Careers

About ShipIn

ShipIn Systems is redefining how the maritime industry understands, manages, and reduces operational risk. Our AI-powered visual fleet intelligence platform connects onboard video with shore-based teams, turning everyday vessel operations into actionable insight that helps prevent incidents before they escalate.

We work with many of the world’s leading shipowners and operators to bring greater visibility, accountability, and learning into daily operations at sea. The result is safer crews, stronger performance, and smarter decision-making across global fleets.

If you’re drawn to complex, real-world industries and want to build technology that changes behavior and improves safety at scale, join us.

About the Role

As an Applied Computer Vision Researcher, you will develop and improve computer vision models for large-scale maritime CCTV environments, working on real-world video understanding challenges in a domain where production-scale computer vision systems are still relatively uncommon.

You will take part in building new AI capabilities for ShipIn’s FleetVision platform, from early-stage research and experimentation to deployment in production. The role combines applied research with hands-on engineering, and includes working with continuous video streams, challenging environmental conditions, and large-scale operational data.

You’ll work closely with product, data, and engineering teams to turn operational and safety needs into practical, reliable computer vision solutions used by global fleets.

Key Responsibilities

• Lead the development of computer vision and deep learning models for maritime CCTV environments, from research and prototyping through production deployment.
• Design and improve models for continuous video analysis, with a focus on accuracy, robustness, and scalability in real-world conditions.
• Explore and evaluate new approaches, architectures, and technologies to expand the platform’s AI capabilities.
• Work closely with cross-functional teams, including product, data, and operations, to define problems and deliver practical AI solutions.
• Optimize models and inference pipelines for large-scale deployments and resource-constrained environments.
• Stay current with relevant research and apply state-of-the-art methods where they provide clear product and operational value.

Qualifications

• Master's degree in Computer Science, Engineering, or a related technical field, with a relevant thesis in computer vision.
• Minimum of 5 years of hands-on experience in Computer Vision and/or Deep Learning, with a proven track record of taking models from POC to production.
• Experience working with CCTV or video-based datasets is required.
• Experience deploying and optimizing models on edge devices or resource-constrained environments.
• Strong proficiency in Python, with the ability to write clean, maintainable, and scalable code for large, long-lived projects.
• Deep expertise in PyTorch and solid experience with OpenCV and other computer vision libraries.
• Strong mathematical foundation and the ability to read, understand, and critically evaluate research papers and algorithms.