Optical Test Automation Co-op/Intern

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.
 

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.

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.
• Coursework or project experience in Fiber Optics, Optoelectronic Devices, Quantum Electronics, Machine Learning, or Neural Networks.
• Familiarity with predictive data analysis techniques.
• Experience with automated data cleanup and analytics frameworks.
• Exposure to AI tools and technologies used for engineering analysis and automation.
• Experience working with optical communication systems, testing environments, or related laboratory equipment.