/Senior/Staff Robotics Integration Engineer

Senior/Staff Robotics Integration Engineer

Mountain View, CAusvia direct
// Job Type
Full Time
// Salary
USD 170,000 - 250,000/year
// Salary Range
170,000–250,000 USD / year
// Posted
1 month ago

About the Role

What you'll do Lead integration efforts of software and hardware components within the autonomous driving system, ensuring seamless operation and robust performance. Develop, execute, and maintain test plans, cases, and procedures for validating system-level functionality, focusing on critical areas such as perception, navigation, and control. Conduct both in-lab and on-road testing for complex robotic systems, simulating diverse operational scenarios to assess reliability and safety. Utilize simulation environments (e.g., Gazebo, Carla) to create reproducible test scenarios for rapid validation of updates and new features. Troubleshoot and debug issues related to sensor integration, data processing, and software-hardware communication to resolve failures quickly and ensure continuous system improvement. Collaborate with software and hardware teams to optimize system performance and address integration challenges, particularly for sensors like Lidar, radar, cameras, and GPS. Analyze and interpret large volumes of test data to identify trends, optimize system performance, and contribute to root-cause analysis. Automate testing and validation workflows, leveraging tools such as Jenkins or custom Python scripts to improve testing efficiency and reliability. What we're looking for Bachelor’s or Master’s degree in Robotics, Electrical Engineering, Computer Science, or a related field. 4+ years of experience in testing, validation, and integration of autonomous or robotic systems, preferably in an autonomous vehicle or transportation environment. Strong proficiency in ROS/ROS2, C++, and Python, with solid understanding of robotic perception, sensor fusion, and navigation systems. Familiarity with simulation tools (Gazebo, Carla) and hardware-in-the-loop (HIL) testing techniques. Hands-on experience with sensors commonly used in autonomous vehicles, such as Lidar, radar, cameras, and IMUs, including calibration and troubleshooting. Experience in data analysis and performance optimization, with the ability to interpret logs and create reports for system-level improvements. Excellent problem-solving skills, attention to detail, and ability to work effectively in a fast-paced, team-oriented environment.

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