Perception Deployment Engineer (AI)

TL;DR

Perception Deployment Engineer (AI): Responsible for deploying, optimizing, and validating deep learning perception models on vehicle-mounted embedded platforms with an accent on using tools like TensorRT, CUDA, and ONNX Runtime for end-side reasoning acceleration. Focus on system-level engineering work in a Linux Embedded environment, including driver and system configuration collaboration, cross-compilation, and system service debugging.

Location: Beijing, Shanghai, Wuxi, China

Company

hirify.global Inc. is a global company creating stronger, more sustainable communities.

What you will do

• Deploy deep learning perception models on vehicle-mounted embedded platforms.
• Use TensorRT, CUDA, cuDNN, and ONNX Runtime for end-side reasoning acceleration.
• Conduct performance analysis and optimization for latency, throughput, memory usage, and power consumption.
• Perform system-level engineering work in a Linux Embedded environment.
• Collaborate with algorithm, fusion, system, and hardware teams to integrate perception modules into the vehicle system.
• Participate in problem localization and bug fixing during the full-process joint debugging and testing phase.

Requirements

• Bachelor's degree or above in Computer Science, Automation, Electrical Engineering, AI, or related field.
• Proficient in C++ and Python with good engineering code capabilities and debugging habits.
• Experience with LiDAR point cloud, understanding point cloud data characteristics and basic processing flows.
• Familiar with the basic process of deep learning model from training to end-side deployment, with practical experience in embedded platform implementation.
• Good problem-solving skills, able to independently promote problem localization and resolution during system joint debugging.

Nice to have

• Familiar with multithreading parallelism, CUDA acceleration, and other performance optimization methods.
• Basic understanding of perception tasks such as object detection and object segmentation.
• Real project experience with NVIDIA vehicle-end or robot platforms such as Jetson / Orin.
• Understanding of perception runtime frameworks such as ROS2 and DeepStream.
• Long-term engineering capability building awareness, focusing on system stability, maintainability, and scalability.

Culture & Benefits

• Global team environment.
• Focus on creating stronger, more sustainable communities.
• Emphasis on progress and innovation.
• Building a better world together.