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

We're looking for a Data Engineer to join our R&D team and take end-to-end ownership of the data pipelines that sit at the core of FleetVision.

Our architecture is uniquely challenging: pipelines run on-premises, aboard vessels at sea, processing continuous, high-volume video streams in real time, in resource-constrained environments, without reliable connectivity. You'll own both the reliability of what exists today and the redesign of what comes next, as we scale the platform and expand into new vessel segments and data sources.

You'll work closely with computer vision, DevOps, and product managers, sitting at the intersection of the on-prem edge and our AWS cloud infrastructure. The problems here are genuinely challenging: low-latency stream processing, ML model integration at the edge, hybrid deployment pipelines, and mission-critical uptime on vessels where downtime isn't an option.

Key Responsibilities

• Design, implement, and optimize data pipelines running in on-prem, vessel-based environments — with a focus on performance, reliability, and real-time throughput.
• Own the full pipeline lifecycle: from maintaining and stabilizing existing systems to driving architectural redesigns and optimizations.
• Develop high-performance pipelines for both stream and batch processing of large-scale video and telemetry data.

Qualifications

• 5+ years of experience designing and operating production data pipelines.
• Strong Python proficiency — this is your primary language day to day.
• Hands-on experience with PostgreSQL or equivalent relational databases.
• Solid understanding of integrating ML models into large-scale production environments.
• Comfort working across hybrid architectures (on-prem + cloud), ideally including AWS.
• Strong communication and collaboration skills.

Advantage

• Familiarity with Rust or C++
• Experience with image or video processing pipelines
• Experience with edge or embedded computing environments