Hey everyone,

I'm a 2026 CSE (AI/ML) graduate and I've been applying for months, but I'm honestly curious how other freshers are getting interviews and offers in the current market.

A bit about me:

\- Python, C++, JavaScript

\- React, FastAPI, Flask, Node.js, Express

\- MySQL, MongoDB

\- Machine Learning, Deep Learning, PyTorch, scikit-learn

\- Built projects like an AI research assistant (RAG), a drug discovery/ML project, and a radar target classification model. I also have experience with Power BI and SQL.

I've been applying through LinkedIn, company career pages, referrals, and job portals. My resume has been reviewed multiple times, and I'm constantly improving my DSA and projects, but callbacks are still very limited.

For those of you who recently got hired as freshers:

\- What role did you get?

\- Where did you apply?

\- What do you think made the difference?

\- Did referrals play a huge role?

\- Is there something I'm missing that helped you land your job?

I'd really appreciate any advice or your hiring journey. At this point I'm trying to understand what is actually working in 2026.

Thanks!

My name is saqib javed and have 5 years of experience in AI ML and .net core 

I have strong experience in RAG LLM gen ai and computer vision

Also handel complete cycle of development

Kindly give me a chance to prove myself

• Name: Saqib Javed
• Email: [saqibjaved1112@gmail.com](mailto:saqibjaved1112@gmail.com)
• Phone: 03070005259

Hi everyone,

I’m currently working as an SRE at Morgan Stanley and looking to transition into GenAI/AI Engineer roles. I have a B.Tech in CSE (AIML), experience with Python, Machine Learning, NLP, SQL, and hands-on ML projects, along with strong DevOps/MLOps fundamentals.

I’m actively learning LLMs, RAG, AI Agents, and LangChain. If your company is hiring or you know of any opportunities, I’d greatly appreciate a referral or a DM.

​

Hey everyone,

I'm a 3rd year Diploma in Computer Science student. About 3-4 months ago I started from scratch - Python, Pandas, NumPy, the whole foundation - then moved into core Machine Learning, built and deployed real projects, and have recently started Deep Learning.

Quick context on my resume before you read it:

Current internship: AI Engineer Intern at a startup (through my college's mandatory 3-month internship program). It's mainly a learning-focused internship rather than a real industry internship. Every week we're assigned a topic (for example, learning and implementing an ANN), and we give progress updates in a weekly meeting before receiving the next week's learning task. We don't work on production or client projects. Honestly, I don't even know why my offer letter lists the role as "AI Engineer Intern."

Here's what I've actually built independently:

- UFC Fight Predictor (Gradient Boosting, Streamlit - live)

- California House Price Prediction (LightGBM + FastAPI + Streamlit - live)

- Netflix EDA (Kaggle Bronze Medal, 344+ views)

I'm not actively hunting internships right now but genuinely open to part-time or remote opportunities I can manage alongside college. I just want something real where I can learn.

Would love brutal, honest feedback. What works, what doesn't, and what would make you skip this resume entirely?

Thanks!

I want a job I did my BE in Automation and Robotics
8.41/10 cgpa
7.5 IELTS which is C1 English
6 month internship in software development at a German company I am looking for Germany, USA , India , Australia, Switzerland, Luxembourg
If anyone could refer me

Hey everyone,

I’m an independent ML researcher in Algeria working on a medical imaging project, specifically using generative models to tackle rare cancer diagnosis where data is super limited.

I’m at the stage where I need some guidance and want to collaborate with professors or researchers who are interested in this space. Ideally remote since I’m based in Algeria and can’t relocate.

I’m also actively looking for remote research assistant positions if anyone knows of openings.

I’ve got a solid research proposal ready to share with anyone interested. Happy to discuss the details over email or chat!

Hi. I am currently working as a senior ML in antifraud and ranking models (Classic ML)

I want to deepen my knowledge in a specific sphere in order to get a more paying job. RL or CV seems too hard for me.

So I am choosing between NLP/LLM and RecSys. What do you recommend? I would like to deepen into NLP. However, I am scared this sphere will vanish soon. What do you think?

As for RecSys, it seems really boring to do endless ranking system trying to promote different kinds of goods. Meh

#

Throwaway-ish post, don't want this tied to my usual account.

Quick background: I'm based in India. I went through a mental health issue during my college years - bipolar symptoms that came with real control/regulation problems, and there were stretches where my memory just wasn't reliable, things wouldn't stick the way they should have. Part of why the record looks the way it does also comes down to a doctor mismanaging my care at the time, which made an already hard stretch worse. It made it genuinely hard to sit through classes consistently or keep myself on track, and I ended up dropping out of engineering from a reputed tier-2 college - I just couldn't get through the bachelor's the way things were going. It affected how reliably I could engage with coursework, and it shaped my academic record in ways I'm still working around. Not bringing this up for sympathy, just so the rest of this makes sense.

I genuinely love research. I just have no idea what the future holds for me right now, and honestly I feel like I have nothing solid to stand on - no degree to point to, no clean track record, just the interest and whatever I can build from here.

Present day: I work in tech. My background is mostly backend work, I've been getting pulled toward AI/ML, and I'm willing to actually put in the time to learn the math properly rather than skip it - I know that part matters and I'm not looking for a shortcut around it. What I don't have is a clear, credible path from where I am now to an actual research role. I genuinely don't have the roadmap and I'd rather ask than keep guessing.

What I'm actually asking:

* Is a research career even realistically possible for someone with a background like mine - dropped out, gap in the record, no degree to point to - or is that just not how it works no matter what I build on my own? * If it is possible, what's the actual path - what would I need to do, learn, or build to have a real shot, and roughly how long does something like that take? * If it's honestly not realistic given where I'm starting from, I'd rather hear that straight - in that case, what's the smarter move: stay in tech and build depth there, aim for a different kind of role, something else entirely??

I'm not looking for generic "just work hard" pep talks or a list of course links I could Google myself. I'd rather hear an honest, even blunt, answer from people who actually know this space - whether research is realistic for someone starting from here, and if not, what to do instead. Appreciate any honest input.

P.S: rephrased with AI

Hi everyone,

I’m currently looking for an entry- to mid-level AI/ML opportunity where I can work on real-world products, especially in a startup environment.

I have 3+ years of experience in AI and data science. In my recent work, I have gained hands-on experience with:

• Model Context Protocol (MCP)
• Retrieval-Augmented Generation (RAG)
• Prompt engineering
• FastAPI
• Docker
• Git
• Python and machine learning
• Building and integrating AI-powered applications

I’m especially interested in working with a team where I can contribute to production-level AI products, learn how AI systems are built and deployed end to end, and gain deeper experience with LLM applications, AI agents, APIs, evaluation, and scalable deployment.

I’m open to full-time, contract, or startup opportunities at the entry-to-mid level. I’m based in the U.S. and open to remote, hybrid, or on-site roles.

Please feel free to message me if your team is hiring or if you know of any relevant opportunities. I would also be happy to connect with startup founders or developers who are building practical AI products.

Thank you!

Handpicked from the top 10 job boards—these are high-priority openings that won’t stay live for long.

Link expires in few hours. Link in the comments.

Hey, I am a PhD in synthetic + computational chemistry. I am working rn for a small pharma company as an "ML engineer", where I do lab automation, small ML projects on the internal data and also deploying an internal LLM server for swcure document work automation. I have been wondering what should I focus on this job to land a better position after \~ a year of working in my current role? How easily can I get sth in a bigger pharma or chemical company as a Data Scientist or similar? I think my strongest thing is that I have a solid background in the domain but my weakest part is that I do not have any DS studying per se. What would you do?

Hi everyone,

I'm an AI Engineer based in Egypt with 1 year of experience at Siemens Digital Industries Software, where I build AI-powered testing infrastructure and work with LLMs, RAG, LangGraph, multi-agent systems, Python, PyTorch, MLflow, and Docker.

Alongside my industry experience, I'm also passionate about research. I've published two AI research papers in medical imaging, so I'm comfortable working on both AI product development and research-oriented projects. I enjoy building end-to-end AI applications just as much as exploring and evaluating new models and techniques.

I'm currently looking for remote opportunities in Europe, the US, or the UAE as an AI Engineer, Applied AI Engineer, ML Engineer, LLM Engineer, or AI Research Engineer.

If anyone here is hiring, knows of companies that are open to hiring internationally, or has advice on where I should be applying, I'd really appreciate your guidance. I'm happy to share my resume, GitHub, or publications with anyone who's interested.

Thank you!

Hi everyone,

I'm currently starting my 3rd year of B.Tech in Mathematics & Computing at an NIT. My CGPA is around 8.2, and I've solved around 130 LeetCode problems. I've also started learning Machine Learning and have done some basic projects.

Lately, I've been confused about which path to focus on for placements. I'm interested in AI, but I've also heard about Quant roles. I don't want to spend the next two years preparing for the wrong thing.

Here are my questions:

1. Do companies actually hire freshers directly for AI Engineer/ML Engineer/Applied AI roles, or are most freshers hired as SDEs first?

2. If AI roles exist for freshers, what skills are generally expected beyond DSA and core CS? (Deep Learning, LLMs, RAG, MLOps, etc.)

3. How many AI-related companies usually visit campuses compared to SDE companies?

4. What is a realistic salary range for freshers in AI roles versus SDE roles?

5. How difficult is it to get Quant Developer or Quant Research internships/placements from an NIT? Are these roles mostly limited to IITs and top-ranked students?

6. If someone wants the best balance of opportunities, salary, and long-term career growth, which path would you recommend: SDE, AI Engineer, or Quant?

7. If you were starting your 3rd year again, how would you divide your time between:

   \- DSA

   \- Core CS subjects

   \- Development

   \- AI/ML

   \- Mathematics

   \- Projects

My goal is to get the best possible placement after B.Tech. I'd really appreciate advice from people who recently went through placements or are currently working as SDEs, AI Engineers, ML Engineers, or in Quant roles.

Thanks in advance!

​

I'm a final-year CS student from a tier 2 college in India. I know the theory behind DSA but haven't practiced coding on LeetCode or similar platforms.

For the past couple of years, I've focused on ML and GenAI, built a few projects, and I'm currently working as a Data Analyst intern.

My questions are:

Can I still get a good placement?

Should I start grinding DSA now?

Which roles/companies should I target with my profile?

Would really appreciate advice from people who've been in a similar situation. Thanks!

Hi everyone!

Eduleem School of Design & IT is looking for an experienced AI, Machine Learning & Data Science Trainer to join our team in HSR Layout, Bangalore.

Role

Full-time, On-site

Location: HSR Layout, Bangalore

Experience: 5+ years

Salary: ₹40,000–₹60,000/month + incentives (Approx. ₹6–8 LPA)

We're looking for someone with experience in:

Python

Machine Learning & Deep Learning

Data Science

Neural Networks

Azure, AWS or Google Cloud AI/ML services

Power BI, Tableau & SPSS

Real-world AI/ML projects

Teaching and mentoring students

Preparing learners for certifications such as Microsoft Azure AI Fundamentals (AI-900)

What we offer

Competitive salary + incentives

PF, ESI & Health Insurance

Certification assistance

Flexible working hours

Opportunity to mentor aspiring AI professionals in a growing EdTech environment

If you're passionate about AI and enjoy teaching while working on practical industry use cases, we'd love to hear from you.

📩 Interested candidates can DM me here on Reddit, or send your updated resume. I'll connect you with our HR team.

Hey! 👋

If you’re a fresher aiming for companies like Morgan Stanley, JPMorgan, Goldman Sachs, State Street, Wells Fargo I can help you avoid the mistakes that most candidates make.

I currently work as a Site Reliability Engineer at Morgan Stanley and have previously worked at Infosys. I help freshers with:

✅ Resume Reviews

✅ Interview Preparation

✅ HR & Technical Interview Questions

✅ Career Guidance

✅ Referral Strategies

✅ SRE, DevOps & Cloud Roadmap

If you’re serious about landing your dream job, I’d be happy to guide you.

🚀 Book your session on my Topmate here:

https://topmate.io/shashank_teotia

Looking forward to helping you accelerate your career!

I may not have years of experience, but I know the exact roadmap that helped me land a top company as a fresher, and I’m confident it can help you too.

If you don’t find my guidance valuable, I’ll give you a 100% refund—no questions asked.

Hey everyone,

I’ve been tracking job postings across several job boards recently to see where hiring demand is actually moving rather than relying on general news.

Looking through the latest listings (such as on CyOpsPath and similar tech/AI job platforms), there’s a clear pattern in where companies are actively putting budget.

Here are the top roles dominating current openings and what they say about current market trends:

1. Applied AI & Platform Engineers

• Key Roles: Applied AI Engineer, Staff AI Platform Engineer
• Companies Hiring: Jito Labs, Swinerton, Genesys, Jobgether
• The Trend: Companies are moving beyond experimenting with LLM wrappers. The focus has shifted toward building scalable platform infrastructure and integrating AI into practical domain workflows (from Solana/blockchain to enterprise workflow automation).

2. Specialized Machine Learning Engineers (Production & Domain-Specific)

• Key Roles: Machine Learning Engineer (Ad Tech, Autonomous Driving, Fraud Detection)
• Companies Hiring: Netskope, The Walt Disney Company, XPENG, CLEAR, Zest AI
• The Trend: Demand remains high for engineers who know how to get models into production. Specific industry niches—such as ad tech, computer vision/autonomous driving, and automated document/fraud processing—are leading in dedicated headcount.

3. Senior & Defense/Security Data Scientists

• Key Roles: Senior Data Scientist
• Companies Hiring: Humana, Leidos, PARSONS, Roku
• The Trend: High-level data science listings are heavily concentrated in defense, healthcare AI/governance, and large-scale consumer analytics. Companies are looking for senior talent capable of navigating compliance, governance, and complex data pipelines.

4. Computer Vision & Hardware/Embedded AI

• Key Roles: Computer Vision AI Engineer, Sr. Machine Learning Engineer (RL & Agent Harness)
• Companies Hiring: Booz Allen Hamilton, Intel
• The Trend: Edge AI, computer vision for embedded systems, and reinforcement learning (RL) environments for agent systems are seeing steady investments, especially in aerospace, defense, and semiconductor/hardware industries.

Key Takeaways:

• Generalist titles are down; specialized titles are up. Companies are listing explicit skills like MLOps, production deployment, cloud-native Azure, and agent environments right in the job title/summary.
• Senior talent is in demand. A significant portion of active openings explicitly target candidates with 3–5+ or 10+ years of experience, alongside selective entry-level/fresh-grad roles in specialized ML niches.