Python ,AIML Intern

Job Description – RAG Engineer / AI Engineer (RAG Specialist) –

Experience Level: 0 – 2 years

(Freshers with strong personal projects / Interns with good RAG work / 1–2 years relevant experience)

About the Role

We are looking for highly motivated freshers and early-career candidates who have hands-on experience building at least 1–2 meaningful RAG-based projects using third-party LLMs + their own private/custom data (PDFs, documents, notes, internal knowledge, etc.).

This role is for people who have gone beyond basic tutorials — who have actually faced issues like poor retrieval, hallucinations, bad chunking, irrelevant answers — and tried to fix them.

Must-have Skills & Experience (We will verify these deeply in interviews)

At least 1 strong RAG project (preferably 2) built end-to-end using third-party LLMs (OpenAI, Grok, Gemini, Claude, Llama3 via Groq/Together/Fireworks/etc.)

→ Must have used your own private data (PDFs, docs, Excel, scraped articles, personal notes — not just public Wikipedia or sample datasets)

Solid understanding of the complete RAG pipeline:

Document loading & preprocessing

Chunking strategies

Embeddings generation

Vector storage & retrieval

Generation with context

Prompt Engineering – ability to write clear, effective prompts (you should know difference between zero-shot, few-shot, chain-of-thought, role prompting, structured output, etc.)

Python – comfortable writing clean scripts (basic data handling, functions, lists/dicts, simple classes)

PDF & Document Handling (very important):

Extracted text from normal + somewhat complex PDFs

Used at least one of: PyMuPDF (fitz), pdfplumber, PyPDF2, LlamaParse, Unstructured

Bonus if you handled tables or scanned PDFs to some extent

Basic web framework experience:

Django or FastAPI (at least built 1–2 simple REST APIs)

Database basics:

PostgreSQL (create tables, basic queries, joins) or used simple vector DB like Chroma/FAISS

Frontend basics:

ReactJS – built at least a simple chat-like interface or file upload + display page

Git & basic project documentation (README, folder structure)

Nice to have (will make you stand out – even small experience counts)

Experimented with different chunk sizes / overlap / recursive chunking

Tried multiple embedding models

Used LangChain or LlamaIndex (even basic implementation)

Added simple reranking or query rewriting

Built a small evaluation (manual checking or basic metrics)

Made a chat UI where user can ask questions on uploaded documents

Apply :- [career@hltechindia.com] [9430552744]

Job Type: Full-time

Pay: ₹5,000.00 - ₹10,000.36 per month

Work Location: In person