5–7 years in Robotics, Autonomous Systems, AI, Computer Vision, or UAV Software Development.

Strong ROS/ROS2, SLAM, Localization, Navigation.

Computer Vision, AI, Deep Learning.

LiDAR, Camera, IMU, GNSS integration.

PCL, OpenCV, Linux, Git.

AirSim, Gazebo, CARLA, CarMaker, Isaac Sim.

PX4, ArduPilot, Mission Planner, QGroundControl preferred.

Docker, CUDA, TensorRT, NVIDIA Jetson preferred.

Innovation: Exposure to reinforcement learning, SLAM, and sensor fusion for UAV autonomy

Compliance Awareness: Familiarity with aerospace/autonomy certification frameworks (DO-178C, DO-254, DGCA UAS guidelines)

Leadership: Ability to mentor junior engineers and lead computer vision design reviews

Reliability Engineering: Experience in robustness testing, fault tolerance, and redundancy strategies

• Programming: C++, Python
• ROS/ROS2
• PCL, OpenCV
• TensorFlow, PyTorch
• Linux,Git
• Simulation: AirSim, Gazebo, CARLA, CarMaker, Isaac Sim
• Docker, CUDA, TensorRT
• Debugging, optimization, documentation

Bachelor's or Master's degree in Robotics, Computer Science, Electronics, Mechatronics, AI, or a related field.

• Design, develop, and deploy software for autonomous robotic systems.
• Develop AI and Deep Learning models for robotic perception and decision-making.
• Design and implement mapping, localization, navigation, and SLAM algorithms.
• Develop perception pipelines using cameras, LiDAR, IMU, GNSS, and other sensors.
• Build and maintain ROS/ROS2-based robotics applications.
• Process and analyze point cloud data using PCL.
• Develop computer vision applications using OpenCV.
• Integrate and optimize AI models for real-time robotic applications.
• Develop, test, and validate robotic software in simulation and real-world environments.
• Perform sensor calibration, system integration, and performance optimization.
• Collaborate with cross-functional teams including embedded, hardware, AI, and software engineers.
• Document software architecture, technical designs, and validation results.