Machine Learning 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 a machine learning engineer for the prediction team. In this impactful role, you will collaborate with a best-in-class team of engineers to tackle hard problems and help advance mobility solutions to improve everyday lives.
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


    • Active learning and Bayesian optimization
    • Anomaly detection
    • Deep networks
    • Distributed/parallel learning algorithms
    • Learning control
    • Predictive modeling

    • PhD in Electrical Engineering, Computer Science/Engineering or a related field.
    • 3 or more years of relevant work or lab experience in Machine Learning, Deep Learning or High-Performance Computing
    • Excellent knowledge of theory and practice of machine learning.
    • Excellent programming skills in some rapid prototyping environment such as MATLAB or Python; C++ and parallel programming (e.g., CUDA) is a plus.
    • Knowledge of common machine learning frameworks.
    • Track record of research excellence or significant product development.
    • Knowledge of application areas such as computer vision or robotics
    • Strong understanding of recent advancements in machine learning research
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