AI Automation and NLP Engineering Intern

Overview

Support an internal automation platform that turns United Nations meeting media into structured, verified reporting and analytical outputs using local large-language-model inference.

Key Responsibilities

• Author and extend automated tests (unit and mocked-LLM tests), lifting coverage across priority modules and hardening pure functions and data-extraction paths (30%)
• Design and run structured model and prompt evaluations, such as per-language machine-translation selection and speech-recognition error detection, including building the labelled gold sets that make results measurable (25%)
• Build and extend deterministic extraction tooling (pattern and catalog matching, fuzzy-match resolvers) consistent with the project's principle that language models never supply structured identifiers (25%)
• Scaffold new modules and utilities to the house architecture, and improve documentation, refactoring and developer tooling (20%)

Required Experience

Strong Python proficiency, including experience with testing frameworks (pytest) and version control (git), is required. Foundational understanding of natural-language processing and of large-language-model prompting and evaluation is required. Familiarity with running or calling local LLMs (e.g. Ollama, Hugging Face) is an asset. Experience designing evaluation harnesses or working with structured (JSON) model outputs is an asset. Clean, documented and reproducible coding practice is essential.

Qualifications

Be enrolled in, or have completed, a graduate school programme (second university degree or equivalent, or higher) related to computer science, data science, artificial intelligence, machine learning, computational linguistics, software engineering, or related disciplines; or Be enrolled in, or have completed, the final academic year of a first university degree programme (minimum bachelor's level or equivalent) related to computer science, data science, artificial intelligence, machine learning, computational linguistics, software engineering, or related disciplines.

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