Data Quality Engineer (m/f/d)

The Data Quality Engineer is responsible for developing and maintaining the automated systems that ensure the quality, consistency, and reliability of robotics training data. This role combines software engineering, data analysis, and robotics knowledge to design scalable quality validation pipelines, monitor data collection in real time, and continuously improve automated quality assessment. The engineer works closely with AI researchers, software engineers, and applications team to ensure high-quality data for model training and evaluation.

• Design, implement, and maintain automated data quality validation pipelines for robotics datasets.
• Develop quality metrics, scoring methods, and acceptance criteria that translate validation results into actionable quality decisions.
• Build dashboards, monitoring tools, and alerting systems to detect quality issues during data collection.
• Investigate recurring quality issues by analyzing datasets, collection workflows, and system behavior, identifying root causes and recommending improvements.
• Collaborate with software, robotics, and operations teams to improve data collection processes and automated validation coverage.
• Continuously improve the reliability, accuracy, and scalability of automated quality assessment while minimizing manual review effort.
• Maintain documentation for quality metrics, validation methodologies, and quality tooling.

• Experience with robotics or autonomous systems.
• Familiarity with machine learning datasets and data annotation workflows.
• Experience building dashboards and monitoring systems.
• Knowledge of computer vision, robotic perception, or robot learning.
• Bachelor's degree in Computer Science, Robotics, AI, Data Science, Software Engineering, or a related field.
• Familiarity with Vision-Language-Action (VLA) models, multimodal foundation models, or large-scale AI models used in robotics.
• Understanding of data requirements, evaluation methodologies, and failure modes of modern AI foundation models.
• Strong programming skills in Python and experience developing production-quality software.
• Experience working with data processing pipelines and data analysis.
• Strong analytical and problem-solving skills with the ability to investigate complex quality issues.
• Experience with software testing, validation, or quality engineering.
• Ability to collaborate across software engineering, AI, and operations teams.

• A dynamic high-tech company combined with financial soundness and world-class investors.
• Join an interdisciplinary, international team with 60+ different nationalities in a collaborative work environment.
• Lots of development opportunities in the context of our continued growth.
• Challenging tasks and impactful projects alongside experts that enable professional and personal growth.
• Corporate Benefits Program that covers health, mobility, and learning with 100€ net per month.
• Modern office facilities with a rooftop terrace overlooking Munich, free drinks & fruits, and regular company events contribute to a good working environment.