Lead Computer Vision Engineer for Warehouse Robotics

DIGITAL PLACE VISION PTE. LTD.; Singapore; On-site; SGD 90,000 - 130,000; Full time

Job summary

Digital Place Vision Pte. Ltd. in Singapore is seeking an experienced Computer Vision Engineer to lead development of visual algorithms for warehouse shelf scanning, barcode/QR recognition, and SKU counting on robotic platforms.

You will integrate cameras, calibrate sensors, optimize models for edge deployment on platforms like NVIDIA Jetson, and weave vision modules into ROS2, with testing in real retail warehouse environments.

Qualifications

• Bachelor’s degree or above in CS/AI/EE/Robotics.
• Proficiency in C++ and Python; Linux development.
• Strong OpenCV and camera calibration experience.
• Experience with ML/DL frameworks (PyTorch or TensorFlow).
• Familiarity with ROS/ROS2 and image transport.

Responsibilities

• Barcode/QR Code Recognition: Develop and optimize robust detection/decoding algorithms.
• Product Recognition & Precision Counting (ML/AI): Train/deploy models to identify, classify, count SKUs.
• Camera & Hardware Integration: Select/integrate industrial cameras, calibrate intrinsics/extrinsics.
• Edge Deployment: Compress/accelerate models for NVIDIA Jetson; ensure real-time performance.
• ROS2 System Integration: Integrate vision modules into ROS2 using C++/Python.
• Field Testing & Iteration: Test in real warehouse environments; improve recall/accuracy.

Skills

C++

Python

Linux development

ML/DL

Software engineering

Education

Bachelor's degree or higher

Tools

OpenCV

ROS2

TensorRT

ONNX

CUDA

cv_bridge

Job description

Digital Place Vision Pte. Ltd. in Singapore is seeking an experienced Computer Vision Engineer to lead development of visual algorithms for warehouse shelf scanning, barcode/QR recognition, and SKU counting on robotic platforms.

You will integrate cameras, calibrate sensors, optimize models for edge deployment on platforms like NVIDIA Jetson, and weave vision modules into ROS2, with testing in real retail warehouse environments.