[Data Engineer] Senior / Staff MLOps Engineer (Bangkok Based, relocation provided)

Bangkok, Thailand · Bangkok (One Bangkok Office) · 5+ years experience · Hybrid · Posted Oct 16, 2026

At a glance

At Agoda, we bridge the world through travel. Our story began in 2005, when two lifelong friends and entrepreneurs, driven by their passion for travel, launched Agoda to make it easier for everyone to explore the world.
Today, we are part of Booking Holdings [NASDAQ: BKNG], with a diverse team of over 7,000 people from 90 countries, working together in offices around the globe. Every day, we connect people to destinations and experiences, with our great deals across our millions of hotels and holiday properties, flights, and experiences worldwide.
No two days are the same at Agoda. Data and technology are at the heart of our culture, fueling our curiosity and innovation. If you’re ready to begin your best journey and help build travel for the world, join us.
ML Platform in Agoda
Agoda ML and AI Platform is built on self-managed Kubernetes and powered by Kubeflow, an open-source solution that enables efficient machine learning workflows.
Our AI Ops team combines the best practices of software engineering with data science to help Machine Learning Engineers and Data Scientists work more effectively, meaning we aim to incorporate data/model versioning, collaboration, monitoring etc. in an intuitive way that allows our users to prosper within the field.

The Senior / Staff MLOps Engineer will lead the design, development, and implementation of on-premises MLOps solutions to support machine learning model delivery.
This role involves collaborating with data scientists and software engineers to build scalable data pipelines and model training systems within the Agoda ML and AI Platform.
The position is based in Bangkok, Thailand, with relocation provided.

Lead the design, development, and implementation of on-premises MLOps solutions.
Collaborate with data scientists and software engineers to build scalable data pipelines and model training and deployment systems.
Develop and maintain monitoring and management tools for on-premises MLOps infrastructure.
Work with stakeholders to understand machine learning needs and develop corresponding solutions.
Stay up-to-date with trends in MLOps, machine learning, and AI to share knowledge with the team.
Mentor junior team members to help them grow their skills and expertise.
Troubleshoot and debug user issues.

5+ years of experience in MLOps, Software engineering, Data engineering, or a related field.
Strong programming skills in a modern programming language (Java, Scala, Python, Kotlin).
Hands-on experience with Kubernetes, including deploying and operating workloads, debugging pod failures, and working with core concepts.
Excellent communication and collaboration skills.
Ability to work effectively in a team environment.
Value code simplicity and performance.

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