MLOps Platform Engineer — Build Scalable AI Infra

ntu; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

NTU, hosting AISG platforms, seeks a Platforms Engineer, MLOps in Singapore to design, build and run modern ML infrastructure and tooling. You will empower AISG teams to train and deploy models at scale, and develop CI/CD for ML workflows across the platform.

Collaborating with data scientists and engineers, you will implement IaC, ensure security and reliability, and drive technical decisions to completion in a fast-paced national AI program.

Qualifications

• At least 3 years in an engineering or infrastructure role.
• Proficiency in Python and at least one other programming language such as TypeScript.
• Proficiency in administering Linux systems.
• Experience with automation tools (Ansible, Terraform, Bash).
• Familiarity with Docker, Kubernetes and Helm ecosystem.
• Experience with cloud platforms (AWS, Azure or GCP).
• Strong DevOps/MLOps practices, debugging, and agile development.
• Excellent written and verbal communication.

Responsibilities

• Design, build and maintain the AISG platform and tooling stack.
• Liaise between Platforms Engineering and AI project teams for ML tooling and CI/CD.
• Develop and implement MLOps pipelines, tests, monitoring and versioning.
• Collaborate with data scientists and data engineers to meet AISG needs.
• Build and maintain production infrastructure that is resilient, secure and high-performing.
• Implement infrastructure-as-code for automation and provisioning.
• Document and investigate issues arising from systems.
• Develop tools that improve infrastructure and mentor AISG Apprentices.
• Drive technical decisions to completion.

Skills

Python

TypeScript

Linux

Docker

Kubernetes

Terraform

Ansible

Bash

CI/CD

AWS

GCP

Azure

Helm

GitOps

Tools

MLflow

Weights & Biases

Prometheus

Grafana

Job description

NTU, hosting AISG platforms, seeks a Platforms Engineer, MLOps in Singapore to design, build and run modern ML infrastructure and tooling. You will empower AISG teams to train and deploy models at scale, and develop CI/CD for ML workflows across the platform.

Collaborating with data scientists and engineers, you will implement IaC, ensure security and reliability, and drive technical decisions to completion in a fast-paced national AI program.