MLOps Platform Engineer: AI Pipelines & LLMs

STRT.ASIA PTE. LTD.; Singapore; On-site; SGD 90,000 - 130,000; Full time

Job summary

STRT.ASIA PTE. LTD. is seeking a skilled ML platform engineer (MLOps) to join our agile platform team within our ML & AI ART division in Singapore.

You will drive orchestration of advanced agentic workflows to enable autonomous AI-driven systems and engineer robust data pipelines with comprehensive model management lifecycles. You will operationalize LLMs, embeddings and multi-agent architectures, containerize applications with Docker, orchestrate via Kubernetes, and build CI/CD pipelines for ML

Qualifications

• Proficient in Python, Docker, and Kubernetes to build and deploy ML solutions.
• Experience with end-to-end ML pipelines from data ingestion to training and serving.
• Familiarity with CI/CD for ML models and LLM applications.

Responsibilities

• Implement end-to-end machine learning pipelines from data ingestion to training and model serving.
• Operationalize LLMs, embeddings, and multi-agent systems in real-world applications.
• Manage the ML lifecycle (experimentation, registry, deployment).
• Oversee model promotion, validation gates, and production deployment.
• Containerize applications using Docker and orchestrate with Kubernetes.
• Build and maintain CI/CD pipelines for ML models and LLM apps.
• Design and implement production-grade RAG systems.
• Write clean, testable, efficient Python code.

Skills

Python

Docker

Kubernetes

CI/CD

MLflow

LLMs

Data preprocessing

Feature engineering

Model lifecycle

Agentic workflows

LLM orchestration

GPU compute

Cloud compute

GitLab/Jenkins

Tools

Weights & Biases

GitLab

Jenkins

Job description

STRT.ASIA PTE. LTD. is seeking a skilled ML platform engineer (MLOps) to join our agile platform team within our ML & AI ART division in Singapore.

You will drive orchestration of advanced agentic workflows to enable autonomous AI-driven systems and engineer robust data pipelines with comprehensive model management lifecycles. You will operationalize LLMs, embeddings and multi-agent architectures, containerize applications with Docker, orchestrate via Kubernetes, and build CI/CD pipelines for ML