Remote MLOps Engineer — AI Model Deployment & CI/CD

Dwikarsa Sejahtera Abadi; Sukabumi; Remote; IDR 1,592,638,000 - 2,300,478,000; Full time

Benefits offered by this job

Fully remote work

Professional development budget

Job summary

Dwikarsa Sejahtera Abadi seeks a highly skilled MLOps Engineer to join a globally distributed, fully remote team. You will design, build, and maintain CI/CD pipelines for ML models and work with data scientists to deploy and monitor AI systems.

The role requires cloud proficiency (AWS/Azure/GCP), Docker, Kubernetes, and strong Python/Bash scripting. You’ll contribute to scalable, secure ML infrastructure from your home office, with flexible hours and opportunities to develop with cutting-edge

Qualifications

• 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.

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

CI/CD

Python

Education

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

Tools

Docker

Kubernetes

AWS

Azure

GCP

Job description

Dwikarsa Sejahtera Abadi seeks a highly skilled MLOps Engineer to join a globally distributed, fully remote team. You will design, build, and maintain CI/CD pipelines for ML models and work with data scientists to deploy and monitor AI systems.

The role requires cloud proficiency (AWS/Azure/GCP), Docker, Kubernetes, and strong Python/Bash scripting. You’ll contribute to scalable, secure ML infrastructure from your home office, with flexible hours and opportunities to develop with cutting-edge