General Software Engineer

Weride in San Jose, CA

$130,000 - $182,000

WeRide is a smart mobility start-up whose mission is to transform mobility with autonomous driving. We are committed to build better transportation experience that’s safe, efficient, affordable and joyful. We have an elite team of entrepreneurs and technologists who share the same passion and pursue continuous excellence in their work.

WeRide.ai is looking for world class coders to work on transforming mobility by solving some of the most challenging AI and robotics problems. You will work with world-class experts in the field of mobility solutions and advance the state of the art in areas such as computer vision, sensor fusion, machine learning, object tracking, and motion planning.
Salary Range: Your base pay is one part of your total compensation package. For this position, the reasonably expected pay range is between $130,000 - $182,000 for the level at which this job has been scoped. Your base pay will depend on several factors, including your experience, qualifications, education, location, and skills. In the event that you are considered for a different level, a higher or lower pay range would apply. This position is also eligible for an annual performance bonus, equity, and a competitive benefits package.

WeRide.ai offers competitive salary depending on the experience. Employee benefits include:
Premium Medical, Dental and Vision Plan (No cost from employees or their families)
Free Daily Breakfast, Lunch and Dinner
Paid vacations and holidays
401K plan


    • BS/MS/PhD degree in Robotics, Computer Science, Electrical Engineering or equivalent practical experience.
    • Experience in data structures and advanced algorithms
    • Experience programming in C++

    • Experience with field robotics and systems design
    • Experience with robust, safety-critical, efficient code.
    • Experience in hands-on robotics research and expertise in one or more of the following: computer vision, LIDAR, object tracking, sensor fusion, perception, machine learning, motion planning, and control
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