TuSimple is dedicated to provide the best autonomous driving solution for commercial trucks.

Our mission is to transform the way people see transportation and make it safer, more reliable, and more efficient. While serving two of the world’s biggest markets, China and The United States. We’re looking for smart and entrepreneurial people to join the world’s leading autonomous driving research and engineering team.
Please note in your resume after your name if you apply for the full-time or Intern

Job Description
We are seeking a talented research engineer with experience in robotics and computer vision.
Join the localization team to design and develop localization and state estimation for
autonomous driving systems. The responsibilities of this role are:
● Design and implement localization algorithms based on vision, GPS, and IMU data.
● Research on topics such as: pose estimation, probabilistic filtering, and multiple view geometry.
● Implement novel technologies as a part of an agile team.

● PhD or MS in Robotics, Computer Science, ECE or a related field.
● At least 2 years of working or research experience (excluding course project) in lidar point cloud processing or computer vision.
● At least one year experience with SLAM (Simultaneous Localization and Mapping).
● Familiar with sensor fusion algorithm.
● Proficiency with C++ or Python.
● A basic understanding of how sensors work.
● Experience in inertial navigation system and pose estimation.
● Experience in probabilistic filtering and nonlinear optimization.

Bonus Points
● Related experience in autonomous driving
● Experience in ROS, PCL, OpenCV
● Experience in deep learning (MXNet preferred)
● Proficiency with Linux
● Strong publication record

● Work with world class AI engineers
● Competitive salary and benefits
● Bonus/options/paid vacations/insurance

● 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.