About us: Peer Robotics is revolutionizing manufacturing with collaborative mobile robots that work seamlessly alongside humans. Peer Robotics builds end to end solutions for material handling that learn from human interaction in real-time. Allowing people on the shop floors to easily integrate and deploy our robots.

Our intelligent, adaptable, and collaborative robots are capable of automating existing assets like trolleys and pallets, enabling manufacturing industries and warehouses to automate their existing operations without making any infrastructure changes.

Role

We are seeking a passionate roboticist who enjoys developing and deploying solutions to solve customer problems. As a Computer Vision intern, you will work on developing computer vision applications in ROS2 (Python/C++) for scene understanding, and detection, segmentation of novel objects in manufacturing and warehousing environments. This role involves end to end developing, fine-tuning and deploying vision models on existing hardware. This is an excellent opportunity to gain hands-on experience in robotics, computer vision, and software development while working with a collaborative and innovative team.

Period: 3 - 6 Months, starting July 2025

Responsibilities

Prepare manufacturing/warehousing datasets for downstream inference tasks.
Train, deploy and fine tune detection, segmentation models and VLMs for novel objects/scenes from scratch.
Optimise trained models for edge devices in ROS2 like Jetson Orin Nano and Orin AGX.
Literature survey and presentation of state of the art computer vision algorithms.
Visit customer sites for data collection, testing and deploying applications..

Requirements

Currently pursuing Master’s degree or PhD in Robotics or Computer Science.
Experience developing and deploying robotics applications on real hardware.
Experience with C++, Python, and RUST programming.
Strong fundamentals in computer vision.
Team player with excellent communication and problem solving skills.

Preferred Qualifications

Prior experience developing and scaling segmentation models on edge devices for novel objects.

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