Vraj Mukeshbhai Patel is a Staff Systems Engineer with more than nine years of experience designing autonomous systems and Physical AI solutions for safety-critical applications. His expertise spans autonomous vehicles, humanoid robotics, connected systems, and IoT platforms, with a strong focus on integrating perception, autonomy, and control into scalable real-world systems. Throughout his career, he has developed advanced system architectures that support intelligent mobility and human-machine interaction while meeting stringent safety and performance requirements.
Currently, Vraj serves as a Staff Systems Engineer at Apptronik, where he contributes to the development of next-generation Physical AI for humanoid robots. In this role, he leads autonomy system architecture by integrating perception, SLAM, navigation, locomotion, and teleoperation into unified control frameworks. He also drives sensor architecture decisions, develops system-level safety and reliability frameworks, leverages System Modeling, NVIDIA’s tool chain for simulation-based validation, and collaborates with cross-functional teams spanning AI, controls, hardware, product, and simulation engineering.
Prior to Apptronik, Vraj was a Senior Systems Engineer at May Mobility, where he played a key role in the development of autonomous mobility technologies. He led initiatives involving Autonomous Driving Kit (ADK) sensor architecture, auto-incident detection, in-cabin monitoring, and safety-critical autonomous driving capabilities for commercial driverless ride-sharing services. His responsibilities included systems engineering, requirements management, hazard analysis, verification and validation planning, and ensuring compliance with industry standards such as ISO 26262 and ASPICE while supporting the scalable deployment of autonomous vehicle platforms.
Earlier in his career, Vraj held engineering and product leadership roles at Luxoft, KPIT Technologies, Millennium Software, Skypersonic, and ZF TRW. Across these positions, he contributed to autonomous driving, digital cockpit connectivity, connected vehicle platforms, telematics, cloud-based IoT solutions, UAV systems, ADAS technologies, multi-camera vision systems, V2X applications, and systems engineering for automotive safety. His work consistently involved translating complex customer requirements into system architectures, managing traceability across the product lifecycle, and supporting cross-functional engineering teams in delivering high-quality products.
Vraj possesses extensive expertise in Model-Based Systems Engineering (MBSE), systems architecture, autonomous systems, sensor fusion, computer vision, SLAM, robotics, machine learning, and functional safety. He is proficient with industry-standard tools and platforms including JAMA Connect, NVIDIA Isaac Sim, MATLAB, AWS, Python, DOORS, Git, and Applied Intuition. His technical foundation is complemented by certifications in Six Sigma Green Belt, Senior Product Manager Certification™, Certified SAFe® 5 Release Train Engineer, and ISO 26262 Functional Safety.
Vraj earned a Master's Degree in Industrial Engineering from Wayne State University and a Bachelor's Degree in Mechanical Engineering from Gujarat Technological University. In addition to his professional experience, he has completed several projects involving autonomous driving and computer vision, including lane detection, traffic sign classification, behavioral cloning, advanced lane finding, and sensor fusion using TensorFlow, OpenCV, and related technologies.