AI/ML Coop/Intern

Description du poste:

Name of the position: AI/ML Coop/Intern
Number of Position(s): 1
Duration: 3-4 Months
Date: May - August 2026
Location: Virtual, Canada
EDUCATIONAL RECOMMENDATIONS
Currently enrolled as a junior or senior in a Bachelor's degree program in Artificial Intelligence, Telecommunications, Computer Science, Computer Engineering, Information Systems, or a related field at an accredited Canadian institution.

* Gain basic knowledge of the Nokia Products, with a particular focus on the deployment, delivery, and operational aspects of Custom Application and Solution products.
* Actively participate in experimental initiatives within the Nokia Lab, working on innovative automation and AI-driven operational workflows, including end-to-end closed-loop automation use cases.
* Conduct comprehensive analyses of experimental outcomes, benchmarking them against existing customer processes to identify gaps, inefficiencies, and opportunities for enhancement.
* Prepare detailed reports on findings, providing actionable insights and recommendations to optimize and improve the current automation solutions and operational workflows

Profil requis du candidat:

* Familiarity with software programming for AI agentic frameworks, data analytics, and strong grasp of algorithms and data structures to solve real-world challenges efficiently.
* Proactive, inquisitive mindset with a can-do attitude toward learning new technologies, tools, and concepts in dynamic environments.
* Strong programming skills in Python; experience with C++, Go, or Java is a plus, along with exposure to big data ecosystems (Hadoop, Spark) or data processing pipelines.
* Interest or background in Artificial Intelligence (AI) or Machine Learning (ML) through projects, research, or personal initiatives.
* Familiarity with distributed systems, containerization, and orchestration tools (e.g., Docker, Kubernetes), plus ability to analyze problems, design experiments, and debug complex system interactions.
* Excellent communication skills and proven effectiveness in collaborative team settings