GPU Model Optimization Engineer

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. 

For more information, please visit: http://www.weride.ai

Job Overview:

As a GPU AI/HPC Expert Engineer, you will provide professional support in the design and implementation of cutting-edge GPU computing to address issues related to deep learning, high-performance computing, and computationally intensive workloads, focusing on optimizing capacity management and allocation within GPU computing clusters.

Locations:

Singapore

Guangzhou, Guangdong, China

Shenzhen, Guangdong, China

Responsibilities:

• Performance Analysis and Optimization:Conduct in-depth analysis of GPU applications to identify and resolve performance bottlenecks, focusing on memory access patterns, thread scheduling, and execution efficiency.
• Algorithm Development: Develop efficient GPU-accelerated algorithms using parallel computing frameworks such as CUDA or DirectX to enhance the processing capabilities of computationally intensive tasks.
• Provide technical guidance and training to the team, sharing best practices and optimization techniques in GPU programming.
• Keep abreast of GPU technology and industry trends, evaluating and integrating new technologies to improve system performance.

Requirements:

• Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field.
• At least 5 years of experience in GPU programming and performance optimization, familiar with CUDA or DirectX development.
• Proficient in C/C++, with in-depth knowledge of computer architecture and parallel computing principles.
• Proficient in using GPU performance analysis and debugging tools, with actual performance optimization achievements.
• Rich experience in performance analysis and tuning of AI/HPC workloads.
• Candidates with practical experience in GPU optimization in fields such as deep learning, computer vision, and scientific computing are preferred.

Plus

• Experience in advanced research or development in the field of High-Performance Computing (HPC) or related areas.
• In-depth understanding of GPU optimization in machine learning frameworks such as TensorFlow or PyTorch.
• Practical experience in deploying and optimizing AI models using Orin and Thor platforms, as well as in developing algorithms related to autonomous driving.
• Practical experience in NVIDIA GPU and CUDA programming.

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