Full Stack Developer (AI/ML Focus)

Singaporean Only

Job Title: Full Stack Developer (AI/ML Focus) Summary

We are seeking a motivated Full StackDeveloper with AI/ML exposure to join our growing software engineeringteam. In this role, you will design and build modern applications that leverageartificial intelligence to deliver smarter, more efficient user experiences.

This position is ideal for engineers whoare passionate about both software development and applied AI , and whowant to work on real-world AI-enabled products.

Key Responsibilities

Design and build scalable full stack applications from frontend to backend

Develop and integrate AI-powered features such as:

Conversational interfaces (chatbots)

Intelligent search or recommendations

Automation and decision-support systems

Work with APIs and microservices to connect AI services with application workflows

Collaborate with cross-functional teams including data scientists and product owners

Participate in system design, architecture discussions, and technical decision-making

Deploy and monitor applications in either cloud or on-prem environments

Write clean, maintainable, and well-documented code

Contribute to both Agile sprints or structured Waterfall phases as required

Technical Requirements

Degree in Computer Science, Software Engineering, or related discipline

2-5 years of experience in full stack development

Strong frontend development skills:

JavaScript / TypeScript

React, Angular, or Vue.js

Backend development experience:

Node.js, Python (FastAPI/Flask), or Java (Spring Boot)

Experience with databases:

Relational (PostgreSQL, MySQL) or NoSQL (MongoDB)

Understanding of API design and integration (REST/JSON)

AI/ML Requirements

Basic to intermediate knowledge of machine learning concepts

Experience (project or professional) with:

AI/ML libraries (TensorFlow, PyTorch, Scikit-learn), or

AI APIs (OpenAI, Azure AI, AWS AI)

Preferred Skills

Experience with cloud platforms (Azure, AWS, or GCP)

Familiarity with CI/CD pipelines and DevOps practices

Exposure to containerization (Docker, Kubernetes)

Experience working in Agile environments or structured SDLC (Waterfall)

Knowledge of security best practices and authentication mechanisms