Kinetic
ADAS Calibration Technician
Phoenix, AZ
Sponsorship not specifiedDetected 25 days ago
Inventory ManagementRoboticsSensors
About the role
- Supporting internal operations and junior technicians, you'll contribute to the continuous improvement and quality of Kinetic's technical and calibration services.
- If you are passionate about making a positive impact in the automotive industry, we want to hear from you!
- If you meet the qualifications for this position and would like to join our team, please submit your resume for consideration.
Responsibilities
- diagnose, troubleshoot, calibrate, and validate ADAS components, including LIDAR, RADAR, camera, and ultrasonic sensors, as well as other ADAS functionality, consistent
- record calibration and diagnostic processes, creating detailed, comprehensive reports that support traceability, quality assurance, and informed decision making
- provide feedback to engineering and product development teams to streamline ADAS calibration processes; improve the performance of Kinetic's application software, AI models, and robotic systems; and support new feature design
- Join the Kinetic team and drive the adoption of ADAS calibration solutions that enhance vehicle safety and reduce administrative friction for customers.
Requirements
- valid driver's license and ability to pass an
- ability to lift objects weighing approximately 50 pounds, use basic hand tools, work outdoors, and operate manual-transmission vehicles
Skills
- The company Kinetic Automation is pioneering effortless modern vehicle repair.
- The company has financial backing from top-tier investors, including Menlo Ventures, Lux Capital, and Construct Capital.
- For more information, visit www.kinetic.auto.
Benefits
- We offer competitive compensation, comprehensive benefits, and regular career-growth opportunities.
Company info
- clearly and professionally communicate with customers, adhering to dispatch schedules to ensure timely task completion
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This listing is sourced directly from Kinetic's careers page and normalized into a canonical job model.