Tasks:
- * Build data quality control systems
- * Build end-to-end embodied data pipelines
- * Decompose long-horizon operation tasks
- * Define embodied task frameworks and annotation standards
- * Design prompt engineering and automated annotation solutions
- * Develop automated data validation tools
- * Evaluate data coverage and diversity
- * Monitor data integrity and temporal consistency
- * Optimize data production workflows
Perks/Benefits:
Skills/Tech stack required:
[Data Annotation] [Data evaluation] [Data Pipelines] [Data Processing] [Data Quality] [Data quality assurance] [Data Validation] [Distributed data] [Distributed data processing] [Embodied AI] [Git] [Linux] [Multimodal Data] [Multimodal Data Processing] [NumPy] [Pandas] [Prompt engineering] [Python] [Quality Assurance] [VLA models]
Educational requirements:
[Bachelor's Degree] [Master's Degree] [PhD]
Role(s):
[AI Data Engineer] [Data Engineer] [Embodied AI Data Engineer] [Engineer] [Robotics Data Engineer]