Computer Vision Engineer

Kooick is building technology that makes complex, large-scale inventory environments transparent, efficient, and reliable. Through our proprietary FusionAI™ platform, we integrate independent data inputs to verify item-level product movement in real time for automated inventory management and unattended commerce.

We are a fast-growing US-based startup expanding our computer vision team in Hong Kong. Please note that this is a fully remote role within HK, and your official employment and payroll will be managed locally through an Employer of Record (EOR). You will receive all standard Hong Kong statutory benefits while working directly with our engineering team. This role is designed for fresh graduates and early-career engineers with 1 to 3 years of experience who are eager to dive into complex, real-world vision problems.

• Collaborate closely with senior engineers to refine vision model architectures on unconventional tasks.
• Transition experimental models from research environments into scalable, production-ready inference engines, ensuring code quality and efficiency.
• Design, build, and maintain robust Python-based MLOps pipelines to automate the training, evaluation, and inference of custom computer vision models.
• Assist in the development of algorithms and models that handle complex visual challenges.

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• Build internal tooling to streamline dataset management, model versioning, and performance monitoring.
• Maintain clean, well-documented codebases and participate in regular technical syncs with the US-based core team to ensure alignment on research goals.

• Bachelor’s degree in Computer Science, Electrical Engineering, Mathematics, or a related field.
• Proficient in Python and PyTorch.
• Solid understanding of core vision tasks, such as object detection and segmentation.
• Hands-on experience tackling custom or real-world datasets that are more complex than standard toy sets.
• Excellent written and spoken English.

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• 1 to 3 years of industry experience.
• Knowledge of containerization and experiment tracking/pipeline orchestration tools to automate machine learning workflows.
• Proven experience building or optimizing algorithms for environments with heavy occlusion, such as retail analytics or crowded public spaces.
• Familiarity with multi-camera calibration techniques, 3D geometry, or spatial understanding algorithms.
• Experience profiling and optimizing model inference for speed and efficiency.
• Previous experience working in a distributed, asynchronous, or international team environment.