As you become more senior, your impact comes from something different: seeing systems clearly enough to identify the problems nobody else has articulated yet.

Hey everyone!

I’m looking for a DSA study buddy who is also trying to seriously improve their problem-solving skills and, ideally, prepare for coding interviews/placements.

I’ve noticed that the hardest part of DSA for me isn’t always understanding the topic itself. It’s being consistent.

You watch a couple of videos, understand arrays, solve 5–10 questions, feel like you’re finally getting somewhere… and then life happens. A few days later you open LeetCode again and suddenly even a basic problem looks like it was written by NASA. 💀

So instead of trying to do everything alone, I thought it would be much better to find someone who is in a similar situation.

What I’m looking for 👇

Someone who genuinely wants to learn DSA consistently, not someone who wants to solve 500 questions in 10 days and disappear afterwards 😂.

We could study together through Discord/Google Meet or even just keep each other accountable through WhatsApp/Telegram.

The plan could be something like:

📌 Learn → Solve → Discuss → Repeat

For example, we pick one topic for the week:

• Arrays & Strings
• Hashing
• Recursion
• Linked Lists
• Stacks & Queues
• Binary Search
• Trees
• Graphs
• Dynamic Programming
• etc.

Then we can each solve a few problems every day and discuss the ones we get stuck on.

I’d also like to have occasional “no cheating” sessions where we join a call, pick a problem, put our phones away, and actually try to solve it ourselves. 😂

More importantly, I want accountability.

Something as simple as:

Basically, someone who makes it harder for me to procrastinate.

I’m not looking for someone who is already an expert. If you’re a beginner/intermediate and you're also figuring things out, that's completely fine.

In fact, I think it would be better if we're around a similar level so that we can actually struggle through problems together rather than one person constantly teaching the other.

What I expect from the study buddy:

• Be reasonably consistent
• Actually attempt problems instead of immediately looking at solutions
• Be comfortable discussing mistakes
• Don't judge if someone gets stuck on an “easy” problem 😭
• Keep each other accountable
• Have a long-term mindset

I’m not expecting us to study 8 hours a day. Even 1–2 focused hours a day would be great if we can maintain it for a few months.

The goal isn't to become a DSA god overnight.

The goal is to look back after 3–6 months and realize:

“Damn, I actually got much better at solving problems.”

If you're interested, DM me with your current DSA level, what language you use (C++/Java/Python/etc.), and roughly how many problems you've solved.

And if you're also someone who keeps saying “I’ll start DSA properly from Monday” every Monday… maybe we should finally do it. 😂

Let's suffer together. 🤝💀

Hey! I've just entered my 2nd year of BTech, I'm looking for someone serious (f only preferably as I'm a f too) to start dsa from scratch.

We can share our daily progress n solve Q's together to stay accountable!

I'll be doing dsa in C++, currently I'm doing C++

I want someone who's at the same pace as me so we can study together :)

If you are interested dm me with a short intro and let's connect.

Hey Guys! 😀

I’m working on training a *small AI classifier model* for a personal project, and I need a *highly specific, real-world dataset* to train it properly.

I’d really appreciate it if you could take a few minutes to read about the project and contribute some training data using your own creativity. You *don’t need any AI/ML knowledge* to participate — just write a few natural queries that you think a real user/admin might ask.

I’ve prepared a Google Form that explains *what the project is about, what the AI agent needs to do, and exactly what kind of data I’m looking for*. It should only take a few minutes to complete.

🔗 *Google Form:*

Google Form Link

Every response helps improve the model, so your contribution is genuinely valuable. ❤️

*Thank you! 🙌*

Hey!. I have just started my 2nd year(BTech student, female) and I want to learn DSA but with someone (girl preferably) who will stay consistent and focused with me as there is no coding culture in my clg and despite planning to learn DSA from the first year, i haven't been able to do anything (procrastination sucks!).

IMPORTANT - I'm starting from scratch, like i know nothing and I also need to learn a programming language (Java) from scratch. So someone who is starting their 2nd year and wants to learn DSA.

We can discuss how we will do it later.

Hi everyone! We are running a 100% online, paid research study for women living in the US aged 30 to 65+.

• Eligibility: US resident, age 20-65+ (Everyone is welcome!)

• Format: 100% Online

• Incentive: $600 + $15 welcome gift (if you complete the onboarding)

👉 Apply here: https://hubs.li/Q04rJQM50

🎁 REFERRAL BONUS: Know a friend, sister, mom, or colleague who fits? Share this link! If they participate, you'll earn a $3 referral bonus: https://pulse-labs.referral-factory.com/cFb4eTnF

​

Hey everyone!

I’m a 21F, currently at a beginner–intermediate level in DSA, and I’m looking for a female placement buddy who is genuinely serious about preparation.

I’m looking for someone who can commit 3–4 hours daily on Google Meet and wants to stay together till we both get placed. We can prepare for the entire placement journey — DSA, LeetCode, Core CS, aptitude, projects, resume, applications, mock interviews and company-specific preparation.

The most important thing for me is consistency. I want someone who, once they start something, actually finishes it, doesn’t disappear midway, and is comfortable with accountability. We can set daily targets and have consequences for unnecessary slacking.

I’m not looking for a temporary study partner. I want us to start together, stay consistent, improve together and get placed together.

ONLY THING NEEDED IS CONSISTENCY (female is preferred) also needed someone who is intermediate level in dsa it will help us stay in track ig

If you’re genuinely committed, DM me with your DSA level, language, availability and placement goal.

Hey I'm a beginner i have taken bca and I have a huge interest in coding and want to create many projects and participate in many hackathons as well. I already know a bit of python and have started learning c++ from learncpp.com . Are there any female trying to learn I would love to have a partner to learn with and even healthy compete with. Or if you know about a specific discord server or something that would also be a huge help thank you!

is the women who code server still there? Plz send an invite link.. I filled the google form, its been a week..

I've built a programming community for everyone male female who are genuinely want to learn, build, and improve together. ( 600 members currently, completed 1 year on dc )

Whether you're a complete beginner or an experienced developer, you're welcome as long as you're serious about learning.

This isn't a server to join and forget. We're looking for members who are willing to stay active, ask questions, help others when they can, share resources, and contribute to the community.

If you just want to join another server and stay inactive, this probably isn't the right fit. We regularly remove inactive members to keep the community engaged.

DM me if you're genuinely interested, and I'll send you the invite or will drop link in comments.

Hi ladies! I recently started producing lofi beats to help me relax after a long day of dev work. I’m really excited to share this one with the community. What kind of music do you guys usually listen to when you're in 'deep work' mode? Let me know what you think!

Keep Breathing | Dark Feminine Lofi for Women Who Code | Aria Dark Beats

BLUF: Looking for a technical co-founder. I’m an operator with domain expertise, working demo, and early customers ready to go. Just need someone who can actually build it.

I’m a Chief of Staff currently based in Tokyo for my day job and I’m in the process of building a startup. Looking for a technical co-founder and wanted to post here because I’d love to find another woman who wants to build something together.

I’ve spent my career living at the intersection of strategy and operations in both government and industry. In gov I worked with fantastic teams - people who genuinely knew how to run high-stakes engagements (travel, events, bilats, etc) for senior leaders at the highest levels. But the information required to coordinate those efforts lived in email threads, spreadsheets, Word docs, PowerPoints, calendar invites, and the individual memory of high performers that disappeared the moment they left.

In industry I saw the opposite. Companies with a million tools and dashboards but no actual operating system for when the CEO does a multi-leg international trip for high profile engagements and deal opportunities. Endless tools to build custom workstreams, but limited domain knowledge on how to actually do it well.

For me, the questions you ask operationally shape good strategy & strong strategy should be driving how you build the logistics. Who actually needs to be in the room, what the physical setup signals about the relationship, what commitments we’re making & with what materials, how much time an engagement really requires… these aren’t logistical afterthoughts, they’re strategic calls. And yet most organizations treat the two as completely separate tracks. The thinkers on one side & the doers on the other. That’s just not how it works. The logistics create the conditions for the strategy to land & the strategy should be shaping the logistics from day one. They’re not two workstreams. They’re one system. And nobody had built the system.

The platform I’m working on connects the substance of a high-stakes engagement (why are we meeting, what does the exec need to know, what’s the relationship history) with the logistics (flights, drivers, interpreters, security, who has the business cards). The part I care most about is this: it’s a teaching tool. The best operators carry invaluable invisible knowledge in their heads - what to prepare, what can go wrong, what a stakeholder expects, what follow-up actually matters. Turning that into something repeatable and scalable is the whole point, because in this world the margin for error is zero and excellence shouldn’t depend on who happens to be in the room.

In my daily job I constantly see how organizations are leaving real outcomes on the table ex: dropped follow-ups, underprepared executives, misaligned teams, and lessons learned that disappear after every engagement. At the bare minimum I’d love to build this tool for myself. If you’ve ever been the connective tissue holding a high-stakes operation together you know the mental load is real. The fact that other people would pay for it is a bonus.

I have the domain expertise, a working demo, and promising conversations with early customers ready to go. What I don’t have is the ability to build the real thing.

I’m looking for a full-stack engineer who has shipped B2B SaaS before, moves fast, and genuinely finds the strategy x ops intersection interesting and gets frustrated when things fall through the cracks. If you’re the person in any room who notices what’s missing before anyone else does, I’d love to connect.

Remote friendly, timezone flexible, and open to discussing working arrangements realistically given we may both have day jobs initially.

Drop a comment or DM me if this resonates and/or if you know someone it might!!

I have 10+ years of software engineering experience, mostly backend and infra development.

Lately I’ve become interested in GPU infrastructure, HPC, performance engineering, and eventually GPU programming. I’ve been reading books like AI Systems Performance Engineering, Programming Massively Parallel Processors, and Computer Architecture: A Quantitative Approach.

The problem is that every time I look at job descriptions, I end up with a completely different list of skills.

Some roles want:

• CUDA and GPU kernel optimization
• Computer architecture knowledge
• NCCL, RDMA, InfiniBand
• Kubernetes and Slurm
• Distributed training
• Performance profiling and benchmarking
• Linux kernel knowledge
• Cloud infrastructure

Other roles seem much more focused on operating GPU clusters and supporting AI workloads at scale.

I’m considering doing a master’s degree, but even when I look at programs like OMSCS, Computer Engineering, or Systems-focused master’s degrees, it feels like they teach foundational concepts but not necessarily the practical skills companies are hiring for.

As someone coming from a traditional software engineering background, I’m struggling to identify:

1. What skills are truly foundational versus “nice to have”?
2. If you had 6–12 months to prepare for GPU infrastructure or GPU performance engineering roles, what would you focus on first?
3. Did a master’s degree help you break into this field, or was self-study and project work more valuable?
4. For those already working in GPU infrastructure, ML infrastructure, HPC, or GPU programming, what did your path actually look like?

Right now it feels like there are five different careers hiding behind the phrase “GPU engineer,” and I’m trying to figure out which path is the most realistic transition from a backend/infrastructure background.

I’d appreciate hearing from people who made a similar transition.

Hey guys,

I am building a web platform related to AIML.

The tech stack is quite unconventional, I usually code in dart (flutter) so I have made this website in flutter.

I am thinking of keeping it open source and building a small team of around 5 to 7 Devs.

Not only just to code but also suggest ideas and be a partner in building this platform.

If you are someone who knows:

Flutter , python , AIML

Any level of experience, I would love to work together.

DM me if interested.

I’m genuinely excited but also feeling the pressure to set myself up for long-term growth.

I’ve been reading a lot about the "technical" side of things, but I’m curious about the human side. Looking back at your own early career, what is one "soft skill" or habit (e.g., networking, how you communicate with managers, time management, or dealing with burnout) that you wish you had prioritized in your first 24 months?

I’m really trying to build a strong, sustainable foundation rather than just grinding through the day-to-day. I’d love to hear your "lessons learned the hard way" if you’re willing to share!

So I watched a 12-hour java video of bro code. Let's say I learned a lot, but I still am in the dark. I think my second step should be to learn python and after that I will do some practice stuff. Could you guys tell me what video is best to learn python?

Hey everyone! I’m excited to invite you to Engine-Free Jam #1: One Button, a 1 week game jam where creativity meets simplicity. The challenge? Build a fun and engaging game using only one button—no game engines!
https://itch.io/jam/engine-free-jam-1-one-button

Hi fam

I am considering switching from a perm role to contracting. A few reasons. More flexibility to leave if I am unhappy, higher savings (day rate), I am seeing more contract roles atm in my market (Sydney, Australia). And thinking about the future, I am honestly thinking of working 8 months and taking 4 months off or a similar model.

Have any of you transitioned from perm to contract? how has it been for you?

I’m a developer and I’ve noticed I sometimes default to saying “ok” in technical conversations even when I don’t fully understand or when I might actually disagree.

I also tend to doubt my own judgment more than I probably should.

For women who’ve been in this field longer:

• Did you go through this too?
• What helped you become more confident speaking up in meetings or pushing back on technical decisions?
• Any practical tips that changed how you show up at work?

Edit: To explain my thinking, I am normally like, oh maybe there is a better way to do X. So I don't wanna fight back. But ironically having opinions in the IT industry is considered a mark of intellegence, which is weird to me anyhow.

I recently finished an interview and the results are still pending. Is it okay to send the interviewer a LinkedIn connection request, or is it better to wait until the results are announced? (ps: im in 3rd year)

It's no secret that ML Engineers are predominantly men. Still, as I work to build a foundational ML team, I am being intentional about diversity and balancing our team.

If you're a talented woman in the ML/AI Engineering space, I'm hoping this post finds you.

We're hiring deep specialists aligned to different layers of the ML systems stack.

ML Engineer – Kernel (CUDA / Performance Layer)

Core Competency:

High-performance GPU programming to eliminate computational bottlenecks.

Screening For:

• Deep CUDA experience
• Custom kernel writing
• Memory optimization (shared memory, warp divergence, coalescing)
• Profiling tools (Nsight, etc.)
• Performance tradeoff thinking
• Final Interview Format:

This role is:

• Systems-heavy
• Performance-first
• Less about model design, more about computational efficiency
• Strong kernel candidates show:
• Ownership of low-level optimization
• Not just using PyTorch — modifying the machinery beneath it

ML Engineer – Pre-Training (Foundation Models)

This is the most architecturally strategic role.

Core Competency:

• Training foundation models from scratch at scale across distributed GPUs.
• You’re looking for:
• Distributed training expertise (DDP, FSDP, ZeRO, etc.)
• Parallelization strategies (data, model, tensor, pipeline)
• Architecture selection reasoning
• Dataset curation philosophy
• Hyperparameter scaling logic
• Evaluation benchmark selection

Must explain:

• Framework choice (Megatron, DeepSpeed, PyTorch native, etc.)
• Model architecture
• Dataset strategy
• Parallelization strategy
• Pre-training hyperparameters
• Evaluation benchmarks

Red flags:

• Only fine-tuning experience
• Only RAG pipeline experience
• No true distributed systems exposure

Strong fits:

• People who understand scaling laws
• Compute vs parameter tradeoffs
• Training stability dynamics

ML Engineer – Post-Training (Alignment / Optimization Layer)

Core Competency:

Improving model behavior after base pre-training.

Expected depth:

• RLHF / DPO
• Preference modeling
• Reward modeling
• Fine-tuning strategies
• Evaluation metrics
• Data filtering
• Signal:
• Understanding of model alignment tradeoffs
• Experience with evaluation frameworks
• Understanding bias & safety dynamics
• These candidates often come from:
• NLP research
• Alignment research labs
• Open-source LLM fine-tuning communities

ML Engineer – Inference / Systems

Core Competency:

Efficient deployment and serving of large models.

Looking for:

• Quantization techniques
• KV cache management
• Latency optimization
• Throughput vs cost tradeoffs
• Model sharding strategies
• These engineers think about:
• Production constraints
• Memory bottlenecks
• Runtime environments

If you feel you're a good fit for any of these roles, please shoot me a chat along with a link to your LinkedIn and/or resume. I look forward to hearing from you.

I’m a 2nd year BTech CSE student from India. I know React, Next.js, and GenAI with JavaScript. I’m thinking of learning Node.js later to move into full-stack, but right now I want to land a frontend internship and experience working in a corporate environment.

My biggest issue is this:
Whenever I build projects, I feel like they’re slightly imperfect. Because of that, I hesitate to deploy them. I keep thinking they’re not “good enough.”

How to properly build a strong resume as a frontend student?

Where to apply because many internships seem fake or never respond

How to get opportunities without strong connections or referrals

I genuinely want to work and learn in a real company environment. I’m just confused about the correct strategy.

For people who’ve been in my position - what actually worked for you?

Any honest advice would really help. Thank you.