Job Description

Key Responsibilities

Develop, improve, and expand deployment pipeline infrastructure and services Build and deploy hyperscale machine learning pipelines into production Works closely with the developer teams to provide self-service test integration, test coverage and quality. Collaborate with the Security Engineering and Architecture team to ensure code meets security requirements and is deployed in alignment with standards and governance processes. Debug and resolve the issues developers encounter when attempting to use cloud services, with an eye toward continuously improving developer experience. Execute against a vision of continuous integration and delivery that empowers developers Understand environmental needs for all data pipelines, processes and evaluate and enforce the required rules
Requirements:

Strong MLOps and DevOps expertise developing MLOps pipeline and operationalizing infra as code to deploy those pipelines art enterprise scale Establish best practices for developing and deploying MLOps pipelines and DevOps IAC. 7-9 years Building Infrastructure-as-code for Public Cloud using Terraform 7-9 years in a Dev Ops engineering or equivalent role. 7-9 years of developing, enhancing, and maintaining CI/CD automation and configuration management using tools such as Jenkins, Snyk, and GitHub 7-9 years' experience in MLOps and orchestration tools such as Airflow, Kubeflow, Optuna, Mlflow or other similar MLOps tools. 7+ years' experience with operationalizing and migrating ML models into production at scale.
Job Type: Permanent

Pay: RM17,000.00 - RM20,000.00 per month

Application Question(s):

This role requires to work in US time (4pm-1am MYT), are you good with it?
Experience:

MLOps & DevOps: 7 years (Required) CI/CD Automation: 7 years (Preferred) Python: 5 years (Required) MLOps tools: 4 years (Required)
Work Location: Hybrid remote in Kuala Lumpur