i was supposed to start tomorrow but i made a slightly unprofessional joke and since they're a startup they said something about building the future of it and rescinding my offer. i'm so dumb. completely my fault. i always forget that the people i'm talking to are my bosses, not my friends. they are never my friends.

I'm waiting on an interview, and I tried practicing the graph questions for google on leetcode, and all of them are near impossible for me to solve! Are they typically this difficult in interviews? They often involve multiple data structures and algorithms like Dijkstra's and binary search in a single question. What the heck?!?

What about for DP and Trees?

Hi I am in a bit of a pickle. I have done 2 pretty good internships but was getting no callbacks so as a experiment just for fun - I decided to fake an experience to see if I'd get more callbacks. The faked experience was at a company less than or equal to the name brand of the two prior internships I just spoke of. That being one way or another I got more interviews. Whether it was because of the experience or because I left it on my resume when I was applying to many places - it's hard to say however I may end up getting a few offers and I'm afraid it won't pass BG check. What should I do in this situation?

So I'm now entering year 2 as a CIS(CS coded curriculum), Imo, I feel on the right track with what I'm doing, so far in this year:-

Took robotics and IOT workshops

Semi built a health fullstack app(onhold cuz of the CCNA)

Now planning on entering network engineering for healthcare via CCNA

Solid gpa of 3.75

It may be redundant, but I'm willing to work more for a honestly fun degree like mine(which has a heavy HIT lean in it)

which pipelines does it open up?

is it considered a decent name internship and could it pivot me to even stronger names?

Also will this help someone get looked at by companies with more of a (oh yea, no doubt, we shouldn’t even think about not hiring this guy..). If I showed that I was a roblox dev in my resume would that give me some sort of advantage? How would recruiters see me?

NEED answers, appreciate yall!

Hi all,

I'm a second year com-sci student in Quebec cegep and I'm looking for opinions on a Com-Sci degree with good co-op programs in Canada.

My Main requirements are:

• Solid co-op program with 70%+ placement rates
• possible connection with Big or local tech hubs
• Reasonable or friendly pathways for CEGEP
• Not to competitive or heavy course load

I'm not considering Waterloo and U of T because they are extremely competitive. I am considering BA in Computer Science from University of British Columbia.

I wanna know:

1. How is your school's co-op placements and opportunities?
2. How is your work opportunities after grad?
3. Was transferring smooth, or did you lose a lot of credits?
4. Which school would you choose if your goal is getting solid co-op?
5. How insane is the workload actually and is it very competitive?

torn between the two options. which one is overall better the better choice? the salary is pretty much the same but obv boston is more expensive. whoop also gives ISOs on top of the salary though… but from an overall standpoint where would you guys think is the best option?? any input would help/things to consider

The MSR undergrad internship is supposed to be due at 5 pm ET on Monday Oct 5. However, the application closed right at 12 am Oct 5??? Does anyone have the same issue/ know who to contact

I’m currently in high school and trying to decide what I want to study at university. My parents are pushing me towards Computer Science, mainly because they believe it has good career prospects and that I could eventually go into cybersecurity. The problem is that I’m honestly not that interested in coding. I don’t completely hate it, but I’m not someone who enjoys programming, spending hours on GitHub, or building software.

What makes me even more confused is the current AI situation. AI is becoming increasingly capable of writing code and automating parts of software development, while at the same time I keep seeing people saying that CS graduates are struggling to find jobs. So I’m wondering whether CS is still a good and safe degree to choose if I’m already not particularly interested in coding. I don’t want to spend 4 years studying something mainly because my parents consider it a “safe” career, only to find out that the job market has changed.

My parents say I should do CS and then specialize in cybersecurity, but I’m not sure how realistic that is. From what I understand, cybersecurity still requires a strong CS/IT foundation and can involve quite a lot of technical work. I’m also wondering whether cybersecurity is actually more resistant to AI automation or whether it will face similar problems.

So, is CS still worth doing in 2026 if you’re not particularly interested in coding? Is the job market really becoming that difficult, and would you personally recommend CS for someone in my situation? I’m not completely against CS, I’m just genuinely unsure whether it makes sense for me.

Thanks.

AI Engineering Topics Covered
Foundation Models
Model as a Service (MaaS)
Scaling Laws
Self-Supervised Learning
Tokenization & Byte Pair Encoding (BPE)
Masked Language Models
Auto-Regressive Language Models
Multimodal Large Language Models
Embeddings
Prompt Engineering
Retrieval-Augmented Generation (RAG)
Fine-Tuning
AI Application Planning (Use Case Evaluation & Metrics)
The AI Engineering Stack (Application Development, Model Development, and Infrastructure)
Foundation Model Training Pipeline
Training Data
Modeling
Post-Training
Sampling
LLM Evaluation
Challenges in Evaluating Foundation Models
Language Modeling Metrics
Exact Evaluation Methodologies
AI as a Judge
Ranking Models with Comparative Evaluation
Evaluation Pipelines
Evaluation Criteria
Model Selection
Designing Evaluation Pipelines
Prompt Engineering
Introductory Prompt Engineering Concepts
In-Context Learning
System Prompts vs. User Prompts
Context Length and Context Efficiency
Prompt Engineering Best Practices
Prompt Engineering Tools
Organizing and Versioning Prompts
Defensive Prompt Engineering Strategies
Prompt Extraction, Jailbreaking, and Injection Attacks
Defenses Against Prompt Attacks (Model, Prompt, and System Levels)
Total Coverage: Foundation Models → Training → Post-Training → Evaluation → Prompt Engineering → RAG → Fine-Tuning → AI Application Development → AI Infrastructure.

Anyone completed software developer oa from hackerrank on campus college placements

Offline oa

Role software developer

It's behind paywall: 2027 Best Undergraduate Computer Science Programs Rankings - US News Rankings. Please don’t comment asking for your college’s rank if it’s not listed here. I also decided to include LACs because there seems to be a lot of demand for them here. Ultimately, keep doing projects, coursework, internships and grind leetcode.

has anyone heard back after taking the visa OA for swe intern 1? i completed 2/3 problems but had a good amount of reasoned code for the third. lmk!

I never learned proper time management and now it’s hitting me like a truck. How does one manage to achieve all of this at once:
- prep for interviews
- do homework and study for tests
- get good sleep
- having fun and hanging out with friends

While everyone else around me is going out every weekend, I’m stuck in my room all day grinding leetcode. I feel so miserable and left out.

Like when I finally finish all my school work and want to take a moment and relax, I feel guilty because I have an upcoming interview I should be preparing for instead. Whenever my friends ask me to hang out, I usually have to turn them down because I literally can’t go out without feeling guilty or missing a deadline. It’s just so exhausting and it feels like this cycle will never end. I genuinely don’t think I’m built for this major…

Please I need some hope I’m literally about to lose it all

does anyone know how many steps do these interviews happen, if there are more technical rounds after the coding assessment or just behavioural, it’s not my targeted field but i was just applying to anything and everything. not sure how to prep 😭

Hi all! I have the first of two technical rounds coming up next week for Waymo's 2027 Summer Intern, BS/MS, Pipeline and Test Health Engineer role on the Systems Engineering team. The role is about keeping release-critical simulation tests healthy, debugging failures and building alerting/automation. The interview lists C++, Python and/or SQL as languages.

Has anyone interviewed for this role, or another Waymo Systems Engineering or simulation intern role, recently? I'm not looking for exact questions, just a sense of the format:

- Were the coding questions LeetCode-style, or more like debugging/extending existing code?

- Was there a SQL portion, and if so, which dialect (BigQuery, Postgres, etc.)?

- Did they ask about SRE topics like SLOs, alerting or flaky tests?

- Any troubleshooting or "how would you test X" questions?

- Could you run your code, or was it a plain shared doc?

- Anything you wish you had prepped more?

For context, I'm a CS undergrad with internships in data engineering (Airflow/ETL) and robotics. I'm comfortable in Python and C, and brushing up on C++.

Any tips appreciated, and I'm happy to share how it went afterward. Thanks!

Hey all, I have my final round for Figma's Data Science Intern role this Thursday, and I'd love to hear from anyone who's been through it or a similar DS intern loop.

Background: CS undergrad, past the online assessment. The final round is three interviews back to back:

- Intern All-Around (45 min)

- Stats & Experimentation (45 min)

- Analysis (60 min)

What I've heard so far: the Analysis round is one case in several parts that build on each other, Stats is more of a conversation than a quiz, and the All-Around may be mostly behavioral. That's from one MS student's loop, though, so I'm not sure how it carries over to undergrads.

Questions:

1. What kind of case did you get in Analysis (metric drop, feature launch, sizing)? Did you write any SQL or pandas live, or was it all discussion?

2. How deep did Stats & Experimentation go? Mostly A/B fundamentals (p-values, power, sample ratio mismatch), or further into network effects and causal inference without an experiment?

3. Was the All-Around purely behavioral, or were there product or technical questions too?

4. Anything that surprised you, or that you wish you'd prepared?

5. Any advice specific to undergrads compared with MS or PhD candidates?

What I've been prepping: A/B test design and pitfalls, metric investigations, sizing, Postgres SQL and pandas, and STAR stories from my projects.

Thanks in advance, and I'll post how it went afterward to pay it forward.

What are the best ways to prep for a c1 powerday (business analyst intern) apart from doing the sample cases they provide?

Did anyone get the CodeSignal OA for Robinhood APM? Or has anyone done it before? If so, could you please share what it was like and how you prepared for it?