Bagging Operator Af

PT Japfa Comfeed Indonesia Tbk; Banyuwangi; Remote; IDR 350,000,000 - 700,000,000; Full time

Job summary

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

You will design and automate ML pipelines, manage infrastructure, and implement best practices for scalability and efficiency. This is an excellent opportunity to drive AI excellence from anywhere and collaborate with data scientists and software

Qualifications

• Bachelor's degree in Computer Science, Engineering, or related technical field.
• Proven experience in MLOps, DevOps, or a similar role focused on automation and infrastructure.
• Strong proficiency in Python and containerization technologies (Docker, Kubernetes).

Responsibilities

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

Skills

MLOps

DevOps

Python

Docker

Kubernetes

AWS

Azure

GCP

ML frameworks

Education

Bachelor's degree in Computer Science or Engineering

Tools

Docker

Kubernetes

Job description

Machine Learning Operations (MLOps) Engineer - Remote

Our client is seeking a skilled Machine Learning Operations (MLOps) Engineer to join their fully remote, high-performing team. This role is essential for bridging the gap between machine learning development and IT operations, ensuring the reliable deployment, monitoring, and maintenance of ML models in production. You will be responsible for building and automating ML pipelines, managing infrastructure, and implementing best practices for scalability and efficiency. This is an excellent opportunity for an experienced engineer to drive operational excellence in AI and contribute to the success of cutting-edge ML applications from anywhere.

About the Role

Our client is seeking a skilled Machine Learning Operations (MLOps) Engineer to join their fully remote, high-performing team. This role is essential for bridging the gap between machine learning development and IT operations, ensuring the reliable deployment, monitoring, and maintenance of ML models in production. You will be responsible for building and automating ML pipelines, managing infrastructure, and implementing best practices for scalability and efficiency. This is an excellent opportunity for an experienced engineer to drive operational excellence in AI and contribute to the success of cutting-edge ML applications from anywhere.

Key Responsibilities

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

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related technical field.
• Proven experience in MLOps, DevOps, or a similar role focused on automation and infrastructure.
• Strong proficiency in scripting languages (e.g., Python) and containerization technologies (e.g., Docker, Kubernetes).
• Experience with cloud platforms (AWS, Azure, GCP) and their ML services.
• Familiarity with ML frameworks and model deployment strategies.
• Excellent problem-solving skills and ability to work independently in a remote setting.

Benefits

• Highly competitive salary and performance-based rewards.
• Fully remote work arrangement, offering exceptional work-life balance and flexibility.
• Comprehensive health, dental, and vision insurance coverage.
• Generous budget for professional development, certifications, and attending virtual conferences.
• Opportunity to work with a talented, globally distributed team on impactful AI projects.