As a Computer Vision Engineer at Ultralytics, you will be at the forefront of developing and refining our world-class, open-source AI models. You will drive the entire lifecycle of our models, from research to real-world deployment. Key responsibilities include:

Developing, training, and optimizing state-of-the-art computer vision models, with a primary focus on the Ultralytics YOLO ecosystem.
Implementing advanced data augmentation and preprocessing techniques to improve model robustness on diverse datasets.
Leading the full lifecycle of model development, from research and training to validation and performance benchmarking.
Mastering model export to various formats such as ONNX, OpenVINO, and TensorRT to support a wide range of hardware.
Working on model deployment strategies, including optimizing models for high-performance inference on both cloud and edge devices.
Contributing to our CI/CD pipelines using GitHub Actions to ensure code quality, reliability, and automated testing.
Collaborating with the team to push the boundaries of what's possible in object detection, segmentation, and other core computer vision tasks.

Your strategic vision and technical expertise will be essential in supporting Ultralytics' mission of delivering top-tier machine learning tools and models like YOLO11 to the community.

Important note here: there are two roles. One for engineering proper and one for R&D.