Machine Learning Engineer (User Trust)

Get to know our Team:

The User Trust team acts as guardians of all our users on Grab. We leverage our rich datasets to find solutions to problems ranging from safety to fraud. We’re a hands on team interested in the end to end data lifecycle: from wrangling data to understanding the tradeoffs between model complexity and deployment in production. If you’re passionate about solving complex problems with immediate real-world impact, we want you!

Get to know the Role:

• Work on problems that run the gamut from data science to deploying and monitoring models in production.

• Build and deploy scalable machine learning models to enable our fraud, risk and safety systems.

• Analyze data and define metrics for feature evaluation and model performance.

• Design and implement robust data pipelines.

• Identify and build new approaches and methods for machine learning as we grow.

The must haves:

• Minimum 5 years of experience building machine learning models in production, or an advanced degree in a quantitative field with at least 2 years of experience.

• Good understanding of machine learning models, feature engineering, and other practical issues, such as overfitting.

• Solid engineering and coding skills. And the ability to write high performance production code. Experience in Go, Python Scala and other equivalent language is a plus.

• Experience with MapReduce, Spark and Hive is a plus.

• Self-motivated, independent learner, and enjoy sharing knowledge with team members.

• Detail-oriented and efficient time manager in a dynamic and fast-paced working environment.