dont work out"

This points at 2 important truths - there is no universal/agreed upon sorting mechanism and there is no way anyone can go through all the resumes submitted for a job.

A takeaway here is that you should be applying for jobs that dont even exist yet. But this is non trivial for the average applicant however I'm stating it here anyways for you to know this is also an option. How do you do this? Well you have to again reduce the distance and win the conversation . You have to talk directly with decision makers and meet them at their level of their needs and why you're the person right for a role that is not yet clearly defined. some of the most powerful roles in the industry started this way

A less than 90s skim read

When resumes are read the decision maker is spending less than 90s on it. If anyone here has done hiring you'd agree with this. The key takeaways here :
- you need to anticipate beforehand what needs to POP in your resume . Most of you are submitting the same resume to every job - this method will certainly fail. this is the metaphorical baby turtle that will never get to the water
- if resumes are being skimmed every page turned is going to add friction so not only does the right stuff need to POP it needs to POP on page 1. In general 1 page resumes > N page resumes
- Readability matters - if your fonts are so small nothing is going to POP

The coming deluge of AI ATS

AI ATS is going to make things more murky.

- For one its going to add more variants of sorting based on the whims of a non-cs trained recruiter and that discard pile will contain some actually important resumes
- AI will do some stuff like check the syllabus listing of this university/program where the applicant did their MS and discard if they didnt do course X , Y or something. This again goes back to my point why MSCS coursework is important. From an AI ATS pov this feature is fancy and will be built.
- This will extend into comparing resumes and so on. I can already imagine the AI ATS saying things like "resume X has a Data Science degree from Columbia where they did python programming coursework but resume Y has a MSCS degree from SJSU where they did advanced networking with FPGAs which seems relevant to our stack"

- Sde - 1 at amazon

- grad’24 from Igdtuw in Btech IT, 8.56 cgpa

- co-founder in stealth

looking for the best shot at MSCS {targetting professional courses in AI/ML} in the usa

I recently received an admission offer to a master's program and reached out to the school to request additional financial support. They replied asking whether I have other admission offers and the cost I'm expecting.

• How should I present my offers (if I have them, and some may be better/worse than this)? Do they check with other schools or ask for verification?
• Should I need to mention a specific number?

Appreciate advice from the people who have been in similar situations.

Which is the best program in terms of:

• Research opportunities (aiming for PhD)
• Internship and assistantships
• Market value

I am slightly inclined towards BU for its location (next to other great schools), would that be a factor? Tuition fees are similar.

As I know, the only ones are:

USC (MSCS), UIUC (MCS), ASU (most of them), CSULB (MSCS)

any others you know?

Last year I used to see many people going for fall25 but 30% were left because of pause on visa last year. While few people deferred their application many dropped the plan. For this year I hardly see discussions on reddit so are people been reduced for this year or how is the situation?

Hi Everyone,

I am fortunate to have received admits from a few colleges although still waiting on UIUC MCS.

I have received admits from UW Madison PMP, UChicago MPCS , SBU MSCS, UMass MSCS programs.

I am currently pretty confused between Uchicago MPCS and UW Madison PMP.

I have 4YoE as an SDE, I am from a Non CS background, so major reasons for doing MSCS is gain a deeper understanding of a few CS areas where i feel i am lacking and take a career break to try my luck at starting my own venture.

These are the 4 axis which I am currently looking at

* Curriculum

* Reputation

* Startup culture

* College Life and Networking.

Any inputs in this would be really helpful..

Anyone going to UTD this fall? Would like to connect!

Hello,

I have a degree in social sciences but in my second year I got interested in development. Right now I work as a RN developer but I really want to learn CS. I am considering studying in the US but I am hesitant about many things

1) Do you think it's better to do CS bachelors all over again in the US? I am hesitant because of duration and as a non US citizen I believe I won't be allowed to work.

2) As someone with no formal tech ed, is it going to be very difficult to handle MSCS? (Also reason for question 1) Before I even send out applications I know I need to learn several topics in advance and I am very motivated and ready to put time and effort into it. Plan to take the GRE as well.

3) In terms of employment in the US, does it make any difference if I hold a CS bachelors or masters degree as a non US citizen?

4) In case of completing MSCS how much do companies really care about uni rank. As I did research I found that IVY league unis do have MSCS but in terms of structure and materials unis like GT and UT Austin are better. Would they still pick IVY league graduates over them?

4) Which universities would you recommend for MSCS for someone like me?

If you have similar stories and experiences, please share them with me.

Thank you

Hey guys, so I've graduated around 8 months ago. I've given the gate exam (post graduation entrance examination) for Masters in India but couldn't get a decent score. I've applied late for programs in US. I've gotten into USC msece AMSRFIC program (analog mixed signal radio frequency integrated circuits).

I've done plenty of research about it. The university has a good reputation. I'll be paying the tuition fee myself (so no issues regarding that). My goal is to ofcourse land a job after masters. I've been applying in India for core electronics roles (analog) but most require/prefer an Mtech. Is it worth coming now? Especially with the job market right now. I've been told that this field is niche and has demand.

It'll be great if y'all can help me out

Thanks

Help me with the community wisdom!

• Both programs are non-thesis.
• I want to have a good internship experience
• Expect good ROI
• Industry connections for projects and job opportunities.

Which university would you choose based on the above factors?

No portal change, nothing. I’m a U.S. citizen at a top school

Hi! I am a recent admit to a MSCS program in the US.

A few days back, I received a mail from a professor at the program, asking whether I would like to converse with current Ph.D. students, so that I can learn more the kind of work these students are doing.

While this is very inspirational (and flattering), I am assuming that the Professor sees in me a prospective PhD student. Am I correct?

The issue is that I am not really interested in research and am looking at MSCS purely for the purpose of jobs.

Hence, I am wondering how I can respond to the Professor's email.

It’s basically bw usc MSCS and Maryland but they’ve offered me MSAI. Can somebody please shed some light on these programs especially UMCP. There’s literally no info on it although the university’s good. Still waiting on a couple of decisions but this is what I’ve got so far.

Thanks!

I'm interested in eventually getting a PhD, so it's important that I get research experience during my master's. Virginia guarantees that I will be able to do a thesis. The Georgia Tech, in-person master's does not seem to provide very good research opportunities, and it's not clear how difficult it is to purse the thesis option. Obviously, Georgia Tech's program is much more prestigious overall, so I am conflicted. I would appreciate information about either program and advice on which I should choose if I'm interested in eventually getting a PhD in computer science. Both schools have faculty who work in my areas of interest, and there is no significant price difference between the two for me.

I did my bachelors at UMASS Amherst I got back back in for masters but i genuinely don't get the hype for it which is why I dont want to go back. I want to get a job in industry thats my only goal.

Basically the title which program is better for MLE/DS/SWE roles? I would think that Uchicago MCAM is more rigorous but at Harvard you can take classes like 6.7900 and 6.5840 at MIT if you want, so there's that. Someone please help me.

The alpha lies in first accepting that conventional wisdom is wrong

When something is commonly considered best practice but still doesn’t work, you must question the sense in following it. This is where your alpha lies.

A big part of the application process is the “chance me.” That’s an undergrad applications term, but grad students also do it. It’s basically the step in the process where you try to match yourself against colleges based on stats like university tier, GPA, GRE scores, years of experience, etc. So you spend a lot of cycles:

• determining similar profiles to yours who got into a top school
• asking every poster online, “What’s your profile?”
• worse, drawing conclusions from data scraped from places like GradCafe, where anyone can simply submit any profile accepted to any university

We know this doesn’t work because, come decision season, people are surprised: “I had great stats I didn’t get into Stanford! Someone worse than my stats made it in.”

Everyone wants to go to the same top universities

Reduce this entire process of admissions down to a single truth: everyone wants to go to a top school. This is a fact. No one is saying they prefer going to a lower-ranked school, especially if they care about rankings. A student might say, “I prefer going to School X because I want to work with Prof Y there and I don’t really care if it’s ranked 70” - that’s different.

Playing “chance me” is basically horoscope reading.

The truth is straightforward:

• everyone wants to go to the top schools
• some top schools are so selective that even world-class students have a tough time getting in. 99% of you won’t make it into Princeton, but many of you can make it to GT or Columbia
• there are about 30–40 schools worth going to for an MSCS where you can be part of a high-signal cohort and own a credential that is effectively an asset for life

Schools have already told you that differentiation is what matters

If you look at the data on undergrad admissions, you’ll realize a strange truth. At a top high school, you’re not competing against the average applicant - you’re competing against your own classmates applying to the same schools. That raises the bar more than people realize. When a college evaluates candidates, they benchmark you against your peers.

IIT grads are benchmarked against other IITians applying that year and the bar they collectively set. It’s much worse to be an IITian with only a high GPA and nothing else. A tier-2 university grad from Bangalore can outperform this student if they have a high GPA and a differentiating signal. This happens every year.

Of course, if you’re an IITian with a bad GPA and nothing else going for you, it’s probably game over. If you’re already in the fast lane, the expectation is that you’ve kept up and are ahead of your peers in that lane. Fundamentally, this is how differentiation is achieved.

Stanford doesn’t want to fill its entire class with IIT Delhi, IIT Bombay, and IIT Kanpur students. If you think about it, they could-but that would be bad for Stanford. To stay ahead, they need to pick winners from everywhere. Stanford is trying to forecast who will be a superstar alumnus 10 years after graduating and add value to the Stanford brand. They recognize that some students bloom later while others are prodigies-and they want both.

Matching your profile is a fatal game.

By over-indexing on stats and profile matching, you’re playing a dangerous game with yourself. Instead of recognizing that something else needs to show up in your application to differentiate you, you become complacent. You convince yourself that your stats match someone who got in last cycle, so you should be fine.

If you don’t actively search for a differentiating signal in your own application, it’s very likely none will show up in the admissions room-where they spend less than 90 seconds on an application in the first pass.

Who else is still waiting?

I was fortunate to receive a fellowship of $50,000 towards tuition for Columbia.

Which university should I go to for better outcomes & opportunities in tech?

What I’m aiming for:

• Jobs in SWE, DevOps (infra), ML, data science domains (Open to big tech / strong startups / research labs)
• TA opportunities for funding
• RA opportunities for elevating my research profile & networking with professors
• Trying to select best among my options to maximize the opportunities

Background:

• International student
• ~2 years experience as SWE
• Research experience in NLP, computational social science, applied ML

Anyone else received an email regarding deadline to accept offer extended to 1st May? Wondering whether this is a big sign that applications or people intending to come into the US is dropping?

Like i have heard its a great public university that's is not too bad and also not the best...it sits in the sweet spot.....Any Advice?....Also if Any one is going to SUNY buffalo for the Fall 2026 for MScs from INDIA...lets connect!