Remote MLOps Engineer - CI/CD for AI Pipelines

Loker Cirebon; Tegal; Remote; IDR 2,154,399,000 - 2,872,531,000; Full time

Job summary

Loker Cirebon is seeking a highly skilled Machine Learning Operations (MLOps) Engineer to join a globally distributed team working entirely remotely. You will streamline and automate the lifecycle of ML models from development to deployment and monitoring, collaborating with data scientists, software engineers, and IT operations to ensure scalable and reliable AI systems.

Key responsibilities include designing CI/CD pipelines, managing training and deployment infrastructure, and implementing

Qualifications

• Bachelor's degree in Computer Science, Engineering, or related field.
• Proven experience in MLOps, DevOps or related infrastructure roles.
• Strong understanding of ML concepts and workflows.
• Proficiency with cloud platforms and ML services (AWS/Azure/GCP).
• Experience with Docker and Kubernetes.
• Strong scripting skills (Python, Bash).
• Excellent problem-solving and remote collaboration abilities.

Responsibilities

• Design, build, and maintain CI/CD pipelines for machine learning models.
• Implement and manage infrastructure for training, deploying, and serving ML models.
• Develop strategies for model monitoring, performance tracking, and retraining.
• Automate model validation and testing processes.
• Collaborate with data scientists to optimize models for production environments.
• Ensure the scalability, reliability, and security of ML infrastructure.

Skills

CI/CD

Cloud platforms

Python

Docker

Kubernetes

MLOps

Remote collaboration

Education

Bachelor's degree in CS/Engineering

Tools

AWS

Azure

GCP

Job description

Loker Cirebon is seeking a highly skilled Machine Learning Operations (MLOps) Engineer to join a globally distributed team working entirely remotely. You will streamline and automate the lifecycle of ML models from development to deployment and monitoring, collaborating with data scientists, software engineers, and IT operations to ensure scalable and reliable AI systems.

Key responsibilities include designing CI/CD pipelines, managing training and deployment infrastructure, and implementing