Intern (P03366)

• Working and hands-on experience on Machine Learning, Computer Vision Applications and optimisation on edge hardware

• Structure from Motion (SfM), Object Detection, Object Tracking, State Estimation, ROS Framework (Mandatory)
• Working Knowledge of sensors : Monocular Camera, Stereo camera, LiDAR, Radar , IMU (Mandatory) 
• Coding Skills : Python, C++14/17, ROS
• ML and Computer Vision Experience : 
• ML Application experience : Pytorch, Tensorflow, JAX 
• CV Applications : OpenCV 

• Edge Deployment : Experience with Nvidia Jetson Device (TensorRT) , ONNX, ncnn 
• Experience with GPU programming skills preferred (CUDA)
• Experience with NLP, large-language models , vision-language models or foundation models

• BTech Students in their 3rd/4th year or MTech Students in the final year with minimum internship period of 6 months
• Btech/MTech from Computer Science/Mechatronics/Robotics/Electronics.

This internship focuses on machine learning and computer vision for autonomous unmanned systems, including perception methods and optimization for edge hardware. The work is connected to defence-oriented research and product development involving unmanned platforms and robotic swarms.

Role at a glance

Skills mentioned

What you will likely work on

• Apply machine learning and computer vision to unmanned systems.
• Develop or work with visual perception methods, including detection, tracking, and state estimation.
• Explore Structure from Motion techniques.
• Work with camera, LiDAR, radar, and IMU sensor inputs.
• Optimize machine-learning and computer-vision applications for edge hardware.
• Contribute to research and product development for unmanned platforms and robotic systems.

Good fit signals

• Currently in the third or fourth year of a BTech program, or the final year of an MTech program.
• Can commit to an internship lasting at least six months.
• Has hands-on experience with machine learning or computer vision applications.
• Has experience with the mandatory perception methods, ROS, and listed sensor types.
• A background in Computer Science, Mechatronics, Robotics, or Electronics aligns with the stated fields of study.