Mitel

R&D Intern (student) - iOS development

In short

This is a Software Development internship at Mitel, working closely with SW and/or AI developers to build software involving Mitel products, test automation tools, or test scripts. The role involves coding, design discussions, code reviews, documentation, and learning Agile practices under engineer mentorship. It requires being 1+ years from graduating in Computer Science or a related field, basic programming knowledge (Python, JavaScript, TypeScript, or C++), familiarity with Git, and advanced English; iOS development experience and basic AI knowledge are advantageous.

Overview
Internship – Software (SW) development
Internship will be working closely with SW developers, and/or AI development designers and/or AI SW developers. Develop SW involving Mitel products or Test Automation tools or test scripts. Support developers in their activities, including/involving infrastructure and development support. Enthusiasm for learning/implementing new technologies is expected.
Responsibilities
•Develop high quality software and solutions based on acquired skills and technical guidance from experienced engineers.
•Contribute to coding tasks, design discussions, and code reviews.
•Contribute to documentation (technical design, implementation notes).
•Explore SW and/or AI concepts to help develop innovative products.
•Learn about Agile development practices.
•Embrace mentorship from engineers to continuously grow technical skills.
Requirements
•Graduating in Computer Science, Computer Engineering, or a related field (1+ years to graduate).
•Basic programming knowledge (e.g., Python, JavaScript, TypeScript, or C++).
•Familiarity with Git and collaborative version control workflows.
•Knowledge of programming concepts (e.g., Object Oriented, full-stack, front-end, back-end, mobile development, etc.).
•Advanced English.
Additional Skills (Advantageous)
•Basic iOS SW development capabilities - coursing Apple Academy at PUC-PR university
•Basic AI knowledge:
•Transformers and Recurrent Neural Networks (RNNs).
•Vector spaces, similarity measures, and distance functions.
•Embeddings and representation learning.
•Foundation models and their applications.
•Concepts behind large language models (LLMs).
•Knowledge of web app development (front-end, back-end, or full-stack).
•Basic understanding of cloud platforms (AWS, Azure, GCP) or serverless architecture.

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