Machine Learning Assistant

About us

Tools for Humanity builds practical, privacy‑minded AI tools that expand economic opportunity and create more inclusive technologies. Our Labelling & Data Collection team develops the high‑quality datasets and tooling that power robust, responsible computer‑vision systems — including biometric and NFC data collection — with a strong focus on data quality, privacy and fairness. We’re based in Munich’s Werksviertel.

Working student (20 hrs/week)

Support dataset curation and annotation for production computer‑vision pipelines: image and metadata labeling (bounding boxes, labels, corrections), quality assurance and consistency checks, dataset cleaning and audit logging, and support for data‑collection workflows and documentation. Optional small scripting tasks (Python) and involvement in tooling/engineering syncs.

Qualifications

Currently enrolled at a university; highly detail‑oriented, reliable and consistent; fast learner and good communicator; comfortable with web apps and spreadsheets. Good command of English (German advantageous). Basic Python and familiarity with databases (MongoDB or Snowflake) or prior annotation experience are a plus. No prior ML experience required — training in privacy and handling biometric/sensitive data provided.