Senior MLOps & Production Reliability Engineer

Systems Limited; Kuala Lumpur; On-site; MYR 180,000 - 240,000; Full time

Job summary

Systems Limited is seeking an experienced MLOps-focused professional to own the production lifecycle of ML models, ensuring validated models are reliably deployed, monitored, and scaled. The role emphasizes CI/CD, cloud infrastructure, automation, observability, cost optimization, and incident management.

You will lead pipelines, collaborate with Data Scientists, mentor engineers, and engage with presales to prove production readiness. On-call duties may apply.

Qualifications

• 6+ years in MLOps/ML Platform Eng with production ownership.
• Strong CI/CD, containerization, cloud infra and ML observability.
• IaC and automated deployment pipelines experience.
• Experience on AWS/Azure/GCP and FinOps practices.
• Ability to communicate incidents to business stakeholders, clearly.

Responsibilities

• Own production serving, CI/CD, deployment and monitoring of ML models.
• Build and maintain model retraining, versioning and deployment pipelines.
• Manage ML infrastructure and optimize cloud costs via FinOps.
• Implement observability, alerting, drift detection and performance monitoring.
• Own production incident response and on-call support.
• Collaborate with Data Scientists to design scalable, production-ready systems.
• Support presales/PoCs by demonstrating production readiness and scalability.
• Mentor engineers on MLOps and production-readiness best practices.
• Communicate infrastructure cost, performance and reliability trade-offs to non-technical stakeholders.

Skills

MLOps

CI/CD

Cloud infrastructure

Observability

FinOps

Model lifecycle

IaC

Mentoring

Stakeholder communication

Tools

AWS

Azure

GCP

Docker

Kubernetes

Terraform

Monitoring tools

Job description

Systems Limited is seeking an experienced MLOps-focused professional to own the production lifecycle of ML models, ensuring validated models are reliably deployed, monitored, and scaled. The role emphasizes CI/CD, cloud infrastructure, automation, observability, cost optimization, and incident management.

You will lead pipelines, collaborate with Data Scientists, mentor engineers, and engage with presales to prove production readiness. On-call duties may apply.