We are seeking an Experienced Software Engineer specializing in UAV/USV applications to join our autonomous systems engineering team. This role focuses on developing, implementing, and deploying machine learning solutions that enable autonomous navigation, intelligent perception, mission planning, and decision-making for our UAV/USV platforms. The ideal candidate will combine deep expertise in AI/ML with practical knowledge of robotics, embedded systems, and aerial vehicle operations.

Autonomous Flight & Navigation Systems

• Develop and implement advanced autonomous navigation and sensor-fusion systems for UAV/USV platforms.
• Design and implement data-driven algorithms for real-time path planning, trajectory optimization, and collision avoidance in dynamic environments.
• Implement advanced flight control algorithms leveraging modern model-based and data-driven optimization techniques.
• Develop visual navigation systems that enable UAV/USV to autonomously navigate using visual landmarks, terrain features, and optical flow.
• Create adaptive route optimization algorithms that dynamically adjust flight paths based on mission requirements, weather conditions, obstacles, and no-fly zones.
• Implement waypoint navigation, geo-fencing, and autonomous take-off/landing capabilities with high precision and robustness.
• Design contingency planning systems for emergency maneuvers, fail-safe operations, and autonomous return-to-home functions.

Computer Vision & Perception Systems

• Develop real-time object detection and tracking algorithms for mounted cameras using state-of-the-art visual perception architectures.
• Implement multi-object tracking systems for persistent surveillance of moving targets from aerial and marine perspectives.
• Create semantic segmentation pipelines for terrain classification, zone detection, and environmental analysis from UAV/USV imagery.
• Develop edge detection and optical flow algorithms for obstacle avoidance and safe navigation.
• Optimize computer vision pipelines for real-time performance on embedded and edge hardware with limited computational resources.
• Design multi-sensor fusion architectures integrating data from cameras, LiDAR, IMU, GPS/GNSS, barometers, magnetometers, ultrasonic sensors, etc.

Onboard Computing & Embedded Optimization

• Optimize perception and autonomy workloads for deployment on embedded GPU/accelerator platforms including NVIDIA Jetson (Nano, Xavier, Orin), etc.
• Design efficient data pipelines that minimize latency and maximize throughput for real-time onboard applications.
• Implement power-efficient onboard processing algorithms to extend navigation time and operational endurance.

Payload Integration & Analytics Infrastructure for UAV Systems

• Develop advanced algorithms and analytics pipelines for processing data from diverse payloads including EO/IR cameras, multispectral/hyperspectral sensors, thermal imaging, SAR, sonar, and LiDAR.
• Implement real-time video analytics for automated target recognition, change detection, and anomaly identification.
• Create automated object classification systems for vehicles, vessels, aircraft, buildings, and persons of interest.
• Design geolocation algorithms that compute GPS coordinates of detected objects using telemetry and gimbal data.
• Design and integrate automated recognition pipelines for faces, license plates, and other biometric identifiers adapted for aerial and marine perspectives.

Software Development & System Integration

• Write production-quality software in Python, C++, and ROS/ROS2 for UAV autonomy and perception systems.
• Integrate perception and autonomy modules with control systems (PX4, ArduPilot) and ground control stations.
• Develop APIs and communication protocols for interaction between onboard perception/autonomy components, controllers, payload systems, and mission computers.
• Implement MAVLink protocol integration for telemetry, command, and control data exchange.
• Design modular software architectures that support multiple platforms and mission configurations.

Required Qualifications

• Bachelor's degree in Computer Science, Robotics, Aerospace Engineering, Electrical Engineering, Artificial Intelligence, or related technical field
• 3-5 years of professional experience in AI/ML engineering, robotics software development, or autonomous systems
• Minimum 2 years of hands-on experience developing AI systems for robotics, autonomous vehicles, or similar mobile platforms