TL;DR

Computer Vision Engineer (AI): Developing and optimizing deep learning models for computer vision tasks including threat detection, face recognition, and object detection in satellite imagery with an accent on advanced AI and machine learning techniques. Focus on designing neural network architectures, conducting rigorous benchmarking, and integrating state-of-the-art methods for high-impact applications.

Location: Remote within the United States

Company

%hirify_global% is a leading provider of AI-powered decision intelligence solutions for national security, supply chain management, and digital identity, headquartered in McLean, Virginia.

What you will do

Design, implement, and optimize deep learning models for various computer vision tasks
Lead experiments and evaluations in security screening, biometrics, and remote sensing domains
Collaborate with cross-functional teams on data acquisition, annotation, and deployment pipelines
Conduct rigorous model benchmarking and contribute to publications or patents
Stay updated with latest research and integrate state-of-the-art computer vision methods

Requirements

Must have a PhD in Computer Science, Electrical Engineering, or related field focused on computer vision or deep learning
4–5 years post-PhD experience developing and deploying deep learning models for computer vision
Strong expertise in PyTorch or TensorFlow frameworks
Proven experience with neural network architectures for detection, classification, and segmentation
Excellent programming skills in Python; C++ experience is a plus
Strong communication and documentation skills

Nice to have

Experience with oriented bounding boxes and object detection in challenging domains like X-ray or satellite imaging
Background in face recognition algorithms and loss functions such as ArcFace, triplet loss, or contrastive loss
Publications or patents in top-tier computer vision conferences or journals

Culture & Benefits

Work remotely within the United States
Opportunity to work on mission-critical AI solutions impacting national security and commercial innovation
Collaborative and multidisciplinary team environment