We’re looking for an experienced Computer Vision Engineer to join our team and help transform the future of logistics and the global trade industry through X-RAY imaging perspective. We're looking for individuals who are driven to tackle state-of-the-art technological obstacles, have a team-player mindset with strong analytical thinking and a drive to build systems that matter. As part of our team, you will contribute to developing AI-driven software that revolutionizes customs control processes, significantly speeding up cargo x-ray inspections, and improving fraud detection.
Job Description
Research, design and development of deep learning models for self-supervised and contrastive learning tasks using SOTA algorithms for X-ray imaging
Hands-on experience working with Large Language Models (LLMs), evaluation, and deployment
Development of fusion algorithms for multiple data sources (visual, textual, and numerical data)
Cross-functional collaboration with software engineers & domain experts
Remote with 1 day in-office
A day in the life
Tackle complex, real-world customs inspection challenges where no “off-the-shelf” solutions exist
Design, develop and improve AI systems that accelerate cargo x-ray inspection and uncover fraudulent trade activities—fusing vision, NLP, and structured data
Research, implement, and evaluate deep learning models for self-supervised learning, contrastive representation learning, and uncertainty quantification
Develop fusion algorithms across multi-modal inputs: X-ray images, scanned documents, textual declarations, and structured numerical data
Work with large-scale international customs datasets and annotated X-ray scans
Contribute high-quality, production-ready code and partner with engineering teams to deploy research outcomes into live operational systems
Make informed technical tradeoffs across model performance, data constraints, scalability, integration requirements, and production readiness
You bring to the table
Track record of working on production-grade computer vision
Advantage: work experience with NLP-based systems
Hands-on expertise with PyTorch and Python's scientific stack (NumPy, Pandas, etc.)
Experience with distributed training techniques and handling large-scale datasets
Strong background in multi-modal AI, including fusion of visual, textual, and numeric data
Solid understanding of uncertainty modeling and quantification in AI systems
Excellent coding practices, with a passion for clean, well-structured, and maintainable code
A strong technical foundation, deep curiosity for your field, and an ownership-oriented mindset. You are a collaborative team player who can independently advance complex technical work, challenge assumptions, bring thoughtful ideas to the table, and apply sound engineering judgment to deliver high-quality solutions
Experience & Education
5+ years of industry experience building and shipping deep learning systems, with a strong focus on computer vision
B.Sc. or M.Sc. in Electrical Engineering or Computer Science, or equivalent STEM field.
Nice to have
Experience with AWS/GCP, Docker & Kubernetes, customs/logistics applications, or multi-view visual reasoning