Remote MLOps Engineer - CI/CD & Cloud Infra

Pt Japfa Comfeed Indonesia Tbk; Jawa Barat; Remote; IDR 180,000,000 - 300,000,000; Full time

Benefits offered by this job

Fully remote

Competitive salary

Health insurance

Professional development budget

Global distributed team

Job summary

Pt Japfa Comfeed Indonesia Tbk is seeking a skilled Machine Learning Operations (MLOps) Engineer to join its fully remote, high-performing team. You will bridge ML development and IT operations, deploying and maintaining ML models in production, building automated pipelines, and scaling infrastructure.

You will collaborate with data scientists and software engineers to ensure reliable monitoring, security, and performance across ML systems, leveraging Python, Docker, Kubernetes, and cloud

Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related field.
• Experience in MLOps, DevOps, or similar roles focused on automation.
• Strong Python and containerization (Docker, Kubernetes) skills.
• Experience with cloud platforms (AWS, Azure, GCP) and ML services.
• Familiarity with ML frameworks and deployment strategies.
• Ability to work independently in a remote setting.

Responsibilities

• Design, implement, and maintain CI/CD pipelines for ML models.
• Automate deployment, scaling, and monitoring of ML models in production.
• Develop infrastructure and tooling to support the ML lifecycle.
• Collaborate with data scientists and software engineers to troubleshoot production issues.
• Implement robust monitoring, logging, and alerting for ML systems.
• Ensure the security, reliability, and performance of ML infrastructure.

Skills

Python

Docker

Kubernetes

Cloud platforms

ML frameworks

Problem solving

Education

Bachelor's degree in CS/Engineering

Tools

CI/CD tooling

Job description

Pt Japfa Comfeed Indonesia Tbk is seeking a skilled Machine Learning Operations (MLOps) Engineer to join its fully remote, high-performing team. You will bridge ML development and IT operations, deploying and maintaining ML models in production, building automated pipelines, and scaling infrastructure.

You will collaborate with data scientists and software engineers to ensure reliable monitoring, security, and performance across ML systems, leveraging Python, Docker, Kubernetes, and cloud