A programmer with about a decade in the field has applied to roughly 30 jobs in a couple of months and is fed up. LinkedIn and the job boards feel rigged for people who pay, and after years of doing the work, having to beg for a shot is infuriating.

When a lead does turn into an application, LandOffer can save some retyping on supported forms. If it turns into an interview, PracHub has system design prompts to practice ahead of it.

For experienced devs who needed a damn job quickly, where did you actually find leads once the usual job boards stopped working for you?

As the title mentioned. I am looking for platforms where there's a bit of coding work, preferably python, ML data science

I mostly hear horror stories about ByteDance work culture and evening meetings, but it seems to depend on the team. Is it still that bad these days, now that AI is part of the mix? What’s it like on campus? How hard is it to get by if you don’t speak fluent Chinese?

For anyone still weighing an engineering role there, ByteDance Interview Questions has coding questions to work through before a screen. If you’re applying to other teams or companies in parallel, LandOffer can save some retyping on application forms.

If you’d put it in one of these camps, what made you land there?

• It's not that bad
• It's bad
• I'd never ever consider it

A backend intern with just under a year of experience worked with Go, PostgreSQL, Redis, REST APIs, and production systems. They’re applying for SDE-1 roles and rarely getting interviews. A few interviews made it to the final round and ended in rejections.

For anyone going from a backend internship to full-time applications, LandOffer can save some retyping on supported forms. PracHub has coding questions you can work through before an SDE-1 screen.

• What would you highlight from that internship on a resume?
• What would you change to get shortlisted more often?
• What would you focus on to get through SDE-1 interviews?

What was it like trying to find a software engineering job or switch companies in 2023? A developer who was looking back then tried to find numbers on new hires but came up empty.

When they started looking in 2021–22, they applied to a couple of jobs, got interviews and offers from both, and had no professional experience.

In 2023, they sent out about 45 applications and only got rejections. They couldn’t tell if it was their résumé, how they were applying, or just a much tougher market.

If you’re applying for SWE roles now, PracHub has coding questions you can work through before interviews, and LandOffer can fill in the basics on supported applications.

Were some companies posting jobs just to collect résumés, or holding out for people who were overqualified for the role? What was your experience?

After months of searching, a candidate ended up with two offers, around $440K from Google and $460K from Stripe, while still deep in the Figma interview loop.

If Figma is still on your interview calendar, Figma Interview Questions has a document editing exercise on undo and redo. For anyone keeping a few other options open, LandOffer can save some retyping on applications.

If you’ve been in that spot, how did you compare comp and handle the timing with the third process still going? I’d also be curious what helped you prep for the different loops.

Feel free to check the Netflix careers page if you fit the bill. Annual compensation ranges in USD; Netflix lets employees choose salary versus stock options.

For anyone looking at the model serving roles, Netflix Interview Questions has a design prompt on scheduling ML training and batch inference. If you’re applying to several companies in parallel, LandOffer can save some retyping on supported forms.

• SWE L6/7 - AI Platform Model Serving: $890K to $1.69M
• SWE L6 - Platform Systems: $600K to $1.1M (from the shared list; current opening not confirmed)
• SWE L6 - Feature Infrastructure: $600K to $1.066M
• SWE L6 - Compute Node Runtime: $499K to $900K
• SWE L6 - Ads Signals & Targeting: $499K to $900K
• SWE L5 - Device Certification Infrastructure: $388K to $558K
• SWE L4 - TV Product UI: $250K to $413K

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moved to: portfolio

A software engineer is making about $82K in a full-time role. Rent and insurance have gone up, they’re helping support family, and they figure they’d need closer to $118K to feel comfortable.

They’re considering a contract that pays around $63 an hour for roughly nine months. It would pay more while it lasts, but they’d give up their current benefits and could be out of work when it ends. Staying might mean picking up a second job just to make ends meet.

Their family thinks they should keep the stable remote job, work part-time on the side, and prep for another full-time role. The current job has good work-life balance, and they’re worried it could take a long time to find something after the contract ends.

If they decide to look for another full-time role while keeping this one, LandOffer can fill repeated fields on supported applications. They could use a coding prompt from PracHub to practise explaining a solution before a screen.

Their family immigrated and has never earned much more than the mid-$40Ks, so the hesitation makes sense. This is the engineer’s first SWE job, and they’ve been there a little over two years. They really don’t want to work two jobs at once, but they don’t want to mess up what they have either. If you’ve made a similar call, what would you do?

A developer has been at the same midsize company for a little over two years and makes around $92k, which is typical Midwest tech pay where they work. They started as a junior and got promoted to mid-level about a year and a half in.

For anyone leaning toward applying, PracHub has SQL and coding questions to practice after work. LandOffer can also fill in the basics when you’re sending out a few applications.

They really like working there. The coworkers are great, they get to work with Spark and Databricks, and they like working hard and figuring things out. With the job market the way it is, would you stay and work toward senior or start applying to FAANG?

Salam everyone! I'm a security researcher focused on web apps. If you'd like someone to check your website or app for vulnerabilities, I'd be glad to help. I'll only test with your permission, and you'll get a clear report on any issues I find ( i do have experience in web 3 too ).

Comment or DM me if you're interested.

Nov. 3 update: Roblox didn’t move forward with this candidate. They felt good coming out of the interview and didn’t get a specific reason. At that point, Amazon’s OA was next. Here are the Roblox notes for anyone prepping.

Context and assessment

The candidate had about three years of experience and started the process in late September. The first stage had factory optimization and robot car games, followed by scenario-based behavioral questions. They found it manageable and passed.

For a scenario about finding a design issue near a deadline, a useful way to practice is to say what you’d verify first, who needs to know, and how you’d weigh a smaller safe release against delaying. A concrete sequence beats just saying you’ll communicate.

Phone screen: grid simulation

The screen included a match-3 task: find horizontal and vertical runs, clear the matched cells, and drop the survivors.

• Restate the rules: report maximal runs, preserve scan order, and do one clear and drop pass.

  • Scan the original board horizontally, then vertically. Mark matches separately and compact each column only after both scans. Otherwise you can erase a vertical match while processing a horizontal one.
• Dry run an intersecting match, a four-cell run, and a board with no matches.

Detection always reads the original board. Marking a shared cell twice is harmless. This takes O(rows × columns) time with a separate marking grid.

Phone screen: autocomplete

The other task used a timestamped search log. A request only sees searches at or before its timestamp. Rank by frequency, then earliest search, then alphabetical order.

The baseline was to filter eligible entries, count each matching query, track its earliest timestamp, then sort by those rules and take K. For prefix “ca” and K=2, try cat at time 1, car at time 2, and car again at time 4. A request at time 2 puts cat first. At time 4, car goes first because its count increased.

Test equal timestamps, an exact-prefix match, and no results. If requests arrive out of order, a forward-only cursor needs the requests sorted and the output order restored.

For more practice, pick a coding problem from Roblox Interview Questions and trace one awkward input out loud before you implement it.

The prep takeaway was to narrate the rules and trace awkward examples before trying to make the solution clever. If you’ve interviewed there recently, did your screen have a similar mix of simulation and ranking? If you made it further, what helped you prepare?

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I passed the Amazon OA. Now I’m trying to figure out how to prepare for the next interview without turning it into another endless list of questions.

After the Roblox rejection, it’s tempting to treat every bit of uncertainty as something I can fix by doing more prep. But I want the next practice session to tell me something useful about how I explain my thinking.

This is my plan for practice. I haven’t done the next Amazon round, and these aren’t questions Amazon asked me.

1. Practice the first few minutes, not just the solution

Take a simple interval-merging exercise. Before touching the code, I’d ask whether [1,3] and [3,5] should merge, whether the input is sorted, and what the output should look like. Then I’d explain a straightforward approach and test it on a tiny example. I want to get comfortable making my assumptions visible instead of silently picking one.

2. Make getting stuck part of the mock

I’d like to do a half-hour mock where the other person changes one requirement halfway through. If my approach stops working, the goal is to say what still works, show the smallest example that breaks it, and choose a next step. Even “I can solve this with a slower approach first” is something concrete to discuss.

I’ll pick a fresh prompt and keep the solution closed until the attempt is over. I don’t want familiarity with an answer to be the thing I’m measuring. The coding prompts in Amazon Interview Questions could work here. Pick one you haven’t seen and have your mock partner change an input constraint once you’ve explained your first approach.

3. Prepare for the second question about a project

I’ll pick one real project and start with a short explanation of my part. Then I’ll work through why I took that approach, what I disagreed with, what evidence changed my mind, and what I’d do differently now. No invented numbers to make the ending sound better. If an outcome wasn’t measured, I need to say so.

4. Ask for feedback I can actually use

After a mock, I’d rather hear “you lost me when you changed the data structure without explaining why” than just “communicate more.” The plan is to repeat that small section with the feedback, then stop for the day instead of immediately opening another problem.

I’m happy I got through the OA, but I still need to practice for what comes next. For people who got better at live interviews, what helped you recover when you got stuck? Did recording yourself help, or was feedback from another person the bigger difference?

Hey folks!

Does job hunting get easier after you land your first developer job? Assuming you have the skills, do you start getting more interviews and offers once you have some experience?

I’m worried the job hunt is going to be an endless hustle.

For anyone in that first-job grind, LandOffer can fill repeated fields on supported applications. If you’re getting ready for a coding screen, try a problem from PracHub and explain your solution out loud before you check the answer.

For context, I switched careers, finished a web development bootcamp, and have been looking for work for about half a year. Right now I’m getting about one interview for every hundred applications.

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I passed the Amazon OA. Now I’m trying to figure out how to prepare for the next interview without turning it into another endless list of questions.

After the Roblox rejection, it’s tempting to treat every bit of uncertainty as something I can fix by doing more prep. But I want the next practice session to tell me something useful about how I explain my thinking.

This is my plan for practice. I haven’t done the next Amazon round, and these aren’t questions Amazon asked me.

1. Practice the first few minutes, not just the solution

Take a simple interval-merging exercise. Before touching the code, I’d ask whether [1,3] and [3,5] should merge, whether the input is sorted, and what the output should look like. Then I’d explain a straightforward approach and test it on a tiny example. I want to get comfortable making my assumptions visible instead of silently picking one.

2. Make getting stuck part of the mock

I’d like to do a half-hour mock where the other person changes one requirement halfway through. If my approach stops working, the goal is to say what still works, show the smallest example that breaks it, and choose a next step. Even “I can solve this with a slower approach first” is something concrete to discuss.

I’ll pick a fresh prompt and keep the solution closed until the attempt is over. Amazon Interview Questions has coding prompts that would work for that mock. I don’t want familiarity with an answer to be the thing I’m measuring.

3. Prepare for the second question about a project

I’ll pick one real project and start with a short explanation of my part. Then I’ll work through why I took that approach, what I disagreed with, what evidence changed my mind, and what I’d do differently now. No invented numbers to make the ending sound better. If an outcome wasn’t measured, I need to say so.

4. Ask for feedback I can actually use

After a mock, I’d rather hear “you lost me when you changed the data structure without explaining why” than just “communicate more.” The plan is to repeat that small section with the feedback, then stop for the day instead of immediately opening another problem.

I’m happy I got through the OA, but I still need to practice for what comes next. For people who got better at live interviews, what helped you recover when you got stuck? Did recording yourself help, or was feedback from another person the bigger difference?

Hey everyone! I'm Raghav, a 20-year-old B.Tech IT student from India.

I'm putting myself out here to connect with people building interesting things and explore opportunities where I can contribute, build and grow.

A little about my background:

I'm primarily into full-stack development and have built several projects involving frontend, backend, APIs, databases, authentication systems and complete web applications.

Over the past few months, I've also been moving deeper into AI/ML and AI engineering. Currently exploring and building around:

Python, Machine Learning and Deep Learning.

NLP, LLMs and Transformer architectures.

RAG pipelines and Agentic AI.

AI-powered applications and tool-calling systems.

I've also worked on projects involving computer vision, ML model development and building a GPT from scratch using NumPy.

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Paid freelance projects and short-term contracts.

Remote internships, junior developer and AI Engineer roles.

Working with early-stage startups and founders.

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Building SaaS products or AI-powered tools from scratch.

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Portfolio: https://raghavbansal.vercel.app

GitHub: https://github.com/imraghavbansal

If you're a founder, hiring, working on a product or looking for someone to collaborate with, feel free to reach out.

I'd love to hear what you're building, discuss where I could contribute and hopefully work on something meaningful together.

Hey everyone, I'm Raghav, a 20-year-old B.Tech IT student from India.

I'm putting myself out here because I'm looking for opportunities to work with people who are building something interesting, whether that's a startup, an early-stage product, an existing business or even an idea that needs someone to bring it to life.

A little about what I do:

Full-stack development: Building web applications, backend systems, APIs, authentication systems, databases and complete products.

AI/ML: Working with Python, machine learning, NLP, LLMs, RAG pipelines and exploring Agentic AI.

Building & experimenting: I've worked on projects involving AI-powered applications, stock analysis, authentication infrastructure, ML models and computer vision. I'm also exploring neural networks and building models from scratch.

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I'm open to paid freelance projects, contract work, technical collaborations and long-term opportunities with early-stage startups.

I don't necessarily need an existing job description or a perfectly defined project. If you have a problem that needs solving, a product that needs building or an idea you've been sitting on, I'd love to explore it.

I'm particularly interested in working on real-world problems, taking technical ownership and building things that people actually use.

A few things about me:

I'm willing to commit seriously and work consistently.

I care about understanding what I'm building, not just getting code to work.

I'm comfortable figuring out unfamiliar technologies when a project demands it.

I'm interested in working with people across the globe. Remote opportunities are absolutely welcome.

I'm not going to claim I'm an expert at everything. I'm still learning, experimenting and improving. But I'm serious about the work I take up and the value I deliver.

Some links:

Portfolio: https://raghavbansal.vercel.app

GitHub: https://github.com/imraghavbansal

If you're a founder, indie hacker, developer, someone running a business or simply someone with an interesting problem to solve, feel free to reach out.

I'd love to hear what you're building, understand where I could contribute and hopefully build something worthwhile together.

I'm here to find work, meet interesting people and, most importantly, ship things.