Data Operations & Labeling Specialist

You are the crucial bridge between raw field data, external labeling partners, and internal Machine Learning teams. You will own the day-to-day operations of the data labeling lifecycle: curating raw data, preparing annotation batches, managing vendor communication, and rigorously assessing the quality of incoming labels.

What you'll do

• Own the day-to-day data labeling lifecycle: curate raw field data, create annotation batches, and prepare deliveries for external labeling companies.
• Serve as the primary point of contact for external data annotation vendors, clarifying edge cases and providing feedback on labeling guidelines.
• Conduct rigorous Quality Assurance (QA) assessments on incoming label deliveries, track error rates, and create performance reports.
• Support data curation efforts, filtering and selecting the most valuable sensor data (images, video, lidar) for model training.
• Work closely with ML Engineers to understand their data needs, edge cases, and specific Computer Vision requirements.
• Help maintain the data catalog by ensuring incoming datasets are properly tagged and logged.

What you'll need

• Highly organized and detail-oriented: you can manage multiple data batches, vendor deliveries, and QA processes simultaneously without dropping the ball.
• Strong communication skills: you are comfortable coordinating with external vendors and writing clear, unambiguous instructions/guidelines.
• Basic understanding of Computer Vision and Machine Learning concepts (e.g., bounding boxes, segmentation masks, object tracking).
• Comfortable with basic scripting (Python) and data querying (SQL) to automate small tasks or filter data batches.
• Pragmatic problem-solver who enjoys bringing order to chaotic data deliveries.
• Fluent in English.

Nice to have

• Familiarity with annotation formats (like COCO) and ML dataset structures.
• Previous experience using data annotation platforms (CVAT, Labelbox, Scale AI, etc.).
• Exposure to sensor data (RGB, Thermal, LiDAR) or robotics domains.