Computer Vision Engineer

We're looking for a Computer Vision Engineer to build visual intelligence features for a product that runs across connected devices and mobile apps.

This is a hands-on engineering role, not a research one: you'll take CV models from training to production, with a strong focus on making them run fast on resource-constrained devices.

What you'll do:

• Design, train, and deploy CV models - object detection, classification, segmentation, visual analysis;
• Optimize models for edge and mobile inference (quantization, pruning, distillation);
• Build data pipelines for image and video processing, including annotation and dataset versioning;
• Set up monitoring and retraining workflows for models in production;
• Work with backend and mobile teams to integrate model outputs into user-facing features.

Requirements:

• 3+ years in applied computer vision or ML with a strong CV focus;
• Solid deep learning background: CNNs, detection and segmentation architectures (YOLO, Faster R-CNN, U-Net), vision transformers;
• Python, PyTorch or TensorFlow, OpenCV;
• Experience deploying and maintaining CV models in production;
• Hands-on with on-device inference: ONNX, TensorRT, TensorFlow Lite, Core ML, or OpenVINO;
• Cloud platforms (GCP, AWS, or Azure) and container-based deployments;
• English: Intermediate or higher.

Nice to have:

• MLOps tools (MLflow, Airflow, Vertex AI);
• Real-time video processing at scale (FFmpeg, GStreamer, Kafka);
• Edge AI or mobile ML experience.