Lead Edge CV Engineer for Retail Intelligence

Remotedxb; Dubai; On-site; AED 300,000 - 560,000; Full time

Job summary

Panoptyc is advancing retail intelligence by developing cutting-edge computer vision capabilities for real-world store environments. The role focuses on building and deploying robust object detection and vision-language models to drive practical decisions in inventory and product understanding.

We seek engineers with proven production-quality CV experience, expertise in YOLO architectures, and strong Python/PyTorch skills.

Qualifications

• 4+ years of hands-on computer vision engineering with production shipping experience.
• Deep expertise with YOLO and YOLO-E architectures.
• Hands-on experience fine-tuning and deploying open-source VLMs.
• Familiarity with VLA frameworks for real-world perception tasks.
• Mastery of edge deployment using TensorRT, ONNX Runtime, or similar frameworks.
• Strong software engineering fundamentals including clean code and CI/CD for ML.

Responsibilities

• Design, train, and iterate on object detection models for retail environments and inventory tracking.
• Fine-tune and deploy open-source vision-language models for product understanding.
• Build vision-language-action pipelines to translate visual understanding into downstream decisions.
• Optimize models for edge deployment using quantization, pruning, and architectural optimization.
• Build robust data pipelines and annotation workflows for continuous model improvement.
• Mentor engineers and drive technical decisions regarding CV infrastructure.

Skills

Computer vision engineering

Edge deployment

YOLO/YOLO-E

Open-source VLMs

VLA frameworks

PyTorch

CI/CD for ML

Tools

TensorRT

ONNX Runtime

vLLM

llama.cpp

SGLang

MLflow

Weights & Biases

Job description

Panoptyc is advancing retail intelligence by developing cutting-edge computer vision capabilities for real-world store environments. The role focuses on building and deploying robust object detection and vision-language models to drive practical decisions in inventory and product understanding.

We seek engineers with proven production-quality CV experience, expertise in YOLO architectures, and strong Python/PyTorch skills.