Senior Applied AI Engineer (Computer Vision)
Core
Design and deploy production-grade computer vision systems for perception, understanding, and reasoning over visual data, integrating them into AI platforms and agent-based workflows.
Role type
Senior Applied AI Engineer (Computer Vision)
Builds
End-to-end visual intelligence systems, multimodal pipelines, and agent-based decision-making workflows
Domain
Computer Vision, Deep Learning, Multimodal AI
Deliverable
production ML models
Required skills
Deep learning frameworks (PyTorch/TensorFlow), Object detection, Segmentation, Multi-object tracking, Vision Transformers, CNNs, Multimodal models (CLIP/VLMs), Geometric methods, Real-time optimization, Data pipeline design
Preferred skills
3D vision (NeRF/SLAM), Video understanding, Active learning, Large-scale distributed training
Technologies
PyTorch, TensorFlow, YOLO, DETR, Mask R-CNN, ViT, Swin, DeiT, CLIP, SORT, DeepSORT, ByteTrack, RNNs
Responsibilities
Design and deploy computer vision systems for object detection, segmentation, tracking, and scene understanding; Build and optimize models using CNNs, Vision Transformers, and detection/segmentation architectures; Develop multimodal systems combining vision and language; Implement algorithms for multi-object tracking, feature matching, and temporal modeling; Apply geometric and classical computer vision methods for camera calibration, pose estimation, and 3D reconstruction; Optimize systems for low-latency inference and edge deployment; Design and build data pipelines for annotation, curation, and synthetic data generation; Integrate vision systems into multimodal AI pipelines and agent-based systems
Seniority
Senior, hands-on IC
