🚀 Qareeb is hiring a Computer Vision & Deep Learning Engineer

About the Role

We are looking for a Computer Vision & Deep Learning Engineer to design and optimize AI models for our edge-based computer vision systems. You will work on video inference pipelines, model deployment, and hardware acceleration, ensuring our edge devices deliver real-time performance under constrained environments.

This role requires expertise in deep learning frameworks, computer vision algorithms, and model optimization techniques for deployment on edge AI accelerators.

Responsibilities

Develop and optimize computer vision and deep learning models for real-time video analytics
Build video inference pipelines (frame extraction, pre/post-processing, batching, asynchronous execution)
Prepare and manage video datasets using tools like CVAT, LabelImg, and custom annotation workflows
Train, fine-tune, and evaluate models for object detection, classification, segmentation, and tracking (YOLO, Faster R-CNN, DeepSORT, etc.)
Apply model optimization techniques (quantization, pruning, TensorRT, OpenVINO) for performance on constrained edge devices
Deploy and benchmark models on AI accelerators (NVIDIA Jetson, Intel Movidius, Hailo, Coral TPU, etc.)
Collaborate with the C++ edge team to integrate AI models into production video pipelines
Monitor and improve accuracy, performance, and resource utilization of deployed models
Research and prototype new CV/AI approaches for multimodal (video + audio) analytics and transformer-based architectures

Requirements

4+ years in computer vision and deep learning development
Proficiency with PyTorch, TensorFlow, and ONNX
Hands-on experience with video inference pipelines (frame extraction, pre-processing, batching)
Strong knowledge of model quantization and acceleration (INT8/FP16, TensorRT, OpenVINO)
Experience preparing and annotating video datasets with tools like CVAT, LabelImg
Familiarity with detection/classification/segmentation/tracking models (YOLO, Faster R-CNN, DeepSORT, etc.)
Background in AI hardware acceleration for edge devices (Jetson, Movidius, Hailo, etc.)

Nice to Have

Experience with multimodal AI (video + audio fusion)
Knowledge of transformer-based models for vision and video understanding
Familiarity with real-time constraints in embedded/edge systems
Exposure to MLOps tools for dataset versioning, training pipelines, and deployment automation
Contributions to open-source CV/AI projects

How to Apply

👉 Apply here:
https://qareeb.io/careers/computer-vision-deep-learning-engineer