Artificial Intelligence Engineer

🚀 About Code at Random

AI-driven Edtech platform

We’re building the web platform that powers this mission — with a strong focus on learning analytics, community interaction, and AI-driven personalization.

🧠 Role Overview

AI Engineer Intern

data collection → model experimentation → API deployment

⚙️ Key Responsibilities

ML/NLP models

1. Personalized learning recommendations
2. Career & skill path prediction
3. Resume/job matching
4. Sentiment analysis of community discussions

• Work on

  data preprocessing, cleaning, and labeling pipelines

• Implement

  vector databases

  (e.g., Pinecone, ChromaDB, Weaviate) for embeddings
• Integrate

  LLM APIs

  (OpenAI, Anthropic, Gemini, Hugging Face) into backend services
• Experiment with

  RAG (Retrieval-Augmented Generation)

  and context retrieval systems
• Build and expose model endpoints as

  REST APIs

  or via

  FastAPI/Flask

• Collaborate with the full-stack developer to integrate AI into the web frontend
• Track model performance, accuracy, and improvement over time
• Maintain experiments and results documentation on Notion/ClickUp

🧩 Required Technical Skills

🧮 Core Machine Learning & NLP

• Python (NumPy, pandas, scikit-learn)
• NLP libraries:

  Hugging Face Transformers, spaCy, NLTK

• Vector embeddings:

  Sentence Transformers, OpenAI Embeddings

• Model evaluation & fine-tuning (classification, recommendation, similarity)

⚙️ AI Systems & Deployment

• Building APIs with

  FastAPI / Flask

• Familiar with

  Docker

  and containerization
• Knowledge of

  Git / GitHub workflows

• Understanding of

  cloud deployment (Azure / AWS / GCP / Vercel)

🧠 LLM Integration & Prompt Engineering

• Experience using

  OpenAI API, Gemini, Claude, or similar LLMs

• Prompt design and evaluation for dynamic user interactions
• Understanding of

  RAG systems, embeddings, and context retrieval

🗃️ Data & Storage

• Familiarity with

  SQL / NoSQL databases

• Knowledge of

  Vector DBs (Chroma, Pinecone, Weaviate)

• Basic understanding of

  data pipelines

  and preprocessing tools

🌱 Good to Have

• Experience with

  LangChain / LlamaIndex / Haystack

• Understanding of

  recommendation systems

• Exposure to

  knowledge graph / semantic search

  concepts
• Basic experience in

  AI evaluation metrics and MLOps fundamentals

• Familiarity with

  Azure Cognitive Services

  or

  OpenAI on Azure

🧩 Tools You’ll Work With

• 🧠 Hugging Face, OpenAI API, LangChain
• 🧩 FastAPI, Flask, ChromaDB
• 🧮 Python, scikit-learn, PyTorch, pandas
• 💾 GitHub

🎯 What You’ll Learn / Gain

• Build end-to-end

  AI features that ship to real users

• Learn

  RAG and LLM pipeline integration

  in production
• Work on secure, cloud-based dev environments
• Collaborate directly with the founder and engineers
• Get exposure to both

  AI system design and product thinking

🕒 Work Setup

• Weekly goals + progress reviews
• Must have good Wi-Fi connection [minimum 40Mbps]

Email your updated Resume/CV along with your portfolio link (optional) atcodeatrandom@gmail.com