
Ship In is a maritime technology company that offers Fleet Vision™, an AI-powered platform designed to enhance fleet management by improving safety, operational efficiency, and environmental…

Ship In is a maritime technology company that offers Fleet Vision™, an AI-powered platform designed to enhance fleet management by improving safety, operational efficiency, and environmental…
Product: FleetVision — AI computer-vision platform that analyzes onboard CCTV for safety, security, compliance, and performance insights
Scale: Claims support for 1,500+ vessels and 2.5B+ hours of video analyzed
Impact: Reported up to 40% reduction in onboard incidents and ~60-day platform ROI
Recent funding: Raised $24M Series A (Oct 2022); total funding reported ~$40M
Maritime fleet safety, operational efficiency, and compliance using onboard video analytics.
2018
Maritime Transportation
$24,000,000
Reported Series A announced October 19, 2022 with participation from Munich Re Ventures, Hyperplane, and at.inc/
“Backed by strategic investors including Munich Re Ventures and venture investors such as Zeev Ventures and Hyperplane”
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About the role
We are seeking an experienced Senior Platform Engineer, Deployment Automation to join our R&D Systems Engineering team , reporting to the Director of Systems Engineering. This role is instrumental in leading the transformation of our deployment infrastructure by adopting modern automation and continuous delivery practices.
This role will be instrumental in leading deployment activities, improving automation processes, and enhancing our customer onboarding experience. Initially, you will spearhead the selection and deployment of a central system to support our deployment infrastructure.
Key Responsibilities
Automation Development & Tooling: Develop, maintain, and own the suite of Python-based orchestration tools and APIs to streamline the end-to-end product delivery process.
Deployment Architecture (CI/CD/GitOps): Design, implement, and maintain scalable deployment architectures to enable robust one-touch deployment across on-premise solution, and edge systems.
Kubernetes & Containerization: Manage and optimize application deployment within Kubernetes (K8s) clusters to guarantee high availability and resource efficiency.
Cost & Efficiency: Lead technical activities to identify and implement resource efficiency improvements, including hardware validation and benchmarking (GPU/CPU) , and optimizing container resource limits to meet cost reduction targets.
Central System Leadership: Lead the evaluation, selection, and deployment of a new central information management system , ensuring robust integration with our automated deployment systems.
System Lifecycle Management: Define and execute product lifecycle management processes (EoS, EoL, asset retirement, and replacement strategies) for customer assets and hardware.
Qualifications
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