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.
Job DescriptionGet to know the Team
The mission of the ML Pipeline team at Grab is to empower machine learning engineers, data scientists, data analysts, and data engineers to test-and-learn their ideas and productionise them at scale. The team develops tools, systems and automation to increase productivity throughout the ML and AI development lifecycle.
Get to know the Role
As a Machine Learning Engineer in our ML Pipeline team, you will be responsible for contributing to the design, implementation, and rollout of cutting-edge ML&AI platforms for large-scale workloads at Grab.
The Critical Tasks You Will Perform
Write production-grade code, perform code reviews and ensure exceptional code quality
Build robust, lasting, and scalable products Iterate quickly without compromising quality
Setup and define standards for complex pipelines including data engineering, feature engineering, model training, model quality verification, model deployment, etc.
Automate cloud infrastructure provisioning and deployments of ML pipelines
What Essential Skills You Will Need
A bachelors/Master degree in computer science, machine learning or related fields
3+ years of machine learning experience in industry
Proficient in at least one programming language such as Golang, Python, Scala, or Java
Strong understanding of machine learning approaches and algorithms
Extensive knowledge of ML frameworks such as TensorFlow, PyTorch, Spark ML, scikit-learn, or related frameworks
Experiences of Docker, Kubernetes, Ray, NoSQL solutions, Memcache/Redis, cloud platforms (specifically, AWS)
Familiarity with machine learning lifecycle management, including feature engineering, model training, validation, deployment, A/B testing, monitoring, and retraining
Experienced in MLOps and managing production machine learning lifecycle is a plus
Experience developing machine learning models for ranking, recommendations, search, content understanding, image generation, or other relevant applications of machine learning is a plus
Prior working experience with building GenAI or llmops platforms is a plus
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.
Top Skills
What We Do
Grab is more than just the leading ride-hailing and mobile payments platform in Southeast Asia.
