Research Intern- Autonomous Perception & Navigation Systems

Job Description

About the Role We?re seeking a Research Intern passionate about applying AI and machine learning to autonomous UAV perception and navigation . You?ll explore and prototype learning-based algorithms that help drones see, localize, and move intelligently ? even in dynamic or GPS-denied environments. This internship provides hands-on exposure to simulation environments, sensor-fusion pipelines, and embedded AI systems. Key Responsibilities: Support research and prototyping of AI/ML algorithms for perception, tracking, localization and navigation. Work on multi-sensor fusion combining visual, inertial, and positional data for improved environmental understanding. Train and test computer vision or deep learning models for detection, motion estimation, and environmental understanding . Use high-fidelity simulations with physics-based environments to generate datasets and test autonomy pipelines. Assist in integrating perception and navigation modules into flight-control or hardware-in-the-loop setups. Optimize real-time inference and video/data streaming pipelines for embedded AI systems. Skills & Qualifications: Strong foundation in deep learning, computer vision, and state estimation . Understanding of object detection, tracking, SLAM, and sensor-fusion techniques . Proficiency in Python and familiarity with PyTorch/TensorFlow and OpenCV . Experience working on Linux environments and basic knowledge of C++ . Familiarity with simulation tools (Gazebo, Webots, Isaac Sim) and autopilot frameworks (PX4, ArduPilot). What you'll Gain: End-to-end exposure to AI-driven autonomous navigation and perception systems . Experience with simulation-driven development and testing of UAV autonomy algorithms. Practical exposure to real-time AI model deployment on embedded hardware. Opportunity to contribute to next-generation UAV guidance and autonomy research