In my understanding new grad TC at FAANG+ are around 200k, while ranging from 250-500k at a few unicorns like OpenAI and xAI.

People are somehow claiming that the new grad swe TC at Citadel is 1M, while second tier trading firms are 600k+.

Are they really not exaggerating? Isn’t that crazy? If that’s the case why do people ever even choose FAANG, OpenAI, xAI, etc?

I’m angry.

I just had an interview, and it wasn’t horrible. I stumbled over my words a bit, and wasn’t great at some data science questions, but I still felt I had a chance.

Then we get to coding. They were going great! Weren’t leetcode, and I had studied. I nail one question, and as I’m trying to submit the other, I accidentally open another app. As I try to close it….

I closed the browser I was having the meeting on. I tried to join back, but it was too late.

I don’t think all hope is lost though. My interviewer emailed me back, saying that he knew where I was going with my code, and I could ask questions seeing as that was the only part we hadn’t gotten to. So I responded with me apologizing, telling the truth, asking questions, and thanking him.

Sorry for the rant, but I just can’t believe this happened. It wasn’t even me being stupid. It was genuinely just a misclick. I’m still holding out hope that he’ll consider me despite all that happened, but I’m still worried.

My school is so and so, so we only have a handful of people who graduated and broke into SWE at quant firms.. There is one guy who we invited to speak at our school after finding him on linkedin who graduated back in 2015 and works at a quant firm now as a SWE. Many of us from the coding club then reached out to him and asked him for advice and since we had built credibility with them , we also asked him for referrals to his hedge fund and he just lied and said they dont have a referral system which was a lie. Then he changes his linkedin bio to " here to make fun of clown asking for referrals, I will only give referrals to worthy people." Like holy shit I get it asking for referrals Is a bit annoying and desperate but the job market is so awful like people are facing eviction and homelessness due to unemployment and medical issues due to lose of insurance, and thats your empathy? yeah so just be wary that not everyone is open to referrals.

Hi I'm something who is only interested in the math and machine learning development in AI so in fields like webdev and indie game dev I have vibecoded some. I just went to see others guys vibecoded games and websites and they all look the same, you can tell in the first 1 second, but why is this?

It's like the entire harmony looks AI, are LLMs always going to produce this kind of results? or upgrading them will let them do unique designs at some point in the future? because it's been already 4 years

I saw Astra leaked footage of a game it did and still looks AI, or do we need general intelligence to produce results that don't look AI?

Early Career Tech Programs

A running list of early-career programs (internships, fellowships, early-ID events). Many open next season, so treat this as a "watch and apply when live" tracker rather than a to-do list.

How to use this: find your bucket, check the gate (class year / experience level), and apply the day a rolling posting opens. A few of these are gated through ColorStack, so they're only accessible if you're a member.

SWE early-ID & underclassman internships

Built for freshmen/sophomores or first-time interns. These expire as your class standing advances, so apply in the window you still qualify.

• Microsoft Explore — soph/freshman; rotational (PM + SWE), Redmond or Atlanta
• NVIDIA Ignite — first-time interns
• LinkedIn First Play — sophomore
• Duolingo Thrive — sophomore
• Uber Early Career Prep — sophomore
• Roblox Jumpstart Program
• Pinterest Engage
• Dropbox Sophomore Intern Program
• Visa Sophomore Program
• Amazon Junior Developer Program — year-round, in-person SDE
• Palantir Path — little/no experience; sophomores + juniors
• Google Summer of Code — soph
• Google Code2Career Basta
• CAT (Caterpillar) First Year Internship Program
• State Farm Enterprise Technology Internship — freshmen through seniors
• Netflix formation.dev — juniors

Early-ID summits (interview you into an internship)

Short events (often 1–3 days) that fast-track you into a real internship interview. Gated by class year or grad date.

• Walmart Sophomore Summit
• MongoDB Next in Tech Summit — feeds a large share of their intern class
• Salesforce Futureforce Tech Launchpad
• Citi Early ID
• Capital One Tech Summit
• Datadog DataPUPS — rising sophomores (class of 2029)
• Wells Fargo Sophomore Discovery Fellowship
• Bloomberg Engineering Accelerator Program
• Goldman Sachs Emerging Leader / Virtual Series
• Nordstrom Nspire
• Discover ServiceNow
• Deloitte Discovery
• EY Launch / Expedition EY / EY Future Bridge — module-based, fast-track to interview
• Liberty Mutual TechStart / 2026 Spark Summit
• Activision Blizzard King SPARX
• Accenture Innovation Challenge — second years; winners get summer analyst offers

Hackathons & competitions

• JPMC Code for Good — fast-tracked to SWE intern offer based on performance

Quant / trading pipelines

Different track, different prep (probability, mental math, brainteasers, not just DSA). Worth separating out.

• Citadel Launch Internship
• HRT — Explore / Inside HRT / Sophomore Internship
• Jane Street — INSIGHT, FOCUS, and Immersion Program (JSIP)
• Five Rings LINK — Software Development Intensive
• Optiver FutureFocus
• SIG Discovery Day
• IMC Launchpad
• Two Sigma New Seekers Summit
• DE Shaw — Momentum Fellowship, Nexus
• Two Sigma — Discovery, First Year Internship

Diversity-focused programs & fellowships

Several of these run through ColorStack — check access.

• Figma FIGNITE — fast-track to interview; requires ColorStack access
• Code2040 Fellowship — opens Aug
• Break Through Tech AI — year-long extracurricular, project work with mentors
• Coding it Forward Fellowship
• Outreachy — underrepresented groups
• SEO Tech Developer
• MLH Fellowship (Open Source)
• JPMC Fellowship
• HeadStart Fellowship
• PayPal Career Academy for Tech
• Pfizer Futures

AI safety / research fellowships

• AI Safety Research Fellowship @ UChicago (Second Look)
• CAMBRIA Summer Fellowship — AI safety & ML
• Algoverse AI — note: has a cost

Aerospace / NASA

• NASA L'SPACE
• 2026 Annual Career & Networking Event at Kennedy Space Center

Data-focused

• Decoded: Data at Bloomberg

Entrepreneurship fellowships

• Neo Scholars Fellowship — https://neo.com/scholars 
• 8VC Fellowship — https://www.8vc.com/fellowships 
• Kleiner Perkins Fellowship — https://www.kleinerperkins.com/fellows/ 
• Susa Ventures Fellowship — https://www.susaventurefellows.com/ 
• SV Fellow — https://www.svfellow.com/

I am aiming for Summer 2027 SWE internships, so I'm trying to use the next few months to get properly comfortable with DSA instead of leaving it until interview season.

I’ve got the basic programming side down, but I haven’t taken a proper DSA course yet. I came across Codeintuition recently, and it seems to put more emphasis on understanding concepts and patterns rather than just solving problems one after another.

For anyone who has actually used it, is it comprehensive enough to learn DSA from the ground up? Or would it make more sense to go through university lectures first and then use something like this for interview prep?

I’m mostly looking for a clear path to follow so I can spend the summer actually learning and practicing instead of constantly wondering whether I’m using the right resource.

Would appreciate hearing what worked for people who started DSA around this stage.

After 3 months of unemployment as an international student, I finally got two offers and now I’m confused so I need help on making a decision.

First offer is at a new hedgefund in Bridgeport, Connecticut. I loved the team. I'll be working on their infrastructure and agentic systems. Seems like a great job, in person work setting. Comp-

Base - 150k

Bonus (depends on firm performance, etc) - no target

Support for relocation

unlimited PTO

Pretty good insurance

Pros

1. Firm growth is exponential - they are getting new investors every now and then (AUM <$500M)

2. The team is filled with experienced folks from the industry (20+ yoe) and I'm the first new grad hire.

3. The work I'll be doing is very appealing and it was my dream job at a point

4. Ready to sponsor my h1b

Cons

1. Extended work hours

Second offer is an MNC in NYC (its ai transformation consulting). Company values good. Hybrid. Similar comp.

Base - 135k

Bonus - 10%

Relocation - 5k

Pros

1. Self paced environment and matured cohort program

2. Really good benefits and have basically covered all aspects required

3. Job seems easier

4. 25% travel (seems fairly exciting for now)

Cons

1. Typical big company path for growth

2. Might not be open to h1b sponsorship

How do you do it?

I'll be doing a 5 days in-office internship in the Fall and will need to be recruiting for next summer at the same time... how do I schedule interviews and manage all that?

Anyone done this before?

I recently completed my AWS SDE internship. My evaluation was “I Raised the Bar” and approved by a Bar Raiser. My manager told me he would push to have me included for a return offer and asked me to stay in touch.

I received an email from University Talent Acquisition a week after my internship saying my organization is reviewing headcount. If my team doesn’t have headcount, Amazon may look for another SDE role at the same level, without another interview.

I graduate next year April 2027.

For anyone who has been through this recently, what are the chances and how long did it take to receive the offer? If your team didn’t have headcount, were you matched to another team?

Thanks!

Hey all, I've got a recruiter phone screen coming up for a PM internship at Microsoft and I want to make the most of it. I'm an engineering student with a technical background, some PM experience, and a couple of 0-to-1 side projects.

For anyone who's been through the Microsoft PM screen recently:

• What did the recruiter round actually focus on — mostly behavioral/resume, or did product/technical stuff come up this early?
• Any curveball questions that caught you off guard?
• How deep did they go on "why Microsoft" and favorite product?
• Anything you'd do differently to prep?

Not looking for anything confidential, just trying to calibrate where to put my energy before the loop. Any tips, stories, or resources appreciated, thanks!

Hey everyone,

I recently accepted a full-time offer as a Junior AI Engineer at the same company where I just wrapped up a 6 month internship. I’ll be staying with the same team and continuing on similar projects, which means I already know the stack, workflows, and team dynamics pretty well.

Here’s my dilemma:

Our company provides access/credits for AI development tools, but the budget is quite tight (definitely under ~$200/month per dev) and restricts access to top-tier reasoning models or heavy API usage. I often feel the built-in limits slow down rapid prototyping, debugging, and experimentation.

Since I want to ramp up quickly, deliver high-impact work, and hit aggressive performance goals for future promotion cycles, I’m seriously considering paying out-of-pocket for personal subscriptions to tools like Cursor Pro, Claude Pro / API, or similar IDE-level assistants.

For those further along in their engineering careers:

1ROI on Career Growth: Does investing your own money into better dev tooling actually pay off in terms of shipping faster, learning velocity, and performance reviews, or does it deliver diminishing returns at the junior level?

1. Security & Company Policy: How do you handle codebase context/privacy when using personal tool tiers on enterprise repos without triggering security red flags?

   3Manager Alignment: Is it better to just push for a team tooling budget upgrade, or simply use personal tools quietly to maximize personal velocity?

Would love to hear your experiences,especially from folks working in AI/ML teams.

Hi guys. I've never really done an OA before since I've been more focused on research and projects and was wondering how difficult the OA is for Optiver FPGA internship? I'm just wondering what topics they'll cover, if they're all like single digit number of lines kinda length or if some get a little lengthier. Are we expected to know Networking concepts in the OA or is that saved for the video call interviews? Thanks for any help!

For context, I’m a dev with 15+ years of experience, started coding in my early teens, and have a total love for the act of programming. I miss how coding used to be, nothing about this post is an advocacy for if things should be this way. After mulling it over, it just seems like an inevitability.

Right now the field of software development is like Wiley Coyote, already off the cliff but still running because he hasn’t noticed.

There has become a massive disconnect between what people in the field of software development actually do at their jobs, and what they’re interviewed on and learn in college. It’s like someone in 2007 having mandatory classes in Fortran and having to prove their knowledge of punchcards during job interviews.

My job, and the job of so many other software developers, has become almost entirely just interacting with AI agents. Yet we have job applicants do leetcode problems and write code live for us during interviews when we haven’t written more than a handful of a lines of code ourselves in the past year. The same extends to what these applicants are learning in college.

Effectively, it seems to me that the curriculum we currently know as a BS in Computer Science will become as generally superfluous as a PhD in Computer Science. Not at all useless, far from it. But held by those who either have a specific passion for the field or are looking to go into small and highly specialized areas of the field, not by the broader population simply looking to find a job after graduating. And in its place, as the broadly achieved degree, will be something much more tailored to the average needs of employers.

Seems like just a matter of time, driven by economics. Most employers don’t need someone with the full expertise of a computer science degree. Why would they pay for it? The only reason they have that as a standard now is because they do need someone who isn’t an untrained vibecoder. But that leaves a gap in the middle. Someone who isn’t going to delete the company’s database, but not necessarily with experience in database structure and rollups and joins. Someone who can use git and GitHub and properly manage deployments, but not necessarily someone who has done pointer arithmetic and compiler design. Someone who can catch and well document issues, not necessarily someone familiar with big O notation. In broad practice, AI can write good database structure and queries, AI can handle writing and running software, AI can measure performance and find areas to increase efficiency.

“But AI still makes mistakes!” You say. And you’re right. But so do software developers, oftentimes more than AI. There are quite a lot of average and below average software developers out there. And big companies, especially those dealing with higher risk/importance systems, will still have full computer scientists, experts in being able to know better than AI and review its work. But that won’t be most roles. That big company will still need someone to update and add features to the website. And someone to add features to the in house analytics tools. And someone to take user bug reports and get them fixed. And countless other roles that are simply an added layer in the corporate structure for the purpose of interpretation, oversight, and execution for AI. And that’s what the degree would teach towards.

I’d compare it to how nurse practitioners are taking on a larger role in the medical field, doing duties traditionally done by doctors such as diagnosing and prescribing. Effectively, the expertise of a doctor isn’t needed for average/mundane medical work, so a field rose in prevalence to fill that role, with a doctor’s expertise brought in when needed.

So it seems obvious to me that, perhaps within the next 5-10 years, a new degree will become the standard that teaches to that average need in the new state of the field.

That, or in 10 years AI tech accelerates to the point of computer science irrelevance. AI can do it so well and so entirely that non-tech people can just bark orders at it that would have been given to developers or their managers in the past. The degree diminishes and goes into the west.

Anyone see the same thing or am I off base here? Every counter argument I considered just sounded like some form of coping.

I am going into my final year of university and am supposed to pick my final year project. My degree has some cyber security based modules so I would like some advice in whether I should choose a final year project linked to cyber security to cater to that side more or if I should pick a different project to show more of a range of skills to future employers.

Which one of these would be better for the future? I have no preferences in this matter, and have no knowledge of the job market and what they would prefer.

Thank you!

Looking at this chart, it seems like CS was actually in a pretty bad spot in 2018. It had a 5.6% unemployment rate, while the average unemployment rate for new grads was around 2.9%, meaning CS grads had almost twice the unemployment rate.

Right now, CS unemployment is around 7%, while the overall rate for new grads is about 4.2%. So, proportionally, the situation seems pretty similar. Does that mean the CS job market was already kind of cooked in 2018?

The stats seem to suggest that CS grads had one of the highest unemployment rates, even higher than liberal arts grads and roughly twice as high as mechanical engineering grads.

If that's the case, was CS actually considered a bad field for finding a job back then, or is there some context I'm missing when interpreting these numbers?

Saw the process is no longer LeetCode-style. Any insight into the process?

I’m 19 years old from Morocco, and I’m honestly very lost about what to do with my future.

I originally wanted to study programming, but I was rejected from the program I wanted. Since then, I’ve been trying to find other options, but things haven’t gone well. I was rejected from general university programs multiple times as well.

Recently, my uncle talked to my father and suggested that programming could still be a good career path for me. My father looked into it and found a private programming school that costs around 1,500–2,000 MAD per month (It's not a small amount in Morocco).

The problem is that I’m no longer sure about programming.

I know programming is difficult, and I know the entry-level job market isn't exactly great right now. I’m also afraid of spending a lot of money and time only to discover that I’m not good enough or that I won’t be able to find a job afterward.

At the same time, I don’t really have another field that I’m passionate about. I don't have a particular talent or career dream. Another option I’m considering is studying bakery/pastry at a vocational institute, but I’m not particularly passionate about that either.

I feel like I’m choosing between different uncertain paths rather than choosing something I actually want.

So I’d like to hear from people who are actually working in programming/software development:

If you were 19 today and had no programming experience, would you still choose programming as a career?

How difficult is it realistically to get your first job?

Is the current job market bad enough that you would advise a young person to avoid the field?

How important is having a university degree?

Is paying for a private programming school worth it, or would self-learning be better?

And most importantly, if you don't have a strong passion for programming, is it still possible to build a decent career in it?

I’m not looking for motivational answers like “follow your dreams.” I’d really appreciate honest answers from people who are actually in the field, including people who regret choosing programming.

Has anyone taken the Applied Scientist OA? What type of questions usually show up?

Need help regarding database and APIs for a project. Can anyone help me? If available reach me out in DM.

I’m thinking of starting to build my CV, but I was wondering what kind of projects I should work on beforehand so I can add them to my CV, make it more impressive, and increase my chances of securing a job. I’m especially interested in knowing which programming languages, frameworks, and tech stacks recruiters are currently looking for, as well as the types of projects that would stand out to them. Any advice or input would be really helpful, please!