Remote MLOps Engineer: Build & Scale AI Pipelines

Jurang Wholesale Limited; Kota Medan ᯔᯩᯑᯉ᯲; Remote; IDR 250,000,000 - 500,000,000; Full time

Benefits offered by this job

Competitive salary and comprehensive福利

Fully remote work arrangement

Cutting-edge MLOps technologies

Professional development support and培训

Job summary

Jurang Wholesale Limited is seeking a highly skilled Machine Learning Operations (MLOps) Engineer to join a globally distributed, fully remote team. You will design and optimize CI/CD pipelines, manage ML training, deployment, and monitoring, and collaborate with data scientists and software engineers from your home office.

The role requires a strong background in MLOps or DevOps, experience with Docker, Kubernetes, cloud services (AWS/Azure/GCP), and solid Python/Bash scripting.

Qualifications

• Bachelor's degree in CS, Engineering, or related field.
• Proven experience in MLOps/DevOps or related infra roles.
• Strong ML concepts and workflows knowledge.
• Experience with AWS, Azure, or GCP ML services.
• Docker and Kubernetes experience; scripting in Python or Bash.
• Strong problem-solving and remote collaboration skills.

Responsibilities

• Design, build, and maintain CI/CD pipelines for ML models.
• 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.
• Ensure the scalability, reliability, and security of ML infrastructure.

Skills

MLOps

DevOps

Python

Bash

Cloud platforms

Education

Bachelor's degree in Computer Science or related field

Tools

Docker

Kubernetes

Job description

Jurang Wholesale Limited is seeking a highly skilled Machine Learning Operations (MLOps) Engineer to join a globally distributed, fully remote team. You will design and optimize CI/CD pipelines, manage ML training, deployment, and monitoring, and collaborate with data scientists and software engineers from your home office.

The role requires a strong background in MLOps or DevOps, experience with Docker, Kubernetes, cloud services (AWS/Azure/GCP), and solid Python/Bash scripting.