TuSimple is dedicated to providing the best solution for autonomous driving. Our mission is to transform the way people see transportation and make it safer, more reliable, and more efficient.
We’re looking for smart and entrepreneurial people to join the world’s leading scientists and researchers team.
We are seeking talented motion planning engineers with experience in mobile robotics to ensure that our autonomous cars deliver consistent, robust performance. You will work on developing planning architectures and working on motion planning algorithms. The ideal candidate will be an expert in decision making and motion control theory and have experience developing production-quality software.
Design and implement on-road trajectory planning algorithm
Participate in cutting edge research in machine intelligence and machine learning applications
Develop solutions for real world, large scale problems
PhD or MS in related academic program or equivalent practical experience
Experience in planning and/or control systems in mobile robotics
Excellent programming experience in AT LEAST ONE of the following languages:
C, C++, Python
Solid understanding on RRT, lattice-based planners, probabilistic robotics, and/or numerical optimization
Publications in top conferences/journals in a related field or equivalent experences
Demonstrated ability to create real-time motion planning algorithms
Published at top tier journals/conferences in CV/ML
Experience in SLAM, probabilistic filtering, and 3D data
Experience in reinforcement learning
Work with world class AI Engineers
Shape the landscape of autonomous driving
Competitive salary and benefits
Daily breakfast, lunch, and dinner
Full Kitchen with unlimited snacks and fruits
Weekly team happy hour
TuSimple is an Equal Opportunity Employer. This company does not discriminate in employment and personnel practices on the basis of race, sex, age, handicap, religion, national origin or any other basis prohibited by applicable law. Hiring, transferring and promotion practices are performed without regard to the above listed items.