Ai Engineer – Is/It International

Thales Group; Jakarta Pusat; Hybrid; IDR 300,000,000 - 600,000,000; Full time

Job summary

Thales Group in Tangerang,Banten, ID is seeking a Senior AI Engineer specialized in Machine Learning Operations (MLOps). This role focuses on building, automating, and scaling ML deployment, monitoring, and management infrastructure in production environments.

You will bridge data science and software engineering, ensuring robust, reliable AI solutions. Requires 5+ years in software/DevOps/ML with strong MLOps focus and cloud experience.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related quantitative field.
• 5+ years in software engineering, DevOps, or ML engineering with MLOps focus.
• Proven experience building and managing CI/CD pipelines for ML models.
• Proficiency in Python and containerization (Docker, Kubernetes).

Responsibilities

• Design and manage robust MLOps pipelines across the ML lifecycle.
• Automate deployment, testing, monitoring, and retraining of ML models.
• Develop and maintain ML-focused CI/CD pipelines.
• Implement IaC for ML environments.
• Monitor production model performance and drift, retraining as needed.
• Collaborate with data scientists and software engineers to move experiments to production.
• Manage cloud-based ML infrastructure (AWS, Azure, GCP).
• Ensure scalability, reliability, and security of ML systems.
• Troubleshoot ML deployments and infra issues.
• Stay current with MLOps tools and best practices.

Skills

Python

CI/CD for ML

MLOps

DevOps

Communication

Team collaboration

Education

Bachelor's or Master's in CS/Engineering

Tools

Docker

Kubernetes

Terraform

Ansible

Airflow

Kubeflow

TensorFlow

PyTorch

scikit-learn

AWS

Azure

GCP

Job description

Senior AI Engineer - Machine Learning Operations (MLOps)

About the Role Our client, a leading innovator in applied AI, is seeking a Senior AI Engineer with specialized expertise in Machine Learning Operations (MLOps) to join their collaborative team in **Tangerang, Banten, ID**. This crucial role focuses on building, automating, and scaling the infrastructure required to deploy, monitor, and manage machine learning models in production environments. You will bridge the gap between data science and software engineering, ensuring that our AI solutions are robust, reliable, and performant. This is an exciting opportunity to significantly impact the efficiency and effectiveness of our AI deployments in the **Tangerang**.

Key Responsibilities

• Design, implement, and manage robust MLOps pipelines for the entire ML lifecycle, from development to production.
• Automate the deployment, testing, monitoring, and retraining of machine learning models.
• Develop and maintain CI/CD pipelines specifically for ML workflows.
• Implement infrastructure as code (IaC) for ML environments.
• Monitor model performance in production and implement strategies for drift detection and retraining.
• Collaborate with data scientists and software engineers to streamline the path from experimentation to production.
• Manage and optimize cloud-based ML infrastructure (e.g., AWS SageMaker, GCP AI Platform, Azure ML).
• Ensure the scalability, reliability, and security of ML systems.
• Troubleshoot and resolve issues related to ML deployments and infrastructure.
• Stay current with the latest MLOps tools, technologies, and best practices.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative field.
• 5+ years of experience in software engineering, DevOps, or ML engineering, with a strong focus on MLOps.
• Proven experience in building and managing CI/CD pipelines for machine learning models.
• Proficiency in Python and experience with containerization technologies (Docker, Kubernetes).
• Hands‑on experience with cloud platforms (AWS, Azure, GCP) and their ML services.
• Familiarity with ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Experience with workflow orchestration tools (e.g., Airflow, Kubeflow).
• Understanding of infrastructure automation tools (e.g., Terraform, Ansible).
• Strong analytical and problem‑solving skills.
• Excellent communication and collaboration skills, suitable for a hybrid work environment in **Tangerang**, **Banten**.