AI Engineer Internship

Job Overview

The Opportunity

We are looking for a high-potential AI Engineer Intern to join our core team for a six-month intensive internship. This is not a "shadowing" role, you will be building production-grade document intelligence systems from day one. Our goal is to transition successful interns into Full-Time AI Engineers based on performance, technical ownership, and contribution to our deployment cycles.

The Mission

You will focus on the intersection of Generative AI and Document Intelligence. Your primary responsibility will be to develop systems that don't just "chat" with data but extract, validate, and automate complex workflows with high precision.

Architectural Design: Exposure to high-level architecture design for robust and scalable AI solutions like RAG, tailored for high precision, recall and accuracy.

Doc Intelligence: Build and optimize end-to-end solutions for automated extraction, layout parsing, and auto filler engines.

Scale with MCP: Implement and manage Model Context Protocol (MCP) servers to extend LLM capabilities.

Fine-Tuning: Conduct experiments with model fine-tuning (LoRa, PEFT) and prompt engineering to reach high accuracy.

Production Code: Write modular, efficient Python code and manage the lifecycle of your models on AWS.

Technical Requirements

Core Fundamentals: A deep understanding of Classical Machine Learning and Deep Learning architectures.

GenAI & LLMs: Theoretical and practical knowledge of Transformers, Attention mechanisms, and LLM orchestration.

Python Expert: Exceptional coding skills in Python (focus on efficiency, readability, and OOP principles).

Version Control: Professional experience with Git/GitHub workflows.

Problem Solving: The ability to break down a vague problem into a scalable technical solution.

Preferred Qualifications (The "Plus" List)

Experience building RAG pipelines or working with Vector Databases (Pinecone, Weaviate, etc.).

Hands-on experience with LangChain, LlamaIndex, or similar orchestration frameworks.

Familiarity with Fine-tuning techniques (PEFT, LoRa) and Doc Intelligence (Extraction/Auto filling).

Basic understanding of AWS services (S3, Lambda, EC2).

What We Offer

Mentorship: Direct collaboration with senior engineers on cutting-edge AI stacks.

Impact: Your code will power real-world solutions used by actual clients.

Growth: A clear, performance-based roadmap to a Full-Time Role within 6 months.