Avride is a rapidly developing company in the autonomous vehicle and delivery robot industry. We develop autonomous vehicle technology from scratch, leveraging the strong technical background of our core team and over seven years of experience in autonomous vehicle development.
We are looking for an experienced software engineer to help us build Avride's Localization and Mapping subsystems. Localization team is responsible for providing exact rover location to all the components of the autonomous rover pipeline like perception, behavior layer and control. We calculate position and orientation of the rover with centimeter and fraction-of-a-degree accuracy, dozens of times per second, and in all conditions.
Our most valuable asset are people, each with many years of experience in robotics, EKF, ICP, SLAM algorithms, distributed data processing, software architecture and machine learning, working together as a motivated, effective and friendly team.
Job Duties:
Develop cloud mapping subsystem with a graph optimization at its core.
Develop the Sensor Fusion Localization subsystem, which combines the measurements of multiple sensors (LiDAR, IMU, GNSS, etc.) to calculate rover position to centimeter precision and orientation to 0.1 deg precision.
Support sister development and operation teams on issues related to localization.
Job Requirements:
Bachelor's degree in Computer Science, Electrical Engineering, Robotics or a related field
3+ years of professional software engineering experience
Strong C++ or Python programming skills
Solid understanding of algorithms, data structures and software design patterns
Solid soft skills - intra- and inter-team collaboration, business-driven development focus, planning and getting-things-done, effective and respectful communication
We prefer:
Experience in robotics. Good knowledge EKF, localization, calibration and point cloud processing algorithms are welcome.
Strong mathematical knowledge and skills, especially in optimization, probability theory and mechanics. Ability to turn ideas into formulas, and formulas into algorithms.
Relevant publications or achievements in information olympiads
Eagerness to track recent advancements of the field and implement best ideas to keep algorithms' performance state-of-the-art and beyond