Remote MLOps Engineer: Automate, Deploy & Scale ML

Cv Syafiiq Enterprise; Batam; Remote; IDR 1,628,959,000 - 2,714,932,000; Full time

Benefits offered by this job

Competitive salary

Fully remote

Health insurance

Professional development budget

Global distributed team

Job summary

Cv Syafiiq Enterprise is seeking a skilled Machine Learning Operations (MLOps) Engineer for a fully remote role. You will bridge ML development and IT operations, deploying, monitoring, and maintaining ML models in production from anywhere.

You will design CI/CD pipelines, automate deployment, and build infrastructure to support the ML lifecycle while collaborating with data scientists and engineers in a distributed team.

Qualifications

• Bachelor's degree in CS/Engineering or related field.
• Experience in MLOps/DevOps or similar automation role.
• Strong Python scripting and containerization (Docker, Kubernetes).
• Experience with cloud ML services (AWS/Azure/GCP).
• Familiarity with ML 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 security, reliability, and performance of ML infrastructure.

Skills

Python

DevOps

CI/CD

Remote work

Education

Bachelor's degree in CS/Engineering

Tools

Docker

Kubernetes

AWS

Azure

GCP

Job description

Cv Syafiiq Enterprise is seeking a skilled Machine Learning Operations (MLOps) Engineer for a fully remote role. You will bridge ML development and IT operations, deploying, monitoring, and maintaining ML models in production from anywhere.

You will design CI/CD pipelines, automate deployment, and build infrastructure to support the ML lifecycle while collaborating with data scientists and engineers in a distributed team.