Scope of the Position:

NuPort Robotics Inc. is currently looking for a strong core motion planning and controls engineer / researcher (full-time, part-time, contract based or internship) to work with us. If anyone is interested or knows any person who would be interested in working with us for deployment of motion planning algorithms on an autonomous vehicle; it would be great to connect. Please directly reach out to hiring@nuport.ai to further discuss.

Qualifications required:

• Masters / PhD in Computer Science, Robotics or related field OR relevant autonomous driving/robotics experience.

• Experience with autonomous systems in one or more of the following areas: planning under uncertainty, decision-making, tracking and prediction, vehicle control systems, perception, localization, estimation, and machine learning

• Experience developing, working with, modifying, and creating advanced algorithms.

• Extensive experience working with autonomous driving systems.

• Large scale probabilistic planning and prediction.

• Advanced vehicle dynamics and control.

• Experience in ROS, C++ and / or python.

• Proficiency with Linux.

• Hands-on experience with autonomous systems.

• Be intellectually curious and have an unending desire to learn.

• Experience of working in a fast-paced environment.

Good to have skills:

• Robust software design for safety-critical systems.

• Multi-modal sensor fusion for localization and dynamic object tracking.

• Naturally enjoy testing of autonomous vehicles out in the wild.

• PhD + industry experience in autonomous driving.

• Some Deep Learning experience and Tensorflow / Pytorch not required but a plus.

Expected tasks:

• Field testing of algorithms in an autonomous vehicle (involves driving, trusting your own software while being driven in the vehicle, etc.)

• Developing Motion Planning algorithms in simulation.

• Deployment and testing of motion planning / controls algorithms on an autonomous vehicle.

• Industrial grade software development adhering to best code / documentation practices.