Machine Learning Working Student

About the Company

Tools for Humanity (TFH) creates the technology that powers World, a network built to help distinguish real people in an AI-driven internet while protecting privacy. Its core products include the Orb, which confirms a person is real and unique; World ID, which lets people prove that privately; and World App, which brings these capabilities directly to users. Together, they form a human verification layer for the modern internet.

World is already operating at a global scale, with over 17 million people verified across 160 countries and new Orb verifications happening every week. World App ranks among the most widely used wallets worldwide, and developers are adopting World ID to create safer online experiences and communities where real humans can participate and be recognized.

TFH was founded in 2019 and now brings together more than 400 people across hardware, software, AI, cryptography, mobile engineering, and global operations. The team includes talent from companies and institutions such as OpenAI, Tesla, SpaceX, Apple, Google, Stripe, Meta, Coinbase, Palantir, and MIT Media Lab, and the company is supported by investors including a16z, Khosla Ventures, Bain Capital Crypto, Blockchain Capital, Variant, Tiger Global, and Coinbase Ventures.

The organization and its work have been covered by TIME Magazine, Fast Company, Bloomberg, The New York Times, Bankless, and TechCrunch, and its leadership has been recognized in the Time AI 100.

Role Overview

This working-student role is based in Munich (Werksviertel) at Tools For Humanity GmbH. It starts immediately and is set up as a 20-hour-per-week position, with days and times arranged flexibly around lectures and exams. The role is fully in-office.

You will work with a small cross-functional team on real machine-learning production pipelines. The work covers dataset curation, annotation support, quality checks, and practical data-collection tasks. It is designed for someone who is curious about AI and computer vision, wants hands-on experience, and values accuracy and structured work. Prior machine-learning experience is not required, as training will be provided.

Responsibilities

• Annotate images and data using internal tools and dashboards, including bounding boxes, labels, and metadata corrections.
• Check labeled datasets for quality, consistency, and correctness.
• Prepare and clean training datasets through data selection, basic preprocessing, and audit logging.
• Support data-collection workflows by following instructions, checking tasks, and handling participant metadata where needed.
• Document issues, help refine annotation guidelines, and contribute to improvements in tools and workflows, including Streamlit dashboards, MongoDB-backed systems, and internal labeling tools.
• Apply privacy, ethics, and data-handling standards when dealing with sensitive biometric information.
• Optionally assist with small Python scripting tasks or join sprint meetings with product and engineering teams.

Requirements

• You must be currently enrolled at a university, as this position requires a working-student contract.
• You should be very detail-focused and able to maintain consistency even with repetitive work.
• You need to learn quickly and adapt smoothly to new tools and processes.
• You should communicate clearly, ask questions early, document work well, and collaborate effectively.
• You must be comfortable using basic technical tools such as web applications and spreadsheets.
• Strong English skills are required; German is helpful but not essential.
• Preferred qualifications include basic Python knowledge, familiarity with databases such as MongoDB or Snowflake, and prior annotation experience.

Perks and Benefits

• Meaningful practical experience working on real machine-learning systems and datasets with direct impact on production workflows.
• The chance to suggest improvements to processes and annotation guidelines, with guidance and review from experienced teammates.
• A flexible schedule of 20 hours per week, arranged around your study commitments, including lectures, tutorials, and exams.
• A modern office in Munich’s Werksviertel with strong transport connections, refreshments, and catering provided three times daily.
• Pay that is positioned above typical student-role compensation levels.
• Structured training in biometric data privacy, ethical handling practices, and internal tools, along with ongoing learning and mentorship.
• Potential to continue with the team after graduation or complete a thesis project with them.
• This is an on-site role.

Application Instructions

To apply, submit a CV and a short cover letter of one to two paragraphs. Your message should include your earliest possible start date, your weekly availability in hours, and your current degree program plus year of study (matriculation).

Contact Details

Constantin Ingelheim
August-Everding-Straße 25
81671 Munich, Germany
constantin.ingelheim@toolsforhumanity.com

Additional Information

Location: Munich (Werksviertel). Company: Tools For Humanity GmbH. Start: immediately. Employment: working student / Werkstudent, 20 hours per week, with exact days and times flexible to fit lectures and exam periods.