Robotics Perception and Edge AI Engineer

### About the Role CDSPACE is looking for a Robotics Perception and Edge AI Engineer to develop real-time perception and intelligent navigation capabilities for UAV and robotic platforms. You will build computer-vision and sensor-processing pipelines, integrate perception systems with ROS/ROS2, and deploy optimized AI models on edge-computing platforms. The role spans algorithm development, sensor integration, simulation, onboard deployment, bench testing, and flight validation. ### What You’ll Do **Robotics Perception** - Develop perception algorithms for object detection, tracking, classification, localization, and scene understanding. - Build real-time image-processing pipelines using OpenCV and GStreamer. - Develop perception capabilities using monocular, stereo, thermal, depth, and other camera systems. - Integrate data from cameras, IMUs, LiDAR, GPS/GNSS, optical-flow sensors, and other UAV payloads. - Support sensor calibration, synchronization, coordinate transformations, and timestamp alignment. - Improve perception performance across changing lighting, motion, altitude, weather, and operating conditions. **Computer Vision and Machine Learning** - Develop, train, evaluate, and improve computer-vision and deep-learning models. - Prepare datasets and define data-collection, annotation, cleaning, and augmentation workflows. - Select model architectures based on accuracy, latency, memory, power, and hardware constraints. - Define evaluation metrics and conduct structured model-performance analysis. - Investigate model failures, dataset limitations, false detections, and edge cases. - Maintain reproducible training, validation, and experiment-tracking workflows. **Edge AI Deployment** - Deploy AI models on NVIDIA Jetson, Raspberry Pi, and other edge-computing platforms. - Optimize models for real-time inference using quantization, pruning, hardware acceleration, and other optimization techniques. - Convert and deploy models using ONNX, TensorRT, or similar inference frameworks. - Profile CPU, GPU, memory, power consumption, throughput, and end-to-end latency. - Integrate inference pipelines with cameras, sensors, communication systems, and flight software. - Develop reliable startup, monitoring, logging, recovery, and health-check mechanisms for onboard AI applications. **ROS and Robotics Integration** - Integrate sensors and perception pipelines with onboard computing platforms using ROS/ROS2. - Develop ROS/ROS2 nodes, services, topics, actions, and launch configurations. - Build and test robotic applications using Gazebo or similar simulation environments. - Integrate perception outputs with guidance, navigation, control, and mission-planning systems. - Develop interfaces between onboard computers, flight controllers, payloads, and ground-control systems. - Diagnose issues across sensors, middleware, networks, embedded software, and onboard computers. **UAV and Autonomous Systems** - Develop perception and navigation capabilities for multirotor and fixed-wing UAV platforms. - Support obstacle detection, target tracking, visual navigation, inspection, and autonomous mission workflows. - Integrate onboard perception applications with PX4, ArduPilot, or similar flight stacks. - Support communication with flight controllers using MAVLink. - Work with QGroundControl, Mission Planner, and related UAV tools. - Collaborate with avionics, embedded software, controls, hardware, and flight-test teams. **Testing and Validation** - Conduct software-in-the-loop and hardware-in-the-loop simulations. - Develop test datasets, test scenarios, and acceptance criteria for perception systems. - Perform bench testing, field testing, and flight trials. - Evaluate system performance under representative operating and environmental conditions. - Diagnose sensor, communication, model, software, and system-level issues. - Perform root-cause analysis and implement corrective actions. - Maintain testing procedures, integration records, model documentation, and validation reports. **Application and Interface Development** - Develop supporting applications, visualization tools, and operator interfaces. - Build tools for model configuration, telemetry monitoring, data recording, playback, and analysis. - Support Qt-based software development when required. - Implement clear logs, diagnostics, and system-health reporting. - Maintain modular, testable, and documented software. ### Required Qualifications and Skills - Strong proficiency in Python. - Working proficiency in C/C++ for performance-critical and hardware-integrated applications. - Experience developing and deploying computer-vision or deep-learning models. - Experience with OpenCV and real-time image-processing pipelines. - Familiarity with GStreamer or similar multimedia frameworks. - Experience with a deep-learning framework such as PyTorch or TensorFlow. - Understanding of model training, validation, dataset preparation, augmentation, and performance evaluation. - Experience deploying AI models on edge-computing platforms. - Familiarity with ROS/ROS2 and robotic software architectures. - Experience integrating cameras, sensors, and onboard computing systems. - Understanding of Linux-based development environments, networking, and system debugging. - Ability to profile and optimize inference latency, throughput, memory usage, and power consumption. - Strong analytical, debugging, and problem-solving skills. - Ability to communicate technical findings clearly and work effectively across engineering teams. ### Good to Have - Experience with NVIDIA Jetson, CUDA, TensorRT, ONNX, or GPU-accelerated computing. - Experience with Raspberry Pi or other embedded Linux platforms. - Knowledge of object detection, tracking, segmentation, visual odometry, SLAM, or sensor fusion. - Experience with ROS/ROS2, Gazebo, and robotics simulation. - Knowledge of MAVLink, QGroundControl, and Mission Planner. - Hands-on experience with PX4, ArduPilot, or a similar flight stack. - Understanding of UAV flight dynamics and multirotor or fixed-wing architectures. - Experience with Qt software development. - Experience with camera calibration, synchronization, streaming, and recording. - Familiarity with MLOps, experiment tracking, dataset versioning, and automated model evaluation. - Experience taking perception or AI systems from research prototypes through field deployment. **Experience:** 3–5 years in computer vision, robotics perception, AI/ML, or edge computing. **Education:** Degree in Electronics, Electrical Engineering, Computer Science, Artificial Intelligence, Robotics, or a related engineering discipline.