Remote MLOps Engineer: Build & Automate AI Pipelines

Pt Rosin Trading Internasional; Indonesia; Remote; IDR 1,085,384,000 - 1,628,075,000; Full time

Benefits offered by this job

Competitive salary

Fully remote work

Health, dental, and vision insurance

Professional development budget

Global distributed team

Job summary

Pt Rosin Trading Internasional 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 models in production while building scalable ML pipelines and infrastructure.

Collaborate with data scientists and software engineers to ensure reliable deployments and robust monitoring, logging, and alerting. This is a remote opportunity with a global, high-performing team.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related technical field.
• Proven experience in MLOps, DevOps, or similar automation and infrastructure roles.
• Strong Python scripting and containerization with Docker and Kubernetes.
• Experience with cloud platforms (AWS, Azure, GCP) and ML deployment skills.

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 engineers to troubleshoot production issues.
• Implement monitoring, logging, and alerting for ML systems.
• Ensure security, reliability, and performance of ML infrastructure.

Skills

Problem-solving

Independent work

Python scripting

Education

Bachelor's degree in Computer Science, Engineering, or related field

Tools

Docker

Kubernetes

AWS

Azure

GCP

Job description

Pt Rosin Trading Internasional 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 models in production while building scalable ML pipelines and infrastructure.

Collaborate with data scientists and software engineers to ensure reliable deployments and robust monitoring, logging, and alerting. This is a remote opportunity with a global, high-performing team.