AI/ML Robotics Engineer

Location: Cupertino, CA (Onsite) – 5 days' work from office

Salary: Market- Based on experience

FTE/Fulltime

Design, build, and integrate

, with the fixtures designed to interface directly with our

. The goal is to stress test products under controlled mechanical conditions while enabling in-situ or sequential CT imaging to inspect internal structural/failure effects. This role requires a hands-on, self-driven engineer who can take a test concept from design through fabrication, CT-system integration, automation, and data analysis — largely independently.

• Design and build custom mechanical fixtures to apply controlled stress (e.g., cyclic loading, vibration, bend/flex, thermal, or compression) to products under test
• Integrate stress-test fixtures with CT scanner hardware — ensuring fixtures fit within scanner bore/stage constraints, are compatible with rotation stages, and don't introduce imaging artifacts (material selection, geometry, X-ray transparency)
• Develop Python software to control test fixtures, synchronize stress cycles with CT scan sequencing, and automate data logging for long-duration/unattended testing
• Apply AI/ML techniques to analyze CT imaging and reliability data — identifying failure onset, crack propagation, wear patterns, and predicting failure modes
• Collaborate closely with CT/imaging, product design, and failure analysis engineering teams to align test design with product risk areas
• Iterate quickly on fixture design based on test results and CT findings
• Document fixture designs, integration procedures, and test results for reproducibility and cross-team use
• Drive projects independently — identifying testing gaps, proposing solutions, and executing with minimal oversight

• Proven experience designing and building custom mechanical/electromechanical test fixtures, ideally for product stress, durability, or reliability testing
• Strong background in robotics and mechatronics : mechanical design, motion control, actuators, sensors, and system integration
• Experience or strong aptitude for integrating hardware fixtures into constrained systems (e.g., adapting designs to fit within existing equipment envelopes/interfaces)

• Proficiency in Python for fixture control, automation, and data analysis
• Practical experience applying AI/ML to engineering, imaging, or test data (anomaly detection, predictive modeling, classification, etc.)
• Self-driven with strong ownership mentality — comfortable defining and executing complex technical projects with ambiguous requirements
• Strong mechanical aptitude — able to work hands-on with hardware (assembly, wiring, troubleshooting, fit-checks)
• Excellent cross-functional communication and documentation skills

• Direct experience with CT (computed tomography) systems — understanding of scan geometry, stage/bore constraints, and material considerations (X-ray attenuation, artifact avoidance) for fixture design
• Background in failure analysis , particularly correlating mechanical stress testing with radiographic/CT imaging findings
• CAD proficiency (e.g., SolidWorks) for fixture design and CT-envelope fit-checks
• Experience in consumer electronics, semiconductor, or precision hardware product testing environments
• Bachelor’s or master’s degree in mechanical engineering, Robotics, Mechatronics, Electrical Engineering, or a related field (or equivalent practical experience)