About The Position

At Orca AI, we're on a mission to shape the future of the shipping industry through cutting-edge autonomous ship technology. Our solutions empower teams both on the ship and ashore to make informed decisions that dramatically enhance safety, reduce fuel consumption, improve navigation, and minimize environmental impact.

We’re looking for a hands-on Edge Software Engineer to join our Innovation Team and build the software backbone that connects prototype AI perception to operational deployment. This is a mid-to-senior level role focused on reliability at the edge. You’ll own communication and synchronization across distributed platforms, design robust runtime architectures, and package perception pipelines into production-grade modules built for harsh real-world constraints.

This isn’t a narrow backend job - it’s an opportunity to build the next generation of AI-powered maritime infrastructure from the ground up, with full ownership and impact, alongside the most innovative team in the most advanced company in this space.

What Will You Do?

• Architect and implement containerized edge pipelines (Docker, DeepStream/Triton) for Jetson and x86
• Design and implement the edge comms stack (sync, heartbeat, telemetry)
• Lead cross-functional integration with algorithm, product, and field teams
• Own the end-to-end integration of AI models into embedded systems
• Drive profiling, debugging, and performance tuning in constrained environments
• Support hardware-software integration in both lab and vessel environments
• Contribute to strategic innovation rollouts and project qualifications
  
  

Requirements:

• 4 years of experience in backend engineering with strong systems/architecture exposure - proficiency in Python and C++
• Strong experience with edge inference stacks (Jetson, DeepStream, Triton, Docker, Linux)
• Comfort with embedded systems and real-world hardware constraints (cameras, sensors, etc.)
• Experience building modular, production-grade software
• Strong communication and collaboration abilities
• A “can-do” mindset and a drive to build and ship real systems
  
  

Nice-To-Haves

• Background in robotics, autonomy, or maritime systems
• Exposure to video streaming, real-time monitoring and encoding pipelines
• DevOps/MLOps experience for embedded/containerized environments
  
  

Challenges & Opportunities

• Tackle real-world edge integration with embedded AI systems
• Lead visible, strategic innovation projects with external partners
• Help define the future of autonomy in the maritime world
• Join a high-impact, close-knit team working at the bleeding edge of autonomy and robotics