Parallel Systems is revolutionizing the freight transportation industry with their innovative autonomous battery-electric rail vehicles. As a Senior Robotics Engineer focusing on Autonomy & Perception, you'll be at the forefront of developing cutting-edge technology that aims to shift freight from trucks to more efficient rail systems.
The role combines hands-on technical work with strategic system design, requiring expertise in robotics, perception systems, and autonomous vehicle technology. You'll be responsible for developing and integrating critical software components that power the autonomous capabilities of their rail vehicles, working with various sensor technologies including LiDAR, radar, and cameras.
The position offers a compelling growth trajectory, starting with immediate hands-on work with the existing autonomy stack and progressing to developing an in-house perception platform. Success in this role means not just technical execution but also strategic thinking about system architecture and team building.
The company offers competitive compensation ($150,000 - $212,000) and the opportunity to work on technology that could significantly impact the future of freight transportation. Located in Los Angeles, you'll be working with a team dedicated to creating cleaner, safer, and more efficient logistics solutions.
This is an ideal role for an experienced robotics engineer who wants to make a meaningful impact on sustainable transportation while working with cutting-edge autonomous technology. The position requires both technical depth in robotics and perception systems, as well as the ability to think strategically about system architecture and team development.
The role offers significant technical ownership and the chance to shape the future of autonomous rail transport. You'll be working on real vehicles and systems, with the opportunity to see your work directly impact the efficiency and safety of freight transportation. The position combines the excitement of a pioneering technology company with the stability of working on infrastructure-scale problems.