Working Student: Data Annotation for ML & Computer Vision

UpCircle Technology AG; Zürich; Hybrid; CHF 28,000 - 41,000; Part time

Job summary

UpCircle Technology AG in Zurich is seeking a working student to annotate images for machine learning, helping build high-quality datasets for computer vision tasks in recycling. You will use annotation tools, ensure data consistency and quality, and support integration of annotated data into ML pipelines.

The role is a part-time position for at least one semester, with potential extension. Candidates should have basic Python, be comfortable with Linux, and familiarity with CVAT or Label Studio

Qualifications

• Currently enrolled at a Swiss university in a technical or scientific field.
• Strong attention to detail and a focus on producing high-quality work.
• Strong interest in data, AI, and machine learning applications.
• Basic understanding of Python.
• Comfortable using Linux and handling large volumes of files.
• Minimum commitment: one semester, with option to extend.

Responsibilities

• Label and annotate image data using specialized tools for computer vision tasks (e.g., object detection, segmentation).
• Ensure data quality by using internal data curation tools and validation processes.
• Support the integration of annotated data into our machine learning pipelines.
• Help organize, version, and store datasets efficiently.
• Collaborate closely with ML engineers to understand how your work supports model development.

Skills

Python basics

Attention to detail

Data literacy

Education

Enrolled at a Swiss university (technical/scientific)

Tools

CVAT

Label Studio

Job description

UpCircle Technology AG in Zurich is seeking a working student to annotate images for machine learning, helping build high-quality datasets for computer vision tasks in recycling. You will use annotation tools, ensure data consistency and quality, and support integration of annotated data into ML pipelines.

The role is a part-time position for at least one semester, with potential extension. Candidates should have basic Python, be comfortable with Linux, and familiarity with CVAT or Label Studio