Computer Vision / Robotics Intern – Summer 2026

Parsons•Westminster, CO

2d•$22 - $38

About The Position

Parsons is now accepting applications for our Summer 2026 Computer Vision / Robotics Internship, supporting development of a new 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. This internship offers an exciting opportunity to apply robotics and computer vision to real-world infrastructure, working side-by-side with an experienced mentor and a software intern. You will help integrate 360° cameras and SLAM/localization tools, map inspector motion on a simple bridge model, and prototype basic defect detection and visualization workflows.

Requirements

Must be enrolled in a Bachelor’s or Master’s program in Robotics, Computer Science, Electrical/Computer Engineering, or 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 (video, trajectories, etc.) 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, working with 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 (e.g., region-of-interest extraction, simple crack/rust/spall detection using existing models or APIs).
Visualize inspector paths and defect points in 2D/3D for internal review and demos.
Collaborate with a software intern and mentor to define interfaces between perception/localization outputs and the inspection data/reporting pipeline.