r/developersPak

Ok so tomorrow’s my interview at ezitech software house people in pindi islamabad might know bout tbis software house. ok So plis can anyone tell me is it legit? like ive read alot of posts on reddit and they say its fake and scam on the other side there are many good reviews tooooo

im confusion
plis
ahahahah 😭😭🤧

has anyone heard back from them after giving the interview?
it feels so bad after clearing so many rounds and ending up getting ghosted by HR

Edit: Lots of people are interested in me open-sourcing this and having a public git repo so they can contribute or learn from it, I will eventually open source it and post a public repo, but not before I solve the big mislabeling problem around political posts myself, and clean up the flow and add proper configurations files for the CLI and local DB support, as it was supposed to be a challenge/fun project for me to learn from, if people start contributing and solving all problems I won't learn as much and that was not the plan I just didn't expect as many people to be interested in contributing to my "4fun" project.

Edit2: Also I'm trying to use this as a prototype to show to Reddit in hopes they'll give me Reddit Data API access so it can have a Live trend section for latest posts on Paki subs so I don't have to rely on public Reddit data dumps to increase the dataset in future.

I had around 3 weeks of downtime from work and I’ve always wanted to work on a proper social media classifier / sentiment analysis pipeline.

Not just basic “positive/negative” sentiment, but something more multi-dimensional. Like topic, intent, toxicity, emotion, political framing, subreddit trends, and local context.

So I built this for Pakistani Reddit:

Dashboard

If you only want to check the dashboard, that’s the link.

If you’re more interested in how I built it, or the technical side / mistakes / pain behind it, read below.

I originally wanted to do this with Reddit’s API. I applied for data API access, but they denied it because I’m not a student or researcher, and I assume they’re obviously careful now about people using post data for ML/custom AI models.

So I went for public Reddit data dumps instead.

Those dumps basically contain posts and comments, but they’re huge. Each monthly dump is around 60GB. My original plan was to download data from 2025 all the way to April 2026 and run my pipeline on that.

That did not happen lol.

The 2026 data was easy enough to download, but the 2025 data was barely seeded and was taking forever. I didn’t have forever. I had 3 weeks.

So I settled for the data I could actually get and process:

• Jan 2025
• Jan-April 2026

After that I had to figure out how to convert the dump format into something actually useful. I settled on Parquet because I like CLI workflows and wanted something fast enough to filter, split, query, and process without constantly fighting the data.

Then I filtered the biggest Pakistani subreddits and extracted the posts/comments I wanted to analyze.

My initial goal was pretty simple:

• sentiment analysis
• emotion detection
• toxicity check
• post topic
• post intent

But then I also wanted Pakistan-specific labels. Stuff public models probably won’t understand properly. Things like Pakistan/India posts, Imran Khan/PTI context, establishment framing, local political language, local subreddit behaviour, religion/culture posts, etc.

So I made a keyword/rule filter to pull likely Pakistan-themed posts, then manually labelled 1,000 posts to train a custom classifier.

The first model was terrible.

Like around 40% accuracy terrible.

So I labelled 2,000 more entries manually. That part was painful af. I think it took me around 6 days total to hand-label 3,000 entries.

After that I got the custom classifier to around 75% accuracy for Pakistan-specific themes, which was good enough for me for a side project.

The final pipeline ended up being a mix of:

• custom classifier trained on my manually labelled Pakistani Reddit examples
• zero-shot models for some topic/intent stuff
• sentiment analysis model
• emotion model
• toxicity model
• BART/NLI-style classification where it made sense
• keyword/rule heuristics
• confidence thresholds
• summary scripts for dashboard-ready tables

I don’t have rented GPU compute or anything. I just used the GPUs I already had at home on different PCs:

• 1080 Ti
• 3070 Ti
• 4080

So I started splitting the Parquet files and running parts of the pipeline across different machines.

At first I only ran around 10k posts at a time, checked the output, reviewed what looked wrong, tuned the rules/model, retrained, then ran it again.

Somewhere in the middle of this, for some reason, I decided to add political framing too.

In hindsight, that was probably the messiest part of the whole project.

Political posts are not clean. A political post can look like a question, a rant, a joke, a news post, an advice post, a meme, or just some vague one-line complaint. So if someone posted something political but framed it like a question, the pipeline might label it as question/help instead of politics.

I could have made it multi-label, but I didn’t want every post to turn into a complicated object with 5 different overlapping labels. I also wanted to keep this cheap/free to host on Supabase + Vercel, keep the schema simple, keep the dashboard understandable, and actually finish the project before my downtime ended.

So yeah, political framing is the weakest part. Some political posts are under-labelled or mislabelled. I’m okay admitting that.

I also set confidence thresholds.

If the model/rules were not confident enough, the post stayed as unclear. That does not always mean the pipeline failed. Sometimes the post was vague, sometimes it was Urdu/Roman Urdu, sometimes it was just an image or video, and my pipeline does not read images or watch videos.

Out of 95,593 total posts from the selected subreddits, 42,730 were labelled with high enough confidence that I felt okay showing them as useful dashboard signals.

The rest are still counted for volume/context, but I don’t treat them as strong labels.

I did try to review why so many were unclear, and a lot of them were either vague, media-based, Urdu/Roman Urdu, or political posts that didn’t fit cleanly into the label structure. But honestly, I was running out of time and I didn’t want to keep all my PCs running 24/7 for a “for fun” project forever.

For the workflow, I mostly avoided Jupyter notebooks. I know notebooks are useful, but for this project I preferred CLI scripts because the whole thing felt more like a data pipeline than an experiment notebook.

The general flow was:

1. download Reddit dumps
2. convert/extract usable data
3. save filtered data as Parquet
4. filter Pakistani subreddits
5. build keyword/rule sets
6. manually label training examples
7. train custom classifier
8. run sentiment/emotion/toxicity/zero-shot models
9. combine model outputs with rules and confidence thresholds
10. generate summary tables
11. upload dashboard-ready tables to Supabase
12. build the frontend on top of precomputed summaries

The app side is:

• Next.js 14 App Router
• TypeScript
• Tailwind
• Recharts
• shadcn/ui style components
• Supabase public read tables
• Vercel hosting

The data side is:

• Python scripts
• Parquet files
• custom classifier
• public ML models
• rule/keyword heuristics
• CLI scripts for summaries/uploads

The dashboard reads precomputed summary tables from Supabase instead of trying to load a massive dataset in the browser. I wanted it to be cheap to host and not completely die if people opened it.

I also used this project to properly test Codex after using Claude Code for months for my actual work. Codex honestly worked better for me on this project, especially for debugging frontend issues, TypeScript problems, and making the dashboard usable instead of just technically working. I honestly think codex might be better than claude code in its current state at least.
Not to mention I one shotted the network page using codex that was all codex, I just gave it a very detailed requirement and spec sheet and fed it obsidian articles about their network graph.

I also used it for script bugs, Supabase upload issues, and some Next.js cleanup. The actual pipeline and structure still took a lot of manual decisions, but for implementation/debugging but yea Codex was surprisingly good.

The dashboard is obviously not perfect.

Political framing needs work. Some labels are probably wrong. Some posts are under-labelled. Urdu/Roman Urdu support could be much better. Image/video posts are not really understood. And the dataset is limited because I could only process the dumps I could actually download in time.

But for a 3-week side project, I’m pretty happy with where it landed.

Would love feedback on what I should do differently in future from any ML people, to improve the pipeline and any idea's how to detect political posts better because right now it kinda sucks at detecting political posts, whenever I get some extra time again, I will probably work on this again and add more data and tune the pipeline more for Political framing and try to add Urdu script support.

Link again:

PakReddit Dashboard

As the title suggests. I wanted to understand, if I may, if anyone or any local startup is working on a tool that allows a user to archive all their generativeAi generated content into a Mandelay citation manager (a competitor then) like research library offline.
A product that is not intended for devs but
for the absolute layman user (who can copy, paste, print and email)
who wants to hoard their online activity with generativeAi offline tool on their own systems.
For the type of user who only knows MS Office.
If you are I would love to reach out.
Please be kind.

I need help. It’ll be my first interview tomorrow for an AI internee position. I kinda exaggerated a bit in my CV about projects etc. 😭 Can someone please guide me well or share possible interview questions? I’d be really grateful 🫶🏻

Would love any resources...

A little about me(from the previous post I made):

I am a 25 year old guy, I have done my bachelors in clinical psychology, but I have decided to transition into the field of tech after a few months of thinking. I got into Python, learned some basics, I would love to get more into cybersecurity in the future as well but for now I have decided to get more into Linux, RedHat and cloud computing. I am on a self-taught journey, I have no CS background. I am passionate about this enough but still at the very initial stage. I look forward to learning from the people here as much as I can.

Now,

Over the past few days, I’ve built and configured an Ubuntu home server while learning core Linux, networking, and self-hosting concepts through hands on troubleshooting and experimentation, it was honestly a fun thing to do. I worked with static IP configuration, Netplan, NetworkManager, SSH, and containerized services like Immich, while also diagnosing real networking issues such as Wi-Fi isolation and firewall accessibility. I explored remote access solutions like Tailscale, learned how Docker and CasaOS function, and began understanding virtualization, self-hosted infrastructure, and multi-service environments.

Through this process, I have understood some concepts and practiced ones I knew. I know this is still very basic but this as my first small project made my happy with the progress. I still have yet to strenthen my concepts as I am still close to three months into this.

If this makes any sense, is there anyone who can tell me how I should processed, what should I do next? I am still going through my KodeKloud LFCS course.

Thank you in advance.

(Edit): I am using an old Dell inspiron to run the server on.

I’m currently doing my A Levels and will be applying to universities soon. I live in Faisalabad and most likely will attend the Chiniot campus of FAST (NUCES), since other universities here don’t have as strong a reputation.

I’m very confused about whether pursuing tech—especially Software Engineering—is still a good path long-term. By the time I graduate (around 2030), will SWE still be worth it? I often hear that entry-level jobs are getting harder and that AI is changing the field.

Another concern is that I’m someone who has always been good at getting grades but hasn’t built any real practical skills yet. I’m worried that this might become a problem in a field like tech where skills matter more than academics.

I also cannot leave my city, so I want to understand realistically:

Are people actually able to get remote software jobs from cities like Faisalabad?

Freelancing and Upwork or fiverr are also becoming dead they are not source of predicatble income. People who are able to get clients off platform mostly they get clients which pay them monthly retainers.

I see people younger than me online claiming to build AI agencies and make money, which motivates that I should go in tech. At the same time, I don’t think I can spend this summer learning those skills because I need to focus on entry test preparation. After that, FAST has a reputation for being very demanding (“ragra”), so I’m concerned I won’t have time to build practical skills during university either.

FAST also offers a Fintech degree, which combines CS and business. From what I’ve heard, graduates often go into roles like data analysts or financial engineers They can also become SWE go into machine learning and stuff.

So my main questions are:

1. Is pursuing tech still worth it for someone graduating around 2030?
2. How realistic is it to get remote work or freelance opportunities from a smaller city?
3. Given FAST’s workload, how do students realistically build practical skills alongside their degree?

I’d really appreciate advice from people who have gone through a similar path or are currently working in the industry.

Have a technical interview regarding the llm intern position. What can i expect?

Hello everyone.

I am a CS student graduating in about a month. Over the last year, I have sent out around 90-100 applications in total, landed about 5 interviews, and received 2 offers (both for internships, no full-time role offered yet). This is driving me crazy given how much effort I’ve put into improving my resume, building multiple high-quality projects, and managing my studies alongside it all.

My university is also considered decent in the market, but despite that, this is where I stand. I am just curious about what other people who are about to graduate or have recently graduated are experiencing. What type of responses are you guys getting? I want to know if this is just a general market problem right now or a problem specifically with me.

Some people have told me that my chances will get better once I officially graduate, but honestly, I am feeling pretty hopeless about that too.

What's the best way you or anyone you know has got a job? Except through networking. I am trying to find job or another internship. But I don't know how to do networking and I have applied on LinkedIn and Indeed but still can't find it. Can you guys give me ways to get a job without networking?

{Not asking for job, just advice/guidance.}

Hi everyone,

I’m currently a CS student at FAST-NUCES, my university has maybe decent or average value in market(idk much about that) and have around 1.5 years of hands-on experience working remotely with a Canada-based client. My work has mostly involved a mix of Full Stack, AI/Data-related tasks, and general engineering support depending on project requirements.

Even though the remote work experience has been great and I’ve learned a lot from it, I still want to experience working in a proper company environment through an internship or junior role because I believe it will help me grow faster technically and professionally.

For the past few months I’ve been applying actively on LinkedIn, but it feels extremely difficult to even get interview calls because most postings already have hundreds of applicants within hours 😭

So I wanted honest guidance from experienced developers here:

• Am I applying the wrong way?
• Is the market really this difficult for juniors right now?
• What skills/projects make a candidate stand out for internships or junior positions?
• How important are referrals compared to cold applying?

If someone is willing to review my resume/portfolio and point out mistakes or improvements, I’d genuinely appreciate it a lot.

I’m continuously learning and currently focusing more on cloud/devops-related skills as well.

Any advice would genuinely help. Thank you ❤️

I'm 5 years into software development as a Full-stack Java (Spring Boot) + Angular. Currently working at a product based company. Feeling a bit clueless at the moment, with the inflation and the industry saturation.

I recently started applying elsewhere and also started prepping for interviews a bit. But honestly I don't even know if I'm aiming for the right thing anymore. Freelance work? Local switch? Foreign remote? A side hustle?

For those who've been at this stage and broken through - what actually worked?

Did anyone else face the same?

I post 100% honest review regarding the toxic culture and incapable people-managers at Systems Limited that i witnessed with my own eyes. Glassdoor approves it as it doesn't go against any of its policies. The review appears on Glassdoor for a few days and then disappears. When i go and check, it has silently been 'archived'.

How can Glassdoor do that?

You guys remember the scene when Tom (Tom & Jerry) looks in the mirror and sees a donkey? Yeah, that's exactly how I feel today.

Startups are the worst. Never consider them your home.

I joined a US-based startup 10 months ago and gave them my 200%. Worked from dusk to dawn (2 to 3 unpaid hours every single day) , and slowly lost my identity as a software developer to become a video editor, because that's what was required of me just to keep my remote job.

In the end it didn't matter. They kept telling me I didn't need to be 100% good, that 85% was enough. Yet they let me go because they wanted someone who is 100% good.

So my advice to every newbie is, no matter how irreplaceable they make you feel, no matter how many promises they make about your bright future with them, don't take it seriously.

Treat it like a business. Give them what they pay for. No gifts. No buy one get one free.

Shift is 6pm to 2am. Day one they had me install something called TeamLogger. It tracks keyboard and mouse activity the whole shift and takes random screenshots so management can see your screen anytime.

Here's where it gets weird. I'm required to log 8 hours daily. The timer only runs when you're actively moving. Stop for 5 minutes. bathroom, reading docs, just thinking timer pauses. So I sat there for basically 9 hours today, gave it everything, and still clocked out at 7 hours logged.

I did my best and still came up short because I dared to think for a few minutes.

What bothers me most:

You can work a full shift and still not hit 8 hours on their system

Thinking, reading, debugging none of it counts unless your mouse is moving

Random screenshots mean management sees your screen without any warning

Night shift 6pm to 2am already wrecks your sleep and social life

All of this on day one, before you even proved yourself

I understand remote work needs some accountability. But this feels less like trust and more like they bought software and called it management.

I need suggestions for Free or paid good file extractors other than the aforementioned. My WinRAR is licensed, but I don't know if it is genuine or pirated.

Got selected for next round of JazzWorld AI Associate program and apparently it will be conducted by a AI called Moxiv AI.

Anyone has any experience with this ?

P.S It feels disrespectful being interviewed by AIs now, the least these companies can do is screen manually.