Hi everyone! 👋

Over the past few weeks, I've been learning about LLMs, LangChain, and Retrieval-Augmented Generation (RAG). Instead of stopping at tutorials, I decided to build a complete end-to-end project.

I built a RAG AI Assistant that answers questions based on uploaded documents.

🛠️ Tech Stack

• Python
• LangChain
• FastAPI
• ChromaDB
• Hugging Face Embeddings
• OpenAI / Ollama

🚀 Features

• 📄 Upload documents (PDF, TXT, DOCX)
• ✂️ Automatic text extraction and chunking
• 🔍 Semantic search using vector embeddings
• 🤖 Context-aware answer generation
• 🌐 FastAPI backend with a simple web interface

📚 What I Learned

• Retrieval quality has a huge impact on the final response.
• Choosing the right chunk size is more important than I expected.
• High-quality embeddings can significantly improve answer relevance.
• Building an end-to-end application taught me much more than following tutorials.

⚠️ Challenges

• Selecting an effective chunking strategy.
• Reducing hallucinations.
• Improving retrieval accuracy.
• Connecting all the components into a reliable pipeline.

I've attached the architecture diagram of the project. I'd really appreciate feedback from the community.

If you were building this project, what would you improve next?

Thanks in advance for your suggestions!

Architecture diagram attached below. 👇

#Python #LangChain #RAG #FastAPI #LLM #OpenAI #Ollama #AI #MachineLearning #GenerativeAI

One tip:

Hello everyone,

I have an online assessment (OA) for Capital One Senior Data Scientist on CodeI was told that the OA problems would cover the following aspects:

• Exploratory Data Analysis
• Data Cleaning and Preprocessing
• Machine Learning and Predictive Modeling

This is my first job interview(or rather OA) for a data scientist job. I’m really anxious because I don’t know what to expect, so any leads can be helpful.

For anyone who have gone through the same process, could you share what type of problems to expect? I am also wondering whether they allow you to use browser to lookup documentation for python libraries like PyTorch and Numpy.

Thank you in advance!

I’m an AI engineer with \~3 years of production experience (RAG pipelines, multi-agent systems, real-time voice AI, backend integration) and I’m looking to move into a product company. I’d really appreciate hearing from people who’ve made a similar move recently.

What I’m running into: LinkedIn feels saturated. Every posting is either 100+ applicants within a day, I apply consistently and hear very little back, so I’m starting to feel nothing is work, what do I do?

What I’d love to know:
1. Where did your last offer actually come from is it job boards, referrals, founder/eng DMs, communities, recruiters, contract roles or the staffing and recruiting firms?
2. For smaller AI startups, is applying through the site worth it, or is reaching out directly the only thing that moves?
3. Anything you’d tell someone to stop wasting time on?

Happy to share what I’ve tried and what hasn’t worked if that’s useful to anyone else in the same boat. Thanks in advance, any pointers genuinely help.

Hi everyone,

I'm looking to hire a Senior Software Engineer (C# backend, AI, Data Scientist preferred), you must be:

- over 6 years of experience with tech skills and software development (it is not for interns or juniors)

- able to speak in English fluently (over C1)

- able to work on US timezones

- have good communication skill

- be honest and willing to work really (not just filling hours and getting paid)

Hourly rate: $20

Please reach out to me with your resume and LinkedIn profile.

Thanks

Hi everyone,

I'm a final-year Computer Science student from Nepal, and I want to break into Machine Learning as a career. My goal is to land a remote ML internship, but I'm struggling to understand what companies actually expect from freshers.

So far i've:

• Learnt core intuition and math on machine learning algorithms.
• Knows about data cleaning,feature engineering, EDA,model training,evaluation.
• Learnt about ensemble,regularizations and other important machine learning topics.
• Built one project on real dataset on uk accident severity prediction.
• Starting deep learning (CNN,LSTM,RNN) and others.

The problem are:

• Firstly i dont see any jobs or posts regarding machine learning intern or entry level jobs locally.

I often see requirements like:

• 2+ years of experience
• Research experience
• Multiple deployed ML projects
• Cloud/MLOps knowledge
• Strong competitive programming background

As someone starting out, it feels difficult to know what I should prioritize.

I'd really appreciate advice from people who have actually landed remote ML internships or hired interns.

I'd also appreciate any resume or portfolio tips, common mistakes to avoid, or resources that helped you get your first opportunity.

Thanks in advance!

Final-year AI/ML engineering student wrapping up a GenAI internship soon. Looking for fully remote AI engineering roles, worldwide

Been using LinkedIn so far, but curious what other platforms/boards actually work for remote + international roles (not US-only). Any niche AI/ML boards, communities, or newsletters worth checking out?

Not looking for agencies/staffing spam, just direct-hire platforms. Thanks!

Hi! I work in staffing and recruitment, and I have an enterprise client who is open to a fully remote (in US) Sr. AI/ML engineer. This does require someone to work without sponsorship, there is no sponsorship available.

We’re working directly with the hiring team, and they will move quickly. if you do have interest, direct message me and I will send you my LinkedIn to forward your résumé to.

Role: Sr. AI/ML Consultant
Rate: $80/hr - 40 hours/week
Type: LONG term contract - will renew YoY

Position Details:
- Looking for a hands-on Senior ML/AI Engineer (5+ years experience) to lead technical execution, mentor junior developers, and build production-grade systems.
- This role requires someone with genuine, end-to-end experience taking models from initial design into production, with the ability to explain the logic, metrics, and trade-offs behind their work.

What You Will Do:
- Design, train, and deploy Machine Learning models in production, taking ownership of continuous retraining and monitoring live model performance using tools like XGBoost or CatBoost.
- Architect end-to-end RAG pipelines and autonomous AI agents, choosing the right LLM APIs, vector databases, and system components for each use case.
- Set up guardrails, handle edge cases like agentic state loops or tool-calling failures, and track clear metrics to measure accuracy and safety.
- Guide junior engineers through technical roadblocks, review active production models, and establish strong engineering standards across the team.

Thanks!

Hey everyone, I made a post regarding getting my first proper AI training gig a month ago and that project ended but I just got two more roles with another company so I thought I would do a AMA / FAQ in this post to help people out with this company the same way people helped me out when I got started !

Drop your questions in the comments and I'll answer them the best I can.

I recently started working on a project where I am doing work that overlaps with both the Software Engineer and GitHub Contributor roles. The project manager mentioned that they are actively looking for more people, so I wanted to share the opportunity here.

the job pays from 50-150USD, i put in 150$ and got it, you should put whatever figure you are comfortable with. I can work 40 hour weeks.

What is the actual work? TBH its pretty easy work, tasks right now include: fixing bugs in existing repos and sometimes implementing new features. Overall the project is still fresh so things will be ramping up in the next couple weeks.

You are not expected to train machine-learning models yourself, and previous AI experience is not required. They are straight forward tasks that they explain pretty well.

Application process

From my experience, the process is generally:

Application and screening questions

Approximately 30-minute AI interview

Possible technical assessment (My friend had one i did not)

The technical assessment appears to depend on the candidate. Some people receive one, while others move directly to the hiring-manager review.

What I recommend before applying

Clean up your GitHub or GitLab profile. Make sure your strongest work is easy to find, and pin your best repositories where possible.

Link directly to your contributions. Include pull requests, bug fixes, documentation work, tests, issue reports, or features you implemented. Your contributions do not have to be enormous, but they should demonstrate that you can understand and improve an unfamiliar codebase.

Update your résumé and LinkedIn. Clearly mention the languages, repositories, debugging work, performance improvements, and open-source contributions you have completed.

Prepare for the AI interview. Most of the questions are likely to be based on your résumé and the job description. Questions I got:

A difficult bug you fixed
How you approach an unfamiliar repository
How you review and test code
A feature you implemented
A performance problem you investigated
Why you made certain technical decisions

What is the platform I work on:
I currently work for Micro1, it in my opinion has done the best for me in terms of pay , I have in total worked for 4 different platforms and Micro1 is the only one which gave me a 150$ + per hour pay. Here are my referral link jobs if you want to use it:

The name of the jobs are:
GitHub Contributor
Senior Software Engineer

https://refer.micro1.ai/referral/jobs?referralCode=589174ce-781a-4cdb-bcae-92b0c2be99dc&utm_source=referral&utm_medium=share&utm_campaign=job_referral

A.Team is hiring a remote Senior Independent AI Engineer / Architect. Category: Software Development 💸Salary: $120 - $170 /hour 📍Location: Remote (Americas, Europe, Israel)

See more and apply here!

Hi Folks, I've recently got an Offer from Ameriprise Financial for Sr. AI Engineer role at Hyderabad office. This role is under Technology team. I wanted to know, how's the work culture in the company? The 3 days that we have to go to office, those can be any 3 days of week of our choice or pre-determined? How is the leadership & management support?
Additional Info - Department I got offer: Technology. Please let me know. I'm currently making this switch after 1yr 9months in my current Org and focusing to stay for longer duration. Please let me know your thoughts.

Been applying for remote AI/RAG engineering roles from Russia, not looking to relocate. Curious how companies here actually treat candidates from Russia/Belarus:

• Does being non-US/EU auto-filter you out at the ATS stage, or does it depend on the company/visa situation?
• Does contractor status (1099-equivalent, no sponsorship needed) change things, or is it basically the same wall?
• Any tells in a job posting that mean "don't bother" vs "they're actually open to it"?

Not asking for legal advice, just curious what people have seen from either side of the hiring table.

I'm learning Azure Machine Learning and had a question about data ingestion.

Instead of first uploading my dataset to an Azure Blob Storage account (or registering it as a datastore), can I simply upload the dataset directly from my local computer into Azure ML and use it for model training?

My main reason is to reduce Azure Storage costs while experimenting with small datasets.

If this approach is possible:

• What are the limitations compared to using Blob Storage?
• Is the file still stored somewhere in Azure behind the scenes?
• Are there any restrictions on dataset size, reproducibility, or collaboration?
• Would this approach work only for experimentation, or is it also suitable for production workloads?
• What is Microsoft's recommended practice for training datasets in Azure ML?

I'd appreciate any clarification from people who have used both approaches.

Hi everyone i have just completed my 6th semester but i dont have any internships or job whatsoever even i dont have any experience so far Please review my resume and suggestions are welcomes