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.
Job DescriptionThe 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.
Key ResponsibilitiesDevelop, maintain, and improve the embedded Linux software stack running on Jetson Orin NX and AAEON edge compute hardware aboard SmartMast units.
Build and integrate ROS2 nodes and packages for multi-sensor orchestration, including EO cameras (Axis), radar, SDR, AIS, GPS, and thermal imagers.
Design and maintain OTA software and firmware update pipelines (AWS IoT Jobs or Mender-based) that reliably deploy to a globally distributed fleet.
Develop sensor driver integrations and calibration routines; ensure co-collection timing and synchronization across heterogeneous sensor modalities.
Optimize AI inference pipelines running on-device (Jetson TensorRT, CUDA), balancing detection quality against power and thermal constraints.
Build and maintain the secure connectivity layer between SmartMast units and the cloud: Starlink backhaul, Peplink networking, local mesh between units.
Design for reliability in denied, degraded, and intermittent connectivity environments—buffering, store-and-forward, graceful reconnection.
Instrument the edge stack with observability tooling; triage and resolve field-reported issues from units deployed at sea.
Collaborate with the Hardware, Cloud Platform, and AI/ML teams to define clear interfaces across the full system stack.
5+ years of embedded Linux or platform software engineering experience on production systems, not just prototype work.
Strong command of C++ and Python; deep familiarity with Linux internals (kernel drivers, systemd, networking stack, file systems).
Hands-on experience with the Yocto Project build framework for creating custom embedded Linux distributions, layers, and recipes.
Hands-on experience with ROS or ROS2 for sensor integration and inter-process communication on robotic or autonomous systems.
Experience with NVIDIA Jetson platforms (Nano, Xavier, Orin) or comparable edge AI hardware; familiarity with TensorRT and CUDA inference optimization.
Solid networking fundamentals: TCP/IP, VLAN configuration, firewall policy (iptables/nftables), and experience with Peplink or similar industrial routers.
Experience building or operating OTA update systems for embedded fleets; understanding of rollback, A/B partitioning, and safe deployment practices.
Ability to read hardware schematics and collaborate closely with electrical/hardware engineers during bringup and integration.
Strong debugging skills across hardware-software boundaries: serial consoles, logic analyzers, packet captures, and field log analysis.
Bonus Points:
Experience with SDR platforms (USRP, RTL-SDR, or similar) and RF signal processing pipelines.
Background in maritime, defense, or other field-deployed, environmentally hardened systems.
Familiarity with AIS protocol decoding, radar data formats, or NMEA message handling.
Experience with mesh networking protocols (802.11s, BATMAN, or custom implementations) for inter-unit communication.
Security experience: secure boot, device attestation, certificate management for field-deployed IoT devices.
Distributed team environment working asynchronously.
Start-up atmosphere with autonomy given to engineers
In office and flexible hours
Open to remote
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