Senior Software Engineer

Position Summary

​​FlightWave is seeking a Senior Software Engineer to develop embedded and perception software for autonomous aircraft and uncrewed aerial systems. This engineer will own production software across microcontrollers and Linux-based application processors, integrate sensors and perception capabilities, and support systems from architecture and hardware bring-up through flight test.

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​The ideal candidate brings recent VTOL, UAS, or other vehicle embedded-software experience; deep expertise in real-time and embedded Linux systems; Perception stack development and the judgment to diagnose issues spanning software, electronics, sensors, networks, and vehicle behavior. The role partners with electrical, systems, controls, autonomy, test, manufacturing, and flight-operations teams.​

Essential Duties and Responsibilities

Essential functions of a job that are crucial to its purpose and must be performed regularly. They are the fundamental tasks that an employee must be able to carry out, with or without reasonable accommodation, and are central to defining the role’s purpose.

• Design, implement, review, and maintain embedded software in C and C++ for microcontrollers, application processors, and heterogeneous edge-compute platforms used on aircraft.

• Own software features through requirements, architecture, implementation, integration, verification, release, and support during ground and flight testing.

• Integrate cameras, EO or IR payloads, IMUs, GNSS receivers, radar, lidar, and other sensors; establish reliable data paths, time synchronization, health monitoring, and fault handling.

• Develop or integrate perception capabilities such as detection, tracking, localization, visual odometry, mapping, calibration, and multi-sensor fusion according to program needs.

• Optimize CPU, GPU, memory, I/O, startup time, latency, throughput, and power use while preserving deterministic behavior on safety- and mission-critical paths.

• Define secure, stable interfaces across perception, autonomy, flight controls, vehicle management, communications, payloads, and operator-facing applications.

• Diagnose complex problems using target debuggers, traces, logic analyzers, telemetry, recorded sensor data, core dumps, and system logs.

• Build automated unit, integration, software-in-the-loop, hardware-in-the-loop, regression, and performance tests; analyze flight data and drive defects to root cause.

• Develop digital twins and simulators/emulators.

• Contribute to requirements traceability, design reviews, coding standards, configuration management, risk analysis, and evidence needed for program assurance or certification.

• Provide technical leadership through architecture decisions, code reviews, mentoring, planning, and coordination with electrical, systems, controls, autonomy, test, manufacturing, and flight-operations teams.

Required Qualifications – The following qualifications are required for any position:

• Bachelor’s/Master’s degree in Computer Science, Computer Engineering, Electrical Engineering, Robotics, Aerospace Engineering, or a related field, or equivalent practical experience.

• Seven or more years of professional software development experience, including demonstrable hands-on development of embedded software for aircraft, autonomous vehicles, automotive systems, robotics, or similarly complex vehicle platforms.

• Advanced proficiency in embedded C and modern C++, including object lifetime, ownership, concurrency, integer behavior, memory layout, performance, and debugging without relying on undefined behavior.

• Production experience on both microcontrollers and application processors, such as ARM Cortex-M and Cortex-A class devices or comparable architectures.

• Experience with an RTOS and embedded Linux, including multithreading, interprocess communication, scheduling, boot flow, device interfaces, and system-level troubleshooting.

• Experience with common vehicle and board interfaces such as DroneCAN or CAN FD, Ethernet, SPI, I2C, UART, GPIO, MavLINK and related transport or messaging protocols.

• Experience integrating real sensors or perception data on a resource-constrained platform, with attention to calibration, timing, dropped data, vibration, lighting, latency, and environmental failure modes.

• Experience taking software from design and hardware bring-up through bench testing, vehicle integration, and field or flight testing.

• Demonstrated ability to create testable interfaces, automated tests, actionable logs, and measurable performance or reliability criteria.

• Ability to communicate technical decisions clearly, lead reviews, mentor engineers, and work effectively with multidisciplinary teams.

• Ability to meet the on-site, travel, work-authorization, and program-access requirements stated in this posting.

Additional Desired Qualifications – The requirements below are desired knowledge, skills and/or abilities we desire but not required.

• Direct experience with UAV aircraft, UAS platforms, autopilots, flight computers, or flight-control ecosystems such as PX4 or an equivalent platform.

• Experience developing or deploying perception for aerial vehicles, including sensor fusion, visual-inertial odometry, SLAM, GNSS-denied navigation, object detection, tracking, or terrain-relative localization.

• Experience developing vision-based guidance capabilities for autonomous aircraft, including visual target localization, camera-to-vehicle coordinate transforms, line-of-sight or target-state estimation, and interfaces to guidance, navigation, and control software.

• Experience with object detection, recognition or classification, and multi-object tracking in optical (visible-light) and infrared imagery, including moving-camera compensation, track association, occlusion, and changing illumination or thermal contrast.

• Experience fusing optical or infrared observations with radar detections or tracks, including sensor calibration, time synchronization, coordinate-frame alignment, state estimation, and uncertainty-aware association.

• Experience evaluating perception and tracking performance on recorded and flight-test data, including detection and false-alarm rates, track continuity, latency, and failure modes caused by clutter, weather, range, or sensor degradation.

• Experience optimizing computer-vision or machine-learning workloads for embedded or edge deployment using OpenCV, Eigen, CUDA, TensorRT, ONNX Runtime, or comparable technologies.

• Hands-on development with NXP, Qualcomm, or NVIDIA processors and their associated board-support packages, acceleration frameworks, profiling tools, and development kits.