Software Engineer Intern - Mapping & Localization
In-person · Santa Clara, CA, US... more
In-person · Santa Clara, CA, US... more
Job Description
As a Software Engineer Intern in Mapping & Localization at our Santa Clara HQ, you will be at the forefront of developing groundbreaking LiDAR-based algorithms essential for autonomous vehicles. Under the mentorship of Yibo Chen, you will be immersed in a high-energy, innovative environment that challenges the limits of autonomous mobility. This role offers the unique opportunity to turn advanced theoretical concepts into real-world applications, making an impactful contribution to the future of transportation.
Responsibilities:
- LiDAR Algorithm Development: Design, develop, and optimize cutting-edge LiDAR-based localization and mapping algorithms to enhance the autonomy of vehicles.
- Map Support: Refine both online and offline map generation algorithms to improve and sustain localization precision.
- Map Interface Enhancement: Advance the functionality and user experience of the LiDAR map interface, focusing on the robust management of various map versions.
- Sensor Fusion Development: Skillfully merge LiDAR data with other sensory inputs (e.g., GPS, IMU, cameras) to devise integrated, real-time mapping and localization solutions.
- Continue to grow within the team, taking on more complex projects and pushing the boundaries of autonomous vehicle technology.
Required Skills:
- Education: MS or PhD in Computer Science, Electrical Engineering, Robotics, or a related discipline.
- Technical Experience: Proven project involvement in LiDAR-based localization and mapping within autonomous vehicles or robotics.
- Sensor Fusion Expertise: Deep understanding of integrating various sensors like LiDAR, GPS, IMU, and camera data.
- Software Proficiency: Solid experience in C++ and ROS.
- Communication: Exceptional ability to communicate complex technical details effectively across multidisciplinary teams.
- concepts to non-technical team members.
Preferred Skills:
- Experience with Gaussian splatting/NeRF is a plus.
- Experience with deep learning techniques applied to localization and mapping is a plus.