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.