Innoviz Technologies is a global leader in LiDAR technology. Beyond automotive, Innoviz provides off-the-shelf LiDAR solutions for defense and homeland security, intelligent traffic management, mobility, robotics, and aerial applications. We are looking for a hands-on, highly analytical System Failure Analysis Engineer to lead end-to-end investigations into complex product and manufacturing failures. In this role, you will act as the technical owner of failure investigations—from the initial symptom and data analysis, through laboratory reproduction and multidisciplinary debugging, to root-cause identification, corrective actions, and final closure. The position combines hands-on laboratory work, system-level analysis, production support, and close collaboration with Hardware, Software, Firmware, Mechanical, Quality, NPI, and Manufacturing teams. You will investigate failures in advanced multidisciplinary systems that integrate electronics, optics, mechanics, embedded software, firmware, ASICs, PCBAs, and complex manufacturing and test processes. Responsibilities - Lead end-to-end investigations of system and production failures, from initial symptom to root-cause identification and closure. - Perform hands-on debugging and failure reproduction in laboratory and production environments. - Analyze failures involving hardware, software, firmware, mechanics, optics, and manufacturing processes. - Work closely with R&D, Eng, Quality, and Manufacturing teams to define corrective actions. - Analyze production and test data to identify recurring failure trends and yield issues. - Support field-return, reliability, and manufacturing failure investigations. - Prepare clear technical reports and present investigation findings to relevant stakeholders. - Improve failure-analysis methods, tools, and documentation. - B.Sc. in Electrical Engineering, Electronics, Mechanical Engineering, or a related technical field. - 4+ years of experience in failure analysis, system debugging, electronics laboratory work, or production engineering. - Strong analytical and troubleshooting skills. - Hands-on experience working with complex multidisciplinary systems. - Experience using standard laboratory equipment such as oscilloscopes, power supplies, multimeters, and logic analyzers. - Basic programming or scripting capabilities, preferably in Python. - Strong communication skills in English and Hebrew. - Independent, hands-on, and able to work effectively with multiple engineering teams. - Experience in manufacturing, NPI, or mass-production environments- Advantage. - Experience with optical, electro-mechanical, or embedded systems- Advantage. - Familiarity with Linux, SQL, automated test equipment, or production data analysis- Advantage. - Experience with structured root-cause methodologies such as 8D, DOE, or 5 Whys- Advantage. - Experience leading technical investigations or multidisciplinary task forces- Advantage.