At Orca AI, we build AI-powered vision systems that enhance safety and decision-making for some of the world’s largest vessels. Our platform processes live video streams from multiple onboard cameras to provide real-time situational awareness, detecting and tracking marine objects, even in low visibility and highly congested environments. These systems directly support navigational decisions and help prevent collisions, reduce human error, and improve operational efficiency. Our systems are already deployed across thousands of vessels and have processed hundreds of millions of nautical miles of real-world data, operating in unpredictable and safety-critical conditions. This role sits at the intersection of AI and high-performance systems engineering, focused on solving real-world problems under strict constraints. You will work on systems where performance and reliability are critical and where improvements have a direct, measurable impact on real-world safety. This is a senior, systems-focused role with end-to-end ownership over performance and reliability of production computer vision pipelines. You will define optimization strategies, identify bottlenecks across the system, and drive improvements under real-world constraints. What you’ll do Build and optimize real-time computer vision pipelines running on edge systems processing live maritime video streams (e.g, NVIDIA Jetson, Triton Inference Server) Take models from research and turn them into production-ready, reliable components deployed on vessels Profile and improve end-to-end system performance across: multi-camera video ingestion; preprocessing; inference; postprocessing Identify and resolve bottlenecks across CPU, GPU, memory, and pipeline coordination Make and justify tradeoffs between latency, accuracy, stability, and resource utilization Design and implement robust data and inference pipelines (video -> model -> actionable output for crew) Develop benchmarking and evaluation workflows to
