DevOps Engineer | MLOps for AI Production & Reliability

Digile Pte Ltd; Kampung Malaysia Tambahan; Presencial; MYR 120 000 - 180 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Travel to customer sites

Exposure to AI/ML Ops

Resumo da oferta

Digile Pte Ltd’s AI Practice seeks a DevOps Engineer with an MLOps focus to join our shared engineering pool serving customer-embedded AI delivery pods in Kuala Lumpur, Malaysia.

You will own deployment, infrastructure and reliability for AI workflows, working with Senior and Junior FDEs and AI Product Managers to ensure workflows are deployable, monitorable and governable across multiple pods.

Qualificações

• 3-5 years of experience in DevOps, SRE, platform or cloud engineering with MLOps exposure.

Responsabilidades

• Design, build and maintain CI/CD pipelines for AI workflows.
• Set up and manage cloud infrastructure with Infrastructure as Code.
• Implement monitoring, logging and alerting including LLM observability.
• Maintain data, model and output quality drift targets and uptime.
• Own deployment and reliability including incident response.

Conhecimentos

CI/CD pipelines

SRE mindset

Security & compliance

Bash & Python scripting

Communication skills

DevOps planning

Ferramentas

Azure DevOps

GitHub Actions

Docker

Kubernetes

Terraform

CI/CD tooling

Descrição da oferta de emprego

Digile Pte Ltd’s AI Practice seeks a DevOps Engineer with an MLOps focus to join our shared engineering pool serving customer-embedded AI delivery pods in Kuala Lumpur, Malaysia.

You will own deployment, infrastructure and reliability for AI workflows, working with Senior and Junior FDEs and AI Product Managers to ensure workflows are deployable, monitorable and governable across multiple pods.