Image Annotator (Student Position)

Om jobbet

Why this role matters

We're building world-class on-device image detection. High-quality, consistently labeled data is the foundation that makes our models reliable in the real world. As aStudent Assistant in Image Annotation, you'll create and validate the training and evaluation datasets that power our detection models-directly improving accuracy, robustness, and user trust.

What you'll do

• Annotate images with precision (e.g., bounding boxes and classes/attributes) using our labeling tools and taxonomies.
• Apply clear guidelines and edge-case rules; raise ambiguities and propose refinements to keep label definitions crisp.
• Quality-assure labels through spot checks, inter-annotator agreement checks, and consensus workflows; fix issues at speed without compromising quality.
• Curate datasets for model training/validation/test, corner cases, and rare classes to improve coverage.
• Support model evaluation by producing ground-truth labels for benchmarks and release testing; help compute and sanity-check key metrics.
• Protect data privacy & security by following our data-handling procedures at all times.

What you'll bring

Must-haves

• Strong visual attention to detail and consistency.
• Ability to follow written guidelines and give clear, constructive feedback when something is ambiguous.
• Comfortable with repetitive tasks when needed-while keeping quality high.
• Good written and spoken English. (Swedish is a plus, not a requirement.)
• Availability 10-20 hours per week during the semester; schedule can flex around exams.

What you'll learn here

• How label quality and taxonomy design drive model performance and generalization.
• Practical dataset operations: curation, splitting, QA, and eval set design.
• How on-device/edge detection models are trained, benchmarked, and validated before release.
• Collaboration with AI/ML engineers, product, and QA in a modern MLOps pipeline.

What we offer

• Impact you can see: your labels and insights will measurably improve production model performance.
• A supportive team that values clarity, inclusion, and continuous learning.
• Flexible hours adapted to your studies and exam periods.
• Competitive hourly compensation.