Job Description

Company DescriptionAbout Grab and Our WorkplaceGrab 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 TeamThe mission of the Machine Learning Pipeline (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 RoleAs a Senior Machine Learning Engineer in our ML Pipeline team, you will be responsible for designing, implementing, rolling out, and evangelizing cutting-edge ML&AI platforms for large scale workloads at Grab.The Critical Tasks You Will Perform

• You will write production-grade code, at scale.
• You will develop platform applications from infrastructure to frontend in full stack.
• You will setup and define standards for complex pipelines including data engineering, feature engineering, model training, model quality verification, model deployment etc.
• You will automate cloud infrastructure provisioning and deployments of ML pipelines.
• You will reason about how to use appropriate frameworks, algorithms, and data structures.

QualificationsWhat Essential Skills You Will Need

• At least 4years of relevant experience in machine learning engineering, ML Ops, LLM Ops or similar roles
• Proficient in at least one programming language such as Golang, Python, Scala, or Java
• Prior experience designing, implementing, and deploying large-scale machine learning systems
• Extensive knowledge of ML frameworks such as TensorFlow, PyTorch, Spark, etc
• Understanding of distributed systems, cloud platforms (specifically, AWS), and containerization technologies like Kubernetes
• Familiarity with machine learning lifecycle management, including feature engineering, model training, validation, deployment, A/B testing, monitoring, and retraining
• Prior working experience with building GenAI or LLM Ops platforms.

Additional InformationLife at GrabWe care about your well-being at Grab, here are some of the global benefits we offer:

• We have your back with Term Life Insurance and comprehensive Medical Insurance.
• With GrabFlex, create a benefits package that suits your needs and aspirations.
• Celebrate moments that matter in life with loved ones through Parental and Birthday leave, and give back to your communities through Love-all-Serve-all (LASA) volunteering leave
• We have a confidential Grabber Assistance Programme to guide and uplift you and your loved ones through life\'s challenges.

What we stand for at GrabWe are committed to building an inclusive and equitable workplace that enables diverse Grabbers to grow and perform at their best. As an equal opportunity employer, we consider all candidates fairly and equally regardless of nationality, ethnicity, religion, age, gender identity, sexual orientation, family commitments, physical and mental impairments or disabilities, and other attributes that make them unique.

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