Capture and curate real-world images of surgical instrument trays using Scalpel’s imaging setup. Perform quality assurance checks on captured images, including resolution, lighting, focus, consistency, and completeness. Validate captured image data to ensure it meets quality standards and AI model requirements. Collaborate with annotation teams to ensure accuracy and consistency in labeled datasets. Maintain accurate and structured metadata for captured and annotated images. Work closely with AI and Computer Vision Engineers to align data collection with model requirements. Identify and report image-quality or data-quality issues and support corrective actions. Follow standardized image-capture protocols and ensure consistency across different locations. Document capture procedures and help ensure reproducibility across multiple sites. Support the continuous improvement of data collection and quality processes. Travel approximately 40–50% regionally to hospitals, surgical facilities, and distributor/warehouse locations. Perform additional duties as assigned in support of AI data quality and engineering initiatives. Qualifications 4-year STEM degree in Engineering, Technology, or a related technical field. Recent graduates and entry-level candidates are welcome. Electro‑mechanical experience or hands‑on technical experience preferred. Background in Mechanical Engineering, Electrical Engineering, Mechatronics, Biomedical Engineering, Robotics, Manufacturing Engineering, or a related field is a plus. Strong attention to detail and ability to identify inconsistencies in images and data. Strong analytical and problem-solving skills. Comfortable working with imaging equipment and technical systems. Ability to work collaboratively with AI/Computer Vision Engineers and data annotation teams. Strong communication and organizational skills. Comfortable with approximately 40–50% regional travel. Ability to work in hospital, warehouse, and other field environments. #J-18808-Ljbffr
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