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
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 qualityBuild robust, lasting, and scalable products Iterate quickly without compromising qualitySetup 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 pipelinesWhat Essential Skills You Will Need
Bachelor's degree in Computer Science, Computer Engineering, or a related fieldProficient in at least one programming language such as Golang, Python, Scala, or JavaStrong understanding of machine learning approaches and algorithmsKnowledge of ML frameworks such as TensorFlow, PyTorch, Spark ML, scikit-learn, or related frameworksBasic understanding of Docker, Kubernetes, Ray, NoSQL solutions, Memcache/Redis, cloud platforms (specifically, AWS)Knowledge of the machine learning lifecycle, including feature engineering, model training, validation, deployment, A/B testing, monitoring, and retrainingInternship or project experience in machine learning, GenAI or related fields is a plusStrong analytical, critical thinking, and communication skillsOur 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.#J-18808-Ljbffr
Built at: 2025-03-28T06:11:04.509Z