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ML / AI Infrastructure Engineering Intern — Summer 2026

San Francisco (Hybrid) · Remote OKInternship$45–60/hr10 weeks, June 1 – August 10, 2026

About the role

Arcline builds AI-powered data tools that help K-12 school districts turn fragmented student data into clear, actionable decisions. We work with superintendents and district leaders across Alabama, California, Kentucky, Texas, Wisconsin, and more — replacing months of manual reporting with instant, AI-driven answers.

We're a small, AI-native team that ships fast and builds with real users. Our interns ship real features to real classrooms.

You'll work on the core intelligence layer that powers Arcline's natural language query engine — the system that lets educators ask questions in plain English and get accurate, cited answers from their district's data.

Day to day

  • Designing and optimizing RAG pipelines using LangChain, LlamaIndex, and vector databases (pgvector, Pinecone)
  • Preprocessing and normalizing messy education data from multiple district sources for use in ML pipelines
  • Evaluating retrieval quality, answer accuracy, and prompt performance across real district datasets
  • Experimenting with fine-tuning and model adaptation techniques to improve performance on education-specific queries
  • Architecting agent workflows that route educator questions to the right data sources
  • Building evaluation harnesses and benchmarks to systematically improve model output
  • Working with the founding engineering team to ship improvements directly to production

Requirements

  • Currently pursuing a B.S./B.A. or M.S. in Computer Science, Machine Learning, Data Science, or a related field
  • Strong foundations in ML — you understand embeddings, retrieval, ranking, and evaluation beyond surface level
  • Proficiency in Python
  • Experience with at least one of: LangChain, LlamaIndex, vector databases, or LLM APIs (OpenAI, Anthropic)
  • Able to commit to a 10-week internship from June 1 to August 10, 2026. Based in San Francisco with remote positions also available. Relocation assistance provided for on-site roles

Bonus qualifications

  • Experience building RAG systems or agent-based workflows in production or side projects
  • Familiarity with evaluation frameworks, prompt optimization, or fine-tuning
  • Coursework or research in NLP, information retrieval, or knowledge graphs
  • Experience with data preprocessing, feature engineering, or working with noisy real-world datasets
  • Experience with Postgres, FastAPI, or data pipeline tools (dagster, dbt)
  • AI-native development habits — you use tools like Cursor, Claude Code, GitHub Copilot, or Codex to ship faster

Compensation

Hourly rate ranges from $45–60/hr. Compensation varies based on role track and experience level.