Infra Observability & AI/ML Intern

Synapxe; Singapore; Hybrid; SGD 13,000 - 20,000; Part time

Job summary

Synapxe internship in Singapore invites you to join the Infrastructure team, focusing on central log management and observability across devices. You will contribute to data-driven AI/ML improvements and surface insights through dashboards, collaborating with stakeholders and learning how to translate requirements into actionable models.

You will gain hands-on experience in data analysis, Kibana visualization, and documenting technical findings, supporting IT operations and proactive issue

Qualifications

• Knowledge of data mining and statistical analysis techniques.
• Basic programming knowledge in Python or similar languages.
• Exposure to data visualization tools, particularly Kibana or similar platforms.
• Familiar with ETL pipelines and data processing methodologies.

Responsibilities

• Engage with stakeholders to understand infrastructure observability needs and identify opportunities for AI/ML-driven improvements.
• Translate user requirements into actionable data and modelling solutions.
• Prototype and develop AI/ML models to support AIOps use cases such as root cause analysis and predictive IT maintenance.
• Create dashboards using Kibana to surface meaningful insights from infrastructure data.

Skills

Data analysis

Python basics

Analytical thinking

Communication skills

Education

Higher Nitec in Business Information Systems / Data Engineering / IT Systems and Networks

Tools

Kibana

SQL

ETL tools

Job description

Synapxe internship in Singapore invites you to join the Infrastructure team, focusing on central log management and observability across devices. You will contribute to data-driven AI/ML improvements and surface insights through dashboards, collaborating with stakeholders and learning how to translate requirements into actionable models.

You will gain hands-on experience in data analysis, Kibana visualization, and documenting technical findings, supporting IT operations and proactive issue