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# Machine Learning Working Student

- **Company:** Tools Gmbh & Co. Kg
- **Location:** München, Germany
- **Contract:** Temporary to permanent
- **Skills:** Artificial Intelligence, Computer Vision, Audit Trail, Spreadsheets, Databases, Python (Programming Language), Machine Learning, MongoDB, Web Applications, Snowflake, Data Management, Machine Learning Operations, Streamlit Framework, Data Selection
- **Published:** June 18, 2026
- **Apply:** https://de.indeed.com/viewjob?jk=030dc0204cc5d15a

## About the Role

* Currently enrolled at a university (required for a working-student contract).
 * Highly detail-oriented and consistent - you care about accuracy even in repetitive tasks.
 * Fast learner and adaptable - you pick up new tools and processes quickly.
 * Strong communicator: asks questions early, documents work clearly, and collaborates well in a team.
 * Comfortable with basic technical tools (web apps, spreadsheets).
 * Good command of English; German is an advantage but not mandatory.
 * Nice to have: basic Python, familiarity with databases (MongoDB or Snowflake) and prior annotation experience.

## Description

Employment: Working student / Werkstudent - 20 hrs/week (exact days/times flexible to fit your lectures and exams)

What to expect

You'll join a small, multidisciplinary team working on real machine-learning production pipelines: dataset curation, annotation tooling, quality control, and hands-on data collection projects. This role is ideal if you're curious about AI and computer vision, want practical experience, and take pride in precision and process. No previous ML experience required - we'll train you.

Your tasks

 * Perform image and data annotation (bounding boxes, labels, metadata corrections) using internal annotation tools and dashboards.
 * Carry out quality assurance and consistency checks on labeled datasets.
 * Help prepare and clean datasets for training ML models (data selection, basic preprocessing, audit logging).
 * Support data-collection workflows and documentation (instructions, task checks, and participant metadata when applicable).
 * Log issues, contribute to annotation guidelines, and help iterate on tooling and workflows (we use
 * Streamlit dashboards, MongoDB backends and in-house labelling tools).
 * Learn and apply privacy, ethics and data-handling best practices when working with sensitive biometric data.
 * Optional: support small scripting tasks (Python) or join product/engineering sprint meetings.


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