Shape the future of software engineering education by leading the Machine Learning track within a pioneering undergraduate programme. This role is central to refining and delivering experiential, student-centered learning that aligns with evolving industry standards and educational innovation.
Core Responsibilities
- Lead the design and continuous improvement of Machine Learning modules, ensuring content remains current, practical, and aligned with both academic and industry expectations.
- Deliver and coordinate in-person and online academic experiences, including live coding, peer learning sessions, hackathons, and mock interviews to deepen student engagement.
- Guide the academic onboarding and ongoing development of both new and current coaching staff, fostering a consistent and high-quality learning experience.
- Review and update curriculum materials each trimester based on student feedback, performance data, and emerging trends in machine learning and software engineering.
- Oversee internship coordination and explore industry partnerships to enrich student learning with real-world applications.
- Ensure all academic components meet internal quality standards and contribute to accreditation and programme review processes.
- Implement improvements based on student evaluations, consultative forums, and annual reviews to maintain programme relevance and effectiveness.
- Support the review of course content developed by external partners and ensure alignment with programme goals.
- Uphold a student-first approach while promoting safeguarding, ethical practices, and inclusive learning environments.
Qualifications and Skills
Candidates must hold a Master’s degree in Computer Science, Software Engineering, or a closely related field with substantial programming focus. A proven background in machine learning applications and at least five years of experience in industry or academic mentoring is essential.
Required expertise includes advanced mathematical foundations of ML, hands-on experience with Python, TensorFlow, Keras, Scikit-learn, and familiarity with transformer models and chatbot systems. Proficiency in Linux, shell scripting, git, and debugging is expected.
Strong communication, coaching, and organisational abilities are crucial, along with a flexible mindset suited to a fast-evolving educational environment. Experience in experiential learning design, student project supervision, and remote teaching is highly valued.
Work Environment
This is a hybrid role based in Mauritius, supporting both in-person and online learning. The position requires collaboration with distributed teams and adaptability to changing educational demands. The ideal candidate thrives in dynamic, mission-driven settings and is committed to ethical leadership and student well-being.
