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Post Date

2022-Dec-20

Close Date

2023-Jan-31

Job Type

FULLTIME

Salary

SGD 5000-12000 per MONTH

Location

One North, , Singapore

Company Description

Grab is more than just the leading ride-hailing and mobile payments platform in Southeast Asia. We use data and technology to improve everything from transportation to payments and financial services across a region of more than 620 million people. We work with governments, drivers, passengers, merchants, and the community, to solve critical problems in Southeast Asia. Grab began as a taxi-hailing app in 2012, but we have since extended our product platform to include GrabCar, GrabShare, GrabBike, GrabHitch, GrabExpress, GrabFood, GrabCoach, GrabShuttle, GrabCycle. We recently launched our fintech platform – GrabFinancial, which consists of payments, lending and insurance. Our latest addition is GrabVentures, an in-house incubation platform. We are focused on pioneering new commuting and payment alternatives for drivers and passengers with an emphasis on convenience, safety, and reliability. Currently, we offer services in 8 countries. Our R&D offices are in Singapore, Seattle, Beijing, Bangalore, Jakarta and Vietnam. We aspire to unlock the true potential of Southeast Asia and look for like-minded individuals to join us on this ride.

Job Description

    Machine Learning PlatformThe Machine Learning Platform team seeks to develop scalable and robust machine learning infrastructure and tooling at Grab, empowering our users to deploy Machine Learning models at scale in production from end to end in a safe and continuous manner.  Get to know the Role:
    • Work on problems that run the gamut from building Machine Learning / Deep Learning models to developing full-scale production systems.
    • Train and predict on Grab’s unique large-scale data sets, leveraging Grab’s unique position as South-East Asia’s most popular SuperApp.
    • Build, deploy, maintain and optimize machine learning-based solutions, including computer vision and search-related applications.
    • 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.
     Get to know the Role (ML Platform):
    • 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.
    • 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.

Requirements

    • 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.
    • Solid 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.

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