AI Computer Vision Engineer

[About the Team and Our Impact]
We solve real-world retail challenges through deep R&D and practical technology implementation.
Our recent work has earned prominent technical recognition in Taiwan and internationally:

■ Selected for NVIDIA GTC Poster presentations in 2025 and 2026: Our technical achievements were invited for presentation at NVIDIA's annual global technology conference (GTC).
■ Selected for the 2025 IT Matters Awards (AI Selected): Named an AI Application Project of the Year, recognizing the team's technical innovation and real-world commercial impact.
■ Expanding across domestic and international markets: Our in-house AI retail solutions have been deployed in Taiwan and overseas and are moving toward large-scale commercial rollout across multiple countries.

[Role Overview]
We develop smart-retail applications for unmanned stores, smart retail cabinets, and automated vending systems. Join our core R&D team to turn AI technology into tangible business value.

Key Responsibilities:
■ Develop computer vision models for retail use cases, including product recognition, object detection, image classification, out-of-stock detection, misplaced-product detection, and anonymized shopper behavior analysis.
■ Use PyTorch to develop, train, and optimize deep learning models, addressing challenges such as occlusion, glare and reflections, visually similar products, rapid onboarding of new SKUs, and limited labeled data.
■ Build and maintain image data pipelines covering data cleaning, annotation-format conversion, data augmentation, model evaluation, and error analysis of incorrect predictions; continuously improve model accuracy.
■ Deploy models to edge devices or GPU servers, using ONNX, TensorRT, and ONNX Runtime for model conversion and inference acceleration to ensure reliable real-time operation.
■ Handle RTSP video streams and image preprocessing using OpenCV and GStreamer, and integrate these pipelines with backend services, IoT devices, hardware, and in-store systems.
■ Stay current with advances in computer vision and assess the feasibility of applying new models and methods to retail use cases.