Pe Operator,Pe Extrusion,Bm

Rge Pte Ltd; Jambi; Remote; IDR 2,123,518,000 - 3,008,317,000; Full time

Benefits offered by this job

Fully remote work arrangement

Professional development budgets

Job summary

Rge Pte Ltd is seeking a highly skilled Machine Learning Operations (MLOps) Engineer to join a globally distributed, fully remote team. You will design, build, and maintain CI/CD pipelines for ML models and collaborate with data scientists to deploy and monitor them at scale.

This role focuses on automation, reliability, and security, with experience across AWS/Azure/GCP, Docker, Kubernetes, and scripting in Python or Bash, all from a remote home office.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related field.
• Experience in MLOps, DevOps, or related infrastructure engineering roles.
• Proficiency with cloud platforms (AWS, Azure, GCP) and their ML services.
• Experience with Docker and Kubernetes.

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

MLOps experience

DevOps

Cloud concepts

CI/CD

Python

Bash

Remote collaboration

Education

Bachelor's degree in CS/Engineering/related

Tools

Docker

Kubernetes

AWS

Azure

GCP

Job description

Machine Learning Operations (MLOps) Engineer (Remote)

Our client is seeking a highly skilled Machine Learning Operations (MLOps) Engineer to join their globally distributed team, working entirely remotely. You will be responsible for streamlining and automating the lifecycle of machine learning models, from development and training to deployment and monitoring. This role is essential for ensuring that our AI solutions are deployed efficiently, reliably, and at scale. You will work closely with data scientists, software engineers, and IT operations to build and maintain robust MLOps pipelines, fostering a culture of continuous integration and continuous delivery for AI systems, all from your home office.

About the Role

Our client is seeking a highly skilled Machine Learning Operations (MLOps) Engineer to join their globally distributed team, working entirely remotely. You will be responsible for streamlining and automating the lifecycle of machine learning models, from development and training to deployment and monitoring. This role is essential for ensuring that our AI solutions are deployed efficiently, reliably, and at scale. You will work closely with data scientists, software engineers, and IT operations to build and maintain robust MLOps pipelines, fostering a culture of continuous integration and continuous delivery for AI systems, all from your home office.

Key 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.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related field.
• Proven experience in MLOps, DevOps, or related infrastructure engineering roles.
• Strong understanding of machine learning concepts and workflows.
• Proficiency with cloud platforms (AWS, Azure, GCP) and their ML services.
• Experience with containerization (Docker) and orchestration (Kubernetes).
• Solid scripting skills (e.g., Python, Bash).
• Excellent problem-solving skills and the ability to thrive in a remote, collaborative setting.

Benefits

• Competitive salary and comprehensive benefits package.
• Fully remote work arrangement, providing ultimate flexibility.
• Opportunities to work with cutting-edge MLOps technologies.
• Professional development support and training budgets.
• A collaborative and innovative team culture focused on empowering AI development.