Internship - AI Engineer

Deadline :- 7th August 2025

🚀 AI Engineer Intern – Build the Future with LLMs & RAG Systems

📍 Remote | Flexible Hours | Full Time

We’re looking for a technically sharp, fast-learning, and highly curious AI Engineer Intern to join our team. You’ll get hands-on experience building real-world applications using LLMs, embeddings, vector databases, and cutting-edge tools like LangChain, OpenAI, and Hugging Face.

Whether you’re an early-career developer or a self-taught ML enthusiast — if you’re passionate about AI and ready to grow, this opportunity is for you.

🧠 Job Description:

Build and experiment with LLM pipelines and RAG (Retrieval-Augmented Generation) architectures
Integrate vector databases (e.g., Pinecone, Weaviate) with AI APIs for semantic search
Write clean, efficient code in Python or Node.js to support internal tools and demos
Work with embeddings, fine-tuning workflows, and prompt engineering
Collaborate with engineers, product leads, and content teams to bring AI features to life
Continuously learn and apply new techniques in NLP, LLMs, and GenAI development

✅ Qualifications:

Have a background (academic or self-taught) in Computer Science, AI/ML, or Data Engineering
Understand the basics of LLMs, embeddings, tokenization, and vector search
Are comfortable coding in Python or JavaScript/Node.js
Are excited by tools like LangChain, OpenAI, Hugging Face, or Supabase
Have strong problem-solving skills and attention to detail
Can work independently and ask the right questions when needed
Excellent communication — can explain complex systems clearly
Self-starter mindset — organized, proactive, and action-oriented
No ego — hungry to learn, fast to adapt, and open to feedback

🌱 No Formal Experience Required — But You Should:

Have built a few personal or class projects related to AI/ML, GenAI, or backend development
Be comfortable navigating documentation, APIs, and CLI tools
Be motivated to turn ideas into working code, even with limited resources
Be willing to take feedback, iterate quickly, and continuously improve

🎁 What You’ll Gain: