Job Description

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Life at Grab

At Grab, every Grabber is guided by The Grab Way, which spells out our mission, how we believe we can achieve it, and our operating principles - the 4Hs: Heart, Hunger, Honour and Humility. These principles guide and help us make decisions as we work to create economic empowerment for the people of Southeast Asia.

Get to know the Team

Grab's Data Science Teams work on some of the most challenging and fascinating problems in transport, economics, logistics, and the space around. Our data scientists apply a myriad of advanced techniques to solve complicated and challenging business problems. The ML Platform team seeks to develop scalable and robust machine learning infrastructure and tooling at Grab, empowering our users to deploy ML models at scale in production from end to end in a safe and continuous manner.

Get to know the Role:

Be involved in the end to end lifecycle of Machine Learning, understanding the Data Science journey and building the right tools for our users

Develop tools and services that enable ML practitioners to build robust machine learning pipelines that adhere to the principles of continuous delivery

The Day-to-Day Activities:

Build and maintain scalable and flexible model training frameworks using containerisation technologies such as Kubernetes, allowing users to run heterogeneous workloads using the right open source technologies

Build and maintain a cost efficient model serving platform at scale, flexible and robust enough to scale up and down depending on traffic patterns

Collaborate with data scientists and ML engineers from different functions to empower them to deploy their machine learning solutions to production to solve business problems

The Must-Haves:

Bachelor/Master/PhD Degree in Computer Science, Math, EE or similar field.

Minimum 2 years experience as a software engineer writing production code

Solid software engineering and coding skills. In addition to Python, experience in at least one backend language like Go, Scala, Java, C++ or other is required

Decent understanding of Machine Learning / Deep Learning and the existing frameworks such as Tensorflow and PyTorch

Strong understanding of distributed ETL frameworks like Spark or Scalding

Experience with cloud-based big data and machine learning services is a plus

Self-motivated, curious, team-player, problem solver

Detail-oriented and focused in a dynamic and fast-paced working environment.

Our Commitment

We are committed to building diverse teams and creating an inclusive workplace that enables all Grabbers to perform at their best, regardless of nationality, ethnicity, religion, age, gender identity or sexual orientation and other attributes that make each Grabber unique.