Minimum Requirements: Master's degree in Computer Engineering, Mechanical Engineering, Robotics, or related software engineering technical field and 1 year of experience in an occupation related to autonomy robotic algorithm software development. Must have experience with each of the following: Camera Geometry (intrinsic/extrinsic models), sensor alignment, and coordinate frame transformations (e.g., SE(3), SO(3)); Python and C++, leveraging libraries like OpenCV, SciPy, and Eigen (or other advanced linear algebra libraries) for robust real-time and offline sensor calibration, as well as simulation; ROS/ROS 2 or equivalent robotics middleware (e.g., DDS) for data logging, replaying bags, message parsing, and real-time debugging of sensor streams; multi-sensor fusion and calibration involving key modalities: Lidar, Camera, IMU, and GNSS, specifically in the context of robotics, ADAS, or autonomous vehicles; modern development tools (Docker, Bazel or similar build systems like CMake, and Git) to develop reproducible, containerized calibration workflows integrated into CI/CD/CT (Continuous Testing) pipelines; and robotic systems, working within a Linux/POSIX development environment, and utilizing bash/zsh and command-line tools for scripting, debugging, and system management.
Alternative Requirements: Bachelor's degree in Computer Engineering, Mechanical Engineering, Robotics, or related software engineering technical field and 5 years of experience in an occupation related to autonomy robotic algorithm software development. Must have experience with each of the following: Camera Geometry (intrinsic/extrinsic models), sensor alignment, and coordinate frame transformations (e.g., SE(3), SO(3)); Python and C++, leveraging libraries like OpenCV, SciPy, and Eigen (or other advanced linear algebra libraries) for robust real-time and offline sensor calibration, as well as simulation; ROS/ROS 2 or equivalent robotics middleware (e.g., DDS) for data logging, replaying bags, message parsing, and real-time debugging of sensor streams; multi-sensor fusion and calibration involving key modalities: Lidar, Camera, IMU, and GNSS, specifically in the context of robotics, ADAS, or autonomous vehicles; modern development tools (Docker, Bazel or similar build systems like CMake, and Git) to develop reproducible, containerized calibration workflows integrated into CI/CD/CT (Continuous Testing) pipelines; and robotic systems, working within a Linux/POSIX development environment, and utilizing bash/zsh and command-line tools for scripting, debugging, and system management.
