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Virginia, United States
Onsite
Quartermaster is building the world's most comprehensive maritime intelligence platform. Our SmartMast™ system transforms commercial and civilian vessels into a persistent, distributed sensing network—combining HD video, AI, radar, RF sensing, and AIS to deliver real-time maritime domain awareness at global scale. With 600+ sensors deployed across 25+ countries and more than 400,000 vessels identified outside of AIS, we are setting a new standard for what ocean surveillance and safety can look like. We are a mission-driven, high-velocity team building dual-use technology for defense agencies, coast guards, and commercial maritime operators.
The SmartMast™ is a sophisticated, vessel-mounted edge computing platform running a dense software stack on NVIDIA Jetson hardware in maritime environments: salt air, vibration, intermittent connectivity, and real operational pressure. We need a Senior Embedded Linux / Platform Software Engineer who can own the software that runs at the tip of our spear. You will build and maintain the embedded Linux platform that integrates HD cameras, radar, SDR, AIS receivers, GPS, and thermal sensors into a unified, AI-capable sensing system. You will work at the intersection of hardware bringup, ROS2-based sensor middleware, edge inference pipelines, and the cloud connectivity layer that gets data from the vessel to our analysts in near real time. This is complex, meaningful work, and it ships to sea.
Own and evolve the embedded Linux platform for SmartMast edge devices.
Integrate and maintain sensor interfaces across cameras, radar, SDR, AIS, GPS/GNSS, and thermal systems.
Build and maintain modular middleware and services (including ROS2-based components) for reliable inter-process and inter-sensor communication.
Develop and optimize edge AI inference pipelines for detection, segmentation, and classification under real compute and bandwidth constraints.
Design and improve edge-to-cloud data paths for latency, resilience, and efficient bandwidth usage in constrained maritime networks.
Manage OTA update workflows for fleet-deployed devices, including staged rollout validation and rollback strategies.
Debug production issues from field signals/telemetry, drive root-cause analysis, and ship durable fixes quickly.
Partner closely with hardware, software, and operations teams to bring systems from lab to vessel deployment.
Lead PTZ camera integration decisions spanning lens selection, sensor convergence/alignment, and stabilization tuning, and translate those tradeoffs into measurable improvements in edge ML performance (detection, classification, tracking robustness).
Bachelor's degree in Computer Science, Robotics, Electronics, Electrical Engineering, or a related field.
4+ years of experience in software development for robotics, electronics, and embedded systems.
Over 4 years of proficiency in Python, C++, and shell scripting. Rust is a bonus.
Solid experience with Linux, particularly the Ubuntu flavor.
Experience with robotics frameworks such as ROS/ROS2.
Experience in mobile/embedded platform development, specifically with NVIDIA Jetson, CUDA, and Yocto.
Familiarity with various sensors and hardware, including GPS, IMU, cameras, Radar, and weather sensors, as well as driver development for these devices.
Experience with industrial PTZ network cameras and video streaming technologies.
Hands-on experience with sensor fusion techniques (Kalman/EKF, particle filters, or learned fusion approaches) across radar, EO/IR, and positioning data.
Expertise in developing and deploying AI/ML models for visual tasks, including detection, segmentation, and classification.
Experience with OTA update systems and device fleet management at scale.
Experience working with cloud infrastructure such as AWS, Azure, and GCP, including cloud-native ingestion services.
Solid foundational networking skills, including diagnosing and resolving connectivity issues.
Experience with remote access management protocols like SSH and VNC.
Problem-solving and results-driven mindset.
Flexibility and resilience to thrive in a dynamic environment.
Strong embedded Linux engineering experience in production environments.
Proven sensor integration experience across multiple hardware interfaces and data streams.
Strong software engineering fundamentals and robust development practices at scale (testing, observability, reliability, maintainability).
Professional experience in Python, C++, and shell scripting.
Experience with NVIDIA Jetson or similar edge compute platforms.
Experience working in fast-moving, cross-functional teams with high ownership expectations.
Solid networking fundamentals and practical remote debugging experience.
Authorized to work in the U.S.
Experience with ROS/ROS2 middleware in robotics or autonomy systems.
Experience with industrial/network cameras and video streaming pipelines.
Deep understanding of PTZ camera system design, including lens/FOV tradeoffs, sensor convergence, and mechanical/digital stabilization, and how these parameters impact ML model accuracy, latency, and false positive/negative behavior in real-world conditions.
Hands-on sensor fusion experience (e.g., Kalman/EKF, particle filters, learned fusion) across EO/IR, radar, and positioning data.
Experience with OTA/fleet management for distributed edge devices.
Familiarity with cloud ingestion pipelines (AWS, Azure, or GCP).
Maritime, defense, autonomy, or other mission-critical deployment experience.
Hard technical problems at the intersection of embedded systems, AI, and real-world operations.
Mission impact with direct relevance to maritime safety and security.
Ownership and growth in a fast-growing organization where high-quality work ships quickly.
