The new R&D center would focus on areas like machine learning.
Singapore-based ride-hailing giant Grab has launched an R&D center in Kuala Lumpur, Malaysia, where the company was first founded in 2012. The new R&D center is Grabś seventh globally, whereas other centers are based in Bangalore, Beijing, Ho Chi Minh City, Jakarta, Seattle, and Singapore.
The company to hire about 100 employees
Reportedly, the Malaysian center would hire 100 tech employees in its first year of operations, including software engineers, data scientists, and data analysts. The team will focus on developing and enhancing real-time communications features such as VOIP calls via GrabChat, as well as build other web features.
Grab to focus on controlling car driver’s fatigue level
According to Grab, they will also develop new safety measures through machine learning. An example of this is Grabś Driver Fatigue feature, which calculates a “fatigue score” based on factors like how long the driver has been on the road, time of day, rest between shifts and even his or her age and profile. When a driver hits a high fatigue threshold, they will be sent a notification to take a break.
An opportunity for Malaysia’s top tech talent to put their skills
DiteshGathani, Head of Engineering at Grab, stated, “By setting up an R&D center in Malaysia, we want to play a part in developing deep tech talent in the country, particularly in areas like machine learning.” Moreover, he added, ¨We also hope that through Grab, Malaysia’s top tech talent will have the opportunity to put their skills to bear against solving complex, real-world issues right here at home,¨ he added.
Grab to boost its AI capabilities
Grab plans to add 1,000 new tech roles in 2019, in a bid to fuel continued development of its GrabPlatform, which is a suite of APIs for partners to integrate their services with Grab. Additionally, the company is also boosting its AI capabilities so it can leverage its vast trove of data to not only improve and develop new services but also to tackle complex problems such as congestion and financial inclusion.
