Computer Vision Engineer

Role overview Develop computer vision and machine learning systems that interpret people, objects, and activity in the physical world. The work combines deep learning with algorithmic approaches to create products that can adapt across domains without requiring extensive data collection for each deployment. The position is remote within the United States.

Responsibilities - Research, design, and implement detection, segmentation, tracking, pose analysis, and multi-view 3D reconstruction methods. - Fine-tune and deploy language and vision-language models on local GPU infrastructure. - Train deep learning models for deployment on NVIDIA Jetson edge devices. - Prepare, augment, and clean data for model training and evaluation. - Optimize algorithms for real-time or near-real-time operation under compute constraints. - Build validation procedures, collaborate on product integration, and document methods and code.

Requirements - Master’s or Ph.D. in computer science, electrical engineering, or a related field. - Strong grounding in computer vision, machine learning, and deep learning. - At least 2–3 years of C++ and Python experience in a Linux or Unix environment. - At least 1 year of experience training and deploying machine learning models. - Practical knowledge of perception tasks such as detection, tracking, segmentation, or camera calibration. - Effective communication and time management, including in remote and ambiguous work settings.

Nice to have - Exposure to NVIDIA Jetson or other machine learning accelerators. - Interest in applying emerging AI methods in a startup environment.