Computer Vision Engineering Intern

Holland, L.P.•University Park, IL
•$18 - $21•Onsite

About The Position

Holland’s Rail Measurement Systems and Services (RMSS) provides railroad track measurement and testing services and technologies. The RMSS Product Development Team designs, builds, and deploys track inspection and measurement systems domestically and internationally, including hi-rail, rail-bound, and locomotive-attended and autonomous measurement systems. The Computer Vision Engineering Intern will develop image-processing algorithms for track geometry and rail-profile measurement systems and develop and optimize image-recognition algorithms for video recordings. This is a full-time summer internship scheduled for 40 hours per week for approximately 12 weeks in Summer 2027. The position is on-site in University Park, Illinois. Final-year undergraduate and graduate students are preferred. The work is primarily in an office and lab, with occasional outdoor field work near railroad tracks. Required personal protective equipment must be worn during field work, and the role requires the ability to lift up to 25 pounds, with or without reasonable accommodation.

Requirements

  • Be a final-year Bachelor’s, Master’s, or PhD student in Computer Science, Electrical/Computer Engineering, or a related field.
  • Have coursework or project experience in computer vision, image processing, or machine learning.
  • Be proficient in Python and OpenCV.
  • Be available to work 40 hours per week on-site for the full summer.
  • Be able to lift up to 25 pounds, with or without reasonable accommodation.

Nice To Haves

  • Experience with PyTorch or TensorFlow.
  • C++ and/or GPU (CUDA) experience.
  • Experience with object detection on video, camera calibration, or laser/3D measurement.
  • Interest in railway or infrastructure inspection.
  • Final-year undergraduate or graduate (Master’s or PhD) student status is preferred.

Responsibilities

  • Develop image-processing algorithms for camera- and laser-based rail-profile and track-geometry measurement.
  • Develop, train, and optimize image-recognition models to detect track features and assets in video recordings.
  • Prepare and label image and video datasets from field recordings.
  • Test algorithm accuracy and speed against reference data, and document results.
  • Work with the software team to integrate prototypes and present final results to the team.
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