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Data Collection Operator- AI Robotics, Swing Shift at… | Swiftcruit
RoboForce is an AI robotics company developing Physical AI–powered Robo-Labor for dull, dirty, and dangerous work. Our robots are engineered for demanding outdoor environments, with a focus on real-world deployment and scalability.
We are seeking a Data Collection Operator- AI Robotics (Contractor) to operate and support robotic systems through advanced robotic control interfaces. In this role, you will execute precise manipulation tasks across a variety of real-world workflows, while generating high-quality data to power RoboForce’s AI systems.
This is a hands-on, physical role requiring strong coordination, attention to detail, and sustained focus in a lab/industrial environment.
Responsibilities
Perform data collection tasks such as manipulation of objects, walk pre-determined routes, follow testing guidelines and test protocols at RoboForce facilities and in public environments.
Start/stop recording devices and perform minor equipment and software debugging.
Provide feedback on the performance of the equipment.
Analyze and report on data collected during shift.
Upload data collected and write daily reports detailing observations and issues.
Maintain equipment in safe working condition, prioritize safety protocols, and communicate with leadership promptly.
Requirements
Associate’s or Bachelor’s degree (or equivalent experience).
Familiar with using teleop tools like UMI style, GELLO style, VR-Based Systems, etc.
Strong attention to detail and manual dexterity.
Ability to follow detailed instructions and work independently with minimal supervision.
Clear written communication and a collaborative attitude.
Basic proficiency with software for data upload and reporting.
Ability to perform technical troubleshooting on equipment and willingness to learn new technologies quickly.
Bonus Qualifications
Experience with robotic systems, teleoperation, or related fields.
Basic working knowledge and familiarity with computer software interfaces and tools (e.g., the command line, bash, linux OS).
Hands-on experience annotating video (boxes/masks/keypoints, action labels, ID tracking).
Proficiency with annotation tools; comfort with pre-annotation/autolabel review and correction.
Knowledge of common annotation formats (e.g., COCO, YOLO, MOT/KITTI) and basic video concepts (frame rate, codecs).
