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ShipIn Systems is an AI-powered visual fleet intelligence platform transforming maritime safety and operations. The company connects onboard video systems with shore-based teams to provide actionable insights that prevent incidents and improve decision-making across global shipping fleets.
As a Senior Computer Vision Engineer, you will develop and enhance computer vision models for large-scale maritime CCTV environments, tackling real-world video understanding challenges in a domain where production-scale systems remain relatively uncommon. This role bridges applied research and hands-on engineering, combining early-stage experimentation with production deployment.
Key responsibilities include:
- Leading development of computer vision and deep learning models for maritime CCTV, from research through production deployment
- Designing and improving models for continuous video analysis with focus on accuracy, robustness, and scalability in real-world maritime conditions
- Exploring and evaluating new approaches, architectures, and technologies to expand platform capabilities
- Collaborating with product, data, and operations teams to translate operational and safety needs into practical AI solutions
- Optimizing models and inference pipelines for large-scale deployments and resource-constrained edge environments
- Staying current with research and applying state-of-the-art methods where they deliver clear product value
Required qualifications:
- Master's degree in Computer Science, Engineering, or related technical field with relevant computer vision thesis
- Minimum 5 years hands-on experience in Computer Vision and/or Deep Learning with proven track record of taking models from POC to production
- Experience working with CCTV or video-based datasets
- Experience deploying and optimizing models on edge devices or resource-constrained environments
- Strong Python proficiency with ability to write clean, maintainable, scalable code
- Deep expertise in PyTorch and solid experience with OpenCV and other computer vision libraries
- Strong mathematical foundation and ability to read, understand, and critically evaluate research papers
