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A leading superapp company in Petaling Jaya is seeking a Machine Learning Engineer to develop and maintain machine learning infrastructure. This role involves designing robust solutions for model training and deployment while ensuring system reproducibility. Candidates should hold a degree in Computer Science or Software Engineering and have at least 1 year of experience in fullstack development. Ideal candidates will have strong skills in Python, Kubernetes, and GitOps, along with a solid understanding of MLOps. Competitive benefits are offered.
Grab is Southeast Asia's leading superapp. From getting your favourite meals delivered to helping you manage your finances and getting around town hassle-free, we've got your back with everything. In Grab, purpose gives us joy and habits build excellence, while harnessing the power of Technology and AI to deliver the mission of driving Southeast Asia forward by economically empowering everyone, with heart, hunger, honour, and humility.
Get to Know the Team
The Grab ML Platform team empowers teams across the company to harness the power of machine learning. We're building cutting-edge tools and infrastructure to drive innovation and automation throughout Grab.
Get to Know the Role
As a machine learning engineer in the ML Platform team at Grab, you will contribute to the creation and maintenance of our machine learning infrastructure. You will help drive the set-up of robust and scalable solutions for model training, deployment, and monitoring.
You will report to the Senior Machine Learning Engineering and work onsite at our office based in Petaling Jaya
The Critical Tasks You Will Perform
What Essential Skills You Will Need
Life at Grab
We care about your well-being at Grab, here are some of the global benefits we offer:
What We Stand For At Grab
We are committed to building an inclusive and equitable workplace that provides equal opportunity for Grabbers to grow and perform at their best. We consider all candidates fairly and equally regardless of nationality, ethnicity, race, religion, age, gender, family commitments, physical and mental impairments or disabilities, and other attributes that make them unique.