AI Data Annotation Specialist (human)

The role

You will design and maintain scalable workflows for automated and human-in-the-loop data annotation. You will transform raw multimodal robot data into structured training datasets for multimodal foundation models.

What you will do

• Design, build, and maintain pipelines for automated, semi-automated, and human-in-the-loop data annotation
• Develop annotation workflows for language-grounded robot learning and Visual Question Answering datasets
• Ingest and integrate multimodal data into structured annotation workflows
• Apply pre-labeling techniques using foundation models to accelerate annotation
• Define and implement data quality checks
• Drive data curation initiatives including dataset balancing and deduplication
• Identify and resolve data quality issues, labeling inconsistencies, and distributional biases

Required qualifications

• Degree in Computer Science, Data Science, Engineering, or a related field
• 4+ years of experience in machine learning operations, AI, or software engineering
• Hands-on experience with data annotation tools and labeling workflows (e.g., Encord, CVAT, Label Studio, or comparable platforms)
• Experience with subtask annotation, ontology/taxonomy design, and VQA-style labelling
• Familiarity with robotics dataset formats and multimodal data structuring (e.g., LeRobot, RLDS, Open X-Embodiment)
• Experience writing annotation guidelines / taxonomies
• Familiarity with VLMs/LLMs for auto-labeling (e.g. open-vocabulary detectors, Gemini/GPT-class models)
• Data engineering basics — comfortable with large-scale/streaming data and formats like ROS bags/MCAP, plus S3-style object storage
• Experience building backend services and tooling (e.g. Node.js/TypeScript, REST APIs) to integrate annotation platforms with internal data infrastructure

Nice to have

• Experience with cloud platforms (AWS, GCP, Azure)
• direct exposure to embodied AI / teleoperation data

About the company

neura-robotics-gmbh