Machine Learning Engineer

The Engineering department oversees all Agoda’s ML and software related requirements. Our goal is to enable and increase Agoda’s business through creative approaches and the implementation of powerful resources such as operational and analytical databases, ML driven solutions, queue systems and data monitoring tools. We hire the brightest minds from around the world to take on this challenge and equip them with the knowledge and tools that contribute to their personal growth and success while supporting our company’s culture of diversity and experimentation. The role the engineering team plays at Agoda is critical as business users, product managers, and many others rely on us to empower their decision making. We are equally dedicated to our customers by improving their search experience with faster results and protecting them from any fraudulent activities. Data is interesting only when you have enough of it, and we have plenty. This is what drives up the challenge as part of the ML engineering squad, but also the reward. We work across structured and non-structured data at scale. For example, our current ML models process millions of images every day to try and enhance the experience that our users get from our app.

Why Agoda Engineering Team (ML role)?

Our engineering teams are at the intersection of business analytics, ml engineering, data warehousing and software engineering. Our job involves dealing with distributed systems, stream processing, ml modeling and computation at tens of PB Scale. We focus on software engineering related to data replication, storage, centralized computation, and Data API’s. By providing our users with ML products/tools, shared frameworks, and ML services, we enable our company to validate strategic decisions, make smarter choices, and react to the fast-changing world. We are a small but passionate team with people from different nationalities working together on a single goal.

In this Role, you will get to:

• Lead the team technically in improving scalability, stability, accuracy, speed and efficiency of our existing ML systems and processes.
• Build, administer and scale ML processing pipelines.
• Be comfortable navigating the following technology stack: Python3, Pyspark, scripting (Bash/Python), Hadoop, SQL, S3 etc.
• Should be able to understand internals of ML models such as Random Forest, CNN, Regression models, etc
• Design, build, test and deploy new libraries, frameworks or full systems for our core systems while keeping to the highest standards of testing and code quality.
• Work with experienced engineers and product owners to identify and build tools to automate many large-scale data management / analysis tasks.
• We believe in end-to-end ownership; this role will involve taking ML models to production at a scale.