Optical Test Automation Co-op/Intern

Nokia
Ottawa, Ontario, CanadaPosted Sep 4, 2026
Winter 2027

About the role

Position: Optical Test Automation Co-op/Intern Number of Position(s): 1 Duration: 8-12 Months Date: Winter 2027 (Starting January 4th) Location: Onsite, Ottawa, Ontario, CANADA

EDUCATIONAL RECOMMENDATIONS

Currently a candidate for a Bachelor's degree or College Diploma in Electronic and Communication Engineering, Physics, Photonics, Electrical Engineering, or a related field with an accredited institution.

RESPONSIBILITIES

What you will do

  • Support optical system verification testing activities for Nokia networking

solutions.

  • Maintain and enhance optical testbeds to support testing requirements and

project objectives.

  • Execute test plans and document results for system validation activities.
  • Develop and maintain Python-based automation tools for test execution, data

collection, and reporting.

  • Automate data extraction, cleansing, and analysis processes to improve test

efficiency.

  • Utilize AI-powered tools to support prediction, analysis, and classification

of test results.

  • Work with IQNOS and GX line system platforms and various optical laboratory

instruments.

  • Analyze test outcomes and prepare presentations and technical summaries to

communicate findings.

  • Collaborate with team members to troubleshoot issues and support continuous

improvement initiatives.

QUALIFICATIONS

You Must Have

  • Basic understanding of fiber optics and optical fiber communication

technologies. Programming experience with Python.

  • Exposure to laboratory environments involving fiber optics, photonics, or

optical communications.

  • Understanding of automation concepts and Python-based development.
  • Strong communication skills with the ability to present technical information

effectively.

  • Ability to work collaboratively in a team environment.
  • Self-motivated and proactive approach to learning and problem-solving.

It Would Be Nice If You Also Had

  • Knowledge of Machine Learning and Neural Network concepts.

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