Computer Vision/Robotics Intern

Parsons Corporation•Westminster, CO

2d•$23 - $40

About The Position

Parsons is accepting applications for its Summer 2027 Computer Vision / Robotics Internship. The intern will support development of an AI-enabled infrastructure inspection capability using drone data, 360° video, localization, and voice to transform how bridge and vertical-structure inspections are captured and reported. The intern will apply robotics and computer vision to infrastructure inspection, working alongside an experienced mentor and a software intern. Work includes integrating 360° cameras and SLAM/localization tools, mapping inspector motion on a simple bridge model, and prototyping defect-detection and visualization workflows. The position is part of Parsons’ Critical Infrastructure team.

Requirements

Must be enrolled in a Bachelor's or Master's program in Robotics, Computer Science, Electrical/Computer Engineering, or a related field at an accredited college or university.
Strong programming skills in Python and/or C++, with experience using libraries such as NumPy and OpenCV.
Familiarity with SLAM, visual odometry, or robotics localization through coursework or projects.
Comfort working with real-world sensor data, including video and trajectories, and debugging noisy inputs.
Strong analytical, organizational, and communication skills.

Nice To Haves

A GPA of 3.0 or higher is desirable.
Prior project or internship experience in robotics, computer vision, or perception is preferred but not required.

Responsibilities

Ingest and process 360° video and use an off-the-shelf SLAM/localization SDK to estimate inspector position over time.
Develop scripts and tools to map timestamps and poses to 3D locations on a simple bridge or structure model.
Prototype basic computer vision routines, such as region-of-interest extraction and simple crack, rust, or spall detection using existing models or APIs.
Visualize inspector paths and defect points in 2D/3D for internal review and demonstrations.
Collaborate with a software intern and mentor to define interfaces between perception/localization outputs and the inspection data/reporting pipeline.