Key Responsibilities

Design, build, and deploy scalable AI and machine learning solutions, supporting the full lifecycle from data ingestion to production deployment
Develop and maintain end-to-end pipelines, including model training, validation, and serving
Work with advanced AI technologies such as Large Language Models (LLMs), embeddings, multi-agent systems, and RAG-based architectures
Manage model lifecycle processes, including experimentation,versioning, validation, and release into production environments
Support the development of reliable and scalable infrastructure using containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines
Collaborate closely with data scientists, engineers, and other stakeholders to translate research and prototypes into production-ready applications
Integrate AI solutions into existing systems while ensuring performance, scalability, and reliability
Monitor and improve model performance, including tracking data drift and optimizing system efficiency
Contribute to engineering best practices through code reviews, testing, and continuous improvement initiatives

Qualifications

Degree in Computer Science, Data Science, Mathematics, Statistics, or a related field, or equivalent practical experience
Strong programming skills in Python, with experience writing clean, maintainable, and testable code
Hands-on experience developing and deploying machine learning models and pipelines in production environments
Familiarity with ML Ops practices and tools such as ML flow, Weights & Biases, or similar platforms
Experience working with Large Language Models (LLMs) and modern AI frameworks
Understanding of agent-based systems, orchestration frameworks, or related AI architectures
Experience with containerization (Docker) and working knowledge of Kubernetes
Familiarity with CI/CD tools such as GitLab, Jenkins, or similar
Solid understanding of data preparation, feature engineering, and model evaluation techniques
Knowledge of core statistical and mathematical concepts relevant to machine learning
Experience working with cloud platforms and GPU-based workloads is an advantage
Strong problem-solving skills and the ability to work effectively in cross-functional teams

This isa permanent role in Singapore.

AI/ML Engineer