NPI Engineering Intern (AI-Assisted Operations)
At a glance
- Location
- Malaysia
- Work type
- Onsite
- Category
- Engineering
NPI Engineering Intern at Nokia in Malaysia. Gain hands-on experience in NPI processes for telecom networks and cloud-native systems, using AI-assisted tools for data processing, log parsing, and automation. Collaborate with cross-functional teams, develop scripts, and maintain lab documentation while learning about AI, networking, and lab operations.
What they are looking for
Location: Malaysia Department: Corporate Services
As an NPI Engineering Intern, you'll be part of the NI S&D CD APAC CE FN NPI team, supporting the NPI process. You'll gain valuable exposure to real-world telecom networks and cloud-native systems, utilizing AI-assisted tools to enhance efficiency. This role is an excellent opportunity to learn and grow within a dynamic and innovative environment.
Assist the NPI team with lab operations, test-bed setup, and data analysis.
Apply basic AI-assisted tools for data cleansing, log parsing, and document summarization.
Collaborate with cross-functional teams to deliver engineering tasks efficiently.
Develop scripts to automate processes and improve workflow.
Ensure accurate and detailed lab documentation.
Troubleshoot and provide auxiliary support for technical issues.
Stay updated with the latest AI and networking technologies.
Contribute to a positive and collaborative team environment.
Complete tasks with a high level of attention to detail and accuracy.
Bachelor's or Master's student in Data Analytics, Computer Science, Telecommunications, or related fields.
Practical knowledge of Linux operating system is a must.
Basic understanding of AI concepts and its application in data processing and analysis.
Foundational knowledge of computer and networking fundamentals, including TCP/IP, Ethernet, routing, and switching.
Strong logical thinking skills and attention to detail for data handling.
Excellent teamwork and communication skills, with the ability to follow technical guidance.
Available to commit at least 16 hours per week during the internship.
Previous experience in lab environments or technical projects is an advantage.
Familiarity with container concepts (Docker/Kubernetes) is a plus.
A self-motivated and proactive attitude towards learning and contributing to the team.