Machine Learning Engineer - Singapore

Weride in One-north

WeRide (Singapore) is the SEA HQ of Weride. Founded in the silicon valley of US in 2017, 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 (Singapore) 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.


WeRide (Singapore) offers competitive salary and excellent employee benefits. Our office is located in the One-north area, a 5min walk from the one-north MRT station. If interested, please send your resume/CV to alex.mah@weride.ai.

More about WeRide:
Website: https://www.weride.ai/
Youtube: https://www.youtube.com/@WeRideAI
LinkedIn: https://www.linkedin.com/company/werideai
Twitter: https://twitter.com/weride_ai

    • 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 robotic
    • Strong understanding of recent advancements in machine learning research
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