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