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