Docker containerization and kubernetes orchestration
Large language models (llms) and agentic workflows
LTM LIMITED Singapore Branch is seeking an AI Engineer to join their agile platform team, focusing on MLOps and bridging experimental data science with production-grade systems. The role involves collaborating with cross-functional teams, engineering data pipelines, and managing the machine learning lifecycle
Job Summary
This role bridges the gap between experimental data science and production-grade systems by driving the orchestration of advanced agentic workflows.
The successful candidate will engineer robust data pipelines and manage the full machine learning lifecycle from experimentation to safe production deployment.
You will collaborate with cross-functional teams to operationalize LLMs, embeddings, and multi-agent systems while ensuring optimal performance and reliability.
Matching Summary
Match Score: 85
LTM LIMITED Singapore Branch is seeking an AI Engineer to join their agile platform team, focusing on MLOps and bridging experimental data science with production-grade systems. The role involves collaborating with cross-functional teams, engineering data pipelines, and managing the machine learning lifecycle.
Skills & Requirements
Must-have
Advanced Python programming proficiency
Docker containerization and Kubernetes orchestration
Large Language Models (LLMs) and agentic workflows
MLflow or similar experiment tracking tools
CI/CD pipeline development for ML applications
RAG system design and implementation
Model lifecycle management and drift monitoring
Nice-to-have
GPU architecture optimization knowledge
Cross-functional collaboration skills
Continuous learning mindset for AI advancements
Strong problem-solving and analytical abilities
Experience with data preprocessing and feature engineering
Key Requirements
Degree in Data Science, Computer Science, Mathematics, Statistics, or related field
Proven work experience in machine learning or data science roles
Hands-on experience with GitLab or Jenkins CI/CD pipelines