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AI Data Annotator

(Data Labeler, Trainings­data Annotator)

Tech & Engineering

Salary

€2.200 - €3.400/mo

Level

Operational

Outlook

prognosis_growing

What does a AI Data Annotator?

(AI Data Annotator) As an AI Data Annotator, you ensure the labeling and annotation of training data needed for machine learning models. You work daily with various data types such as images, texts, audio and video files that you provide with accurate labels and metadata. Using specialized annotation tools like Label Studio, CVAT or Labelbox, you categorize objects, mark relevant parts and add descriptive tags. You work closely with data scientists, machine learning engineers and product teams to ensure that the labeled data meets quality requirements and project specifications for training AI systems.

Required Education

For this position, you need at least an MBO level 3-4 education, preferably in the direction of ICT, data management or a technical study. The subject profile Nature & Technology (N&T) or Economics & Society (E&M) provides a good foundation due to the focus on logical thinking and systematic working. Subjects like mathematics, computer science and English are valuable because you work with international datasets and technical documentation. Practical experience with computers and strong attention to detail can sometimes compensate for formal education.

Required Skills

Career Perspective

You can start as a junior data annotator or trainee at a tech company or AI startup. With experience, you grow into a senior annotator where you manage more complex datasets and guide junior colleagues. Next steps are data quality specialist, annotation team lead or a transition to data analyst or machine learning engineer. With additional training, you can grow into a data scientist or product manager in AI teams.

AI Impact on the job

As an AI Data Annotator, you stand at the foundation of the AI revolution by providing the essential training data that AI systems need to function. New AI tools make your work more efficient through automatic pre-labeling and smart suggestions, allowing you to focus on more complex annotations and quality control. The explosive growth of AI applications creates an ever-increasing demand for high-quality labeled data, which only makes your role more important.

Career Ladder

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