Remote MLOps Engineer: Build & Scale AI Pipelines

Cari; Tegal; Remote; IDR 1,615,799,000 - 2,333,932,000; Full time

Benefits offered by this job

Competitive salary

Fully remote work

cutting-edge MLOps technologies

Professional development support

Collaborative team culture

Job summary

Cari is seeking a skilled 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 and engineers.

The role requires cloud expertise (AWS/Azure/GCP), Docker and Kubernetes, Python or Bash scripting, and strong problem-solving in a remote, collaborative environment. If you thrive with AI deployments, apply now.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or 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

Remote collaboration

Problem-solving

Teamwork

Education

Bachelor's degree in Computer Science or related field

Tools

Docker

Kubernetes

AWS

Azure

GCP

Job description

Cari is seeking a skilled 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 and engineers.

The role requires cloud expertise (AWS/Azure/GCP), Docker and Kubernetes, Python or Bash scripting, and strong problem-solving in a remote, collaborative environment. If you thrive with AI deployments, apply now.