Machine Learning Engineer

Weride in San Jose, CA

$150,000 - $220,000

WeRide is a leading, commercial-stage global company that develops autonomous driving technologies from Level 2 to Level 4. It offers an all-rounded product mix of Robotaxi, Robobus, Robosweeper, Robovan and Advanced Driving Solution to provide services. WeRide aims to develop safe and reliable driverless solutions to make our mobility and transportation safer, more affordable, and accessible.

At WeRide, we are dedicated to developing efficient autonomous driving algorithms and evaluation systems to enhance and optimize our autonomous driving technology. As end-to-end models become increasingly mature, we aim to integrate more model techniques and end-to-end capabilities into the autonomous driving domain. This includes tasks such as path planning, scene generation, and scene reconstruction based on large-scale autonomous driving data.
We are seeking experienced algorithm engineers to join our team. This role will focus on the development and optimization of Multi-Agent Planning, 3D Reconstruction, and World Model tasks. The ideal candidate should have extensive experience in algorithm development within the autonomous driving or related fields, along with strong skills in model design, programming, and innovation.
Salary Range: Your base pay is one part of your total compensation package. For this position, the reasonably expected pay range is between $150,000 - $220,000 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
    • Multi-Agent Planning : Design and optimize path planning algorithms for road participants to ensure the creation of realistic and logical movement trajectories. This includes modeling interactions between multiple agents to form rich and diverse complex environments.
    • 3D Reconstruction : Develop and improve 3D reconstruction algorithms to create high-precision 3D environmental models from various sensor data sources.
    • World Model : Create and maintain the vehicle's world model by integrating sensor data to enhance the end-to-end simulation capabilities of autonomous driving.
    • Collaboration : Work closely with cross-functional teams including perception, control, and software engineering to drive project progress.
    • Performance Analysis and Optimization : Conduct performance analysis and optimization of algorithms to ensure high efficiency and reliability in real-world applications.
    • Research and Innovation : Keep abreast of the latest research and technological developments in the field, continuously improving and innovating our systems.
    • Master’s or PhD in Computer Science, Electrical Engineering, Robotics, or a related field.
    • At least 5 years of relevant experience, particularly in autonomous driving, robotics, or related model development fields.
    • Proficiency in programming languages such as C++ and Python, with strong capabilities in algorithm design and implementation.
    • In-depth understanding and practical experience in path planning, 3D reconstruction, and environmental modeling.
    • Familiarity with deep learning, reinforcement learning, and other machine learning techniques, and the ability to apply them to real-world problems.
    • Strong foundation in mathematics and statistics, capable of performing complex algorithm analysis and optimization.
    • Team-oriented with excellent communication skills, able to work effectively with colleagues from diverse backgrounds.
    • Innovative mindset, capable of proactively proposing new solutions and improvements.
    • Publications in top-tier academic conferences or journals in related fields.
    • Experience with frameworks such as ROS, TensorFlow, or PyTorch.
    • Practical project experience or participation in autonomous driving competitions.
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