Remote MLOps Engineer Trainee

Jurang Wholesale Limited; Indonesia; Remote; IDR 446,400,000 - 781,200,000; Full time

Benefits offered by this job

Fully remote

Training budget

Cutting-edge MLOps tech

Job summary

Jurang Wholesale Limited is seeking an experienced MLOps Engineer to join a globally distributed team working fully remotely. You will streamline the lifecycle of ML models from development to deployment and monitoring, collaborating with data scientists and software engineers to build robust pipelines.

The role emphasizes CI/CD, scalable cloud infrastructure, and reliable ML service delivery, with strong emphasis on remote collaboration and cutting-edge MLOps practices.

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

DevOps

Cloud Platforms (AWS/Azure/GCP)

Docker

Kubernetes

Python

CI/CD pipelines

Model monitoring

Education

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

Tools

Docker

Kubernetes

AWS

Azure

GCP

Job description

Jurang Wholesale Limited is seeking an experienced MLOps Engineer to join a globally distributed team working fully remotely. You will streamline the lifecycle of ML models from development to deployment and monitoring, collaborating with data scientists and software engineers to build robust pipelines.

The role emphasizes CI/CD, scalable cloud infrastructure, and reliable ML service delivery, with strong emphasis on remote collaboration and cutting-edge MLOps practices.