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
