Senior Computer Vision Engineer

About the role

At Digital Place Vision, we are seeking an exceptional Senior Computer Vision Engineer to help stores do planogram compliance. In this role, you will lead the development of end-to-end computer vision algorithm systems that enable retail stores to accurately locate and recognize every SKU (around 5000+ SKUs) on the shelf. From building robust visual recognition pipelines for complex, real-world retail environments to leveraging AI for automated product detection, classification, and localization, you will develop intelligent systems that assess planogram compliance and generate actionable recommendations to improve store execution and operational efficiency.

Key responsibilities:

• Lead the design, development, and deployment of end-to-end computer vision systems for retail shelf analysis and planogram compliance.

• Develop and optimize algorithms for product detection, SKU recognition, localization, and shelf segmentation in complex retail environments.

• Build scalable AI pipelines that accurately identify products and evaluate planogram compliance from images and video captured in stores.

• Design and implement machine learning and deep learning models for SKUs identification and detection.

• Improve model accuracy, inference speed, and robustness across varying lighting conditions, camera angles, shelf layouts, and product packaging.

• Develop data collection, annotation, augmentation, and model evaluation strategies to continuously improve AI performance.

• Analyze model performance using quantitative metrics and conduct error analysis to identify opportunities for improvement.

• Research and evaluate the latest advancements in computer vision and deep learning, and translate them into production-ready solutions.

• Optimize models for edge devices (Android device) and cloud-based inference to ensure scalable and efficient deployment.

• Establish engineering best practices, including code quality, testing, documentation, and MLOps workflows.

Requirements:

• Bachelor's degree or above in Computer Science, Artificial Intelligence, or a related field.

• Solid programming foundation with proficiency in C++ and Python.

• Familiarity with Linux development environments and strong software engineering practices.

• Strong mastery of OpenCV and deep understanding of fundamental to advanced image processing algorithms.

• Proficiency in mainstream deep learning frameworks (e.g., PyTorch or TensorFlow).

• Ability to design custom vision models using PyTorch or TensorFlow if needed.

• Understanding of best practices on model tuning to get best results.

• Familiarity with AI model on edge deployment and inference acceleration tools such as TensorRT, ONNX Runtime, NCNN, or CUDA.

• Experience with MLOps platforms such as Weights & Biases (W&B), MLflow, TensorBoard, or similar tools for experiment tracking, model versioning, and reproducible training workflows.

• Experience implementing production monitoring and logging for AI systems using tools such as Grafana, Prometheus, ELK Stack, OpenTelemetry, or similar observability platforms.

About us

At Digital Place Vision, we’re a team of Visionaries on a mission to light up the retail world with intelligent AI. We're not just about tech; we’re all about seeing the future of retail and making it happen today. From smarter operations to better decisions, we’re here to turn the retail challenges into opportunities for growth.