AI Engineer: NLP, RAG & Multi-Modal AI Deployment

InternSG; Singapore; On-site; SGD 20,000 - 27,000; Part time

Job summary

InternSG is offering a part-time internship in Singapore focusing on AI engineering and model deployment. You will work on developing and optimizing AI models, integrating AI features into applications, and building automated workflows with mentoring from senior engineers.

Role emphasizes experimentation, data preprocessing, and creating documentation and demos to showcase results. Candidates should be passionate about AI engineering and cloud-based deployment.

Qualifications

• Proficiency in Python and familiarity with AI/ML frameworks.
• Understanding of large language models (LLMs), including RAG, fine-tuning, and prompt engineering.
• Knowledge of data processing, vector databases, and API development.
• Strong interest in AI engineering, automation, and model deployment.

Responsibilities

• Support the development and optimization of AI models (NLP, RAG, OCR, image, and multi-modal models).
• Assist in integrating AI capabilities into web applications, APIs, or enterprise software.
• Participate in experimentation, testing, data preprocessing, and model tuning for internal AI projects.
• Build and test AI workflows, automation systems, and engineering tools.
• Translate business use cases into technical solutions with support from senior engineers.
• Prepare technical documentation, test reports, and demos.

Skills

Python

AI/ML frameworks

LLMs

RAG

Prompt engineering

Vector databases

API development

Automation

Model deployment

Tools

Docker

Kubernetes

Cloud platforms

GitHub

Job description

InternSG is offering a part-time internship in Singapore focusing on AI engineering and model deployment. You will work on developing and optimizing AI models, integrating AI features into applications, and building automated workflows with mentoring from senior engineers.

Role emphasizes experimentation, data preprocessing, and creating documentation and demos to showcase results. Candidates should be passionate about AI engineering and cloud-based deployment.