About Fractics

Fractics builds production-grade Agentic RAG and LLM solutions that power enterprise automation and modern customer experiences. As an intern, you'll work with real datasets, real systems, and real deployments-not toy academic projects. This role is ideal for someone who wants to learn the full lifecycle of building and shipping AI systems. Experience or interest in recommender systems is a strong plus.

What You'll Work On

Designing and improving Agentic RAG pipelines (chunking, embeddings, retrieval, reranking)
Cleaning, structuring, and enriching enterprise data for AI workflows
Reading and implementing cutting-edge AI research
Building LLM workflows, evaluators, and orchestration logic
Working with vector databases like Pinecone, Chroma, and MongoDB Atlas Search
Experimenting with embeddings, transformers, and semantic search
Deploying ML components using FastAPI, Docker, and cloud environments
Running experiments to improve grounding, reduce hallucinations, and optimize latency
Exploring advanced systems such as modern recommender engines integrated with agentic AI

What We're Looking For

Strong interest in Machine Learning, NLP, and LLM applications
Solid Python skills and familiarity with ML/NLP libraries (HuggingFace, Scikit-Learn, PyTorch/TensorFlow, LlamaIndex)
Understanding of embeddings, tokenization, and vector search fundamentals
Exposure to RAG workflows or frameworks like LangChain or LlamaIndex (personal or academic projects count)
Curiosity to learn full-stack ML engineering from experimentation to deployment

Bonus points for:

Experience with FastAPI or backend fundamentals
Knowledge graphs or semantic search
Docker or basic DevOps familiarity
An agentic builder mindset: self-review, iterative improvement, and comfort with tools like GitHub Copilot or Antigravity

What You'll Get

Hands-on experience building production Agentic AI systems for enterprises
Mentorship from engineers across ML, backend, and automation domains
Ownership and the opportunity to contribute directly to live deployments
A fast-paced learning environment designed for growth
Strong career outcomes including potential full-time conversion based on performance

Data Science / ML Engineer Intern