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# AI Data Annotation Specialist (human)

- **Company:** Neura Robotics GmbH
- **Location:** Metzingen, Germany
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, C++ (Programming Language), Computer Programming, Python (Programming Language), Machine Learning, Tensorflow, Software Engineering, Google Cloud, Data Ingestion, Information Technology, Machine Learning Operations
- **Published:** May 16, 2026
- **Apply:** https://de.indeed.com/viewjob?jk=27330c579be8fcd8

## About the Role

Do you have experience in Python?, * Degree in Computer Science, Data Science, Engineering, or a related field

 * 3+ years of experience in machine learning operations, AI, or software engineering
 * Strong programming skills in Python and C++
 * Solid understanding of AI / machine learning fundamentals and data requirements
 * Experience with data annotation tools or labeling workflows
 * Familiarity with dataset structuring and formatting for ML frameworks (e.g., robotics datasets, multimodal data)
 * Strong attention to detail and a quality-driven mindset
 * Experience with cloud platforms (AWS, GCP, Azure) is a plus

## Description

As an AI Data Annotation Specialist, you will operate at the intersection of data ingestion, processing, and machine learning. Your primary responsibility is to design and maintain scalable workflows for automated data annotation, while ensuring that datasets are properly validated, standardized, and formatted for efficient model training.

You play a critical role in enabling high-quality AI systems by transforming raw data into structured, reliable training datasets.

 * Design, build, and maintain pipelines for automated and semi-automated data annotation
 * Ingest and integrate data from multi modal sources into structured data workflows
 * Apply pre-labeling techniques using existing models to accelerate annotation processes
 * Validate and ensure the quality, consistency, and completeness of annotated datasets
 * Identify and resolve data quality issues, inconsistencies, and biases
 * Transform and standardize datasets into model-ready formats
 * Collaborate closely with ML Engineers to optimize datasets for training and evaluation


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