Intern - AI Engineer

About the role

We're hiring an AI Engineering Intern to help us build production AI features for clients and internal products. You'll work across the full AI stack: prompt engineering, retrieval-augmented generation, fine-tuning, evaluation, and deploying ML systems. This is a hands-on role with real shipping deadlines, not a research internship.

What you'll do

• Build LLM-powered features using providers like Anthropic, OpenAI, or open-source models.
• Design and implement RAG pipelines - embeddings, vector stores, retrieval logic, evaluation.
• Prototype agentic workflows and tool-use systems for client use cases.
• Write evaluation harnesses to measure model quality and catch regressions.
• Integrate AI features into existing applications via clean APIs.
• Document patterns and findings so the team can build on your work.

What we're looking for

• Undergraduate in Computer Science, AI/ML, Data Science, or equivalent demonstrated experience.
• Strong Python skills and comfort with one ML/AI library (PyTorch, Hugging Face, LangChain, LlamaIndex, etc.).
• Hands-on experience with at least one LLM API or open-source model - even via side projects.
• Understanding of how transformers, embeddings, and tokenization work at a practical level.
• Comfortable reading research papers and adapting techniques into working code.
• Able to commit to a 3–6 month internship.

Nice to have

• Published projects, blog posts, or open-source contributions involving LLMs or ML.
• Experience with vector databases (Pinecone, Weaviate, pgvector, Qdrant).
• Familiarity with evaluation frameworks (Ragas, Promptfoo, LangSmith).
• Backend experience in Python (FastAPI) or Go.
• Cloud deployment experience (AWS, GCP, Modal, Replicate).

What you'll gain

• Monthly stipend.
• Mentorship from engineers actively shipping AI to production.
• A portfolio of real AI features deployed to enterprise users.
• Clear conversion path to a full-time AI engineering role.