Intern, Machine Learning Engineer

About Grab and Our Workplace

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

At the AI Automation Team, we aim to stay ahead by building comprehensive automated ML/AI solutions to solve complex challenges in Grab's marketplace. Our team focuses on areas like experiments, embeddings, recommendations, and large-scale marketplace optimizations. We're excited to welcome machine learning engineers who are passionate about advancing our mission by designing and refining ML and experiment platforms.

This is a paid internship role. You will report to our Senior Machine Learning Engineering Manager and be based onsite at our office in Petaling Jaya, Selangor.

Get to Know the Role

This is an applied research role aimed at developing foundation model solutions for Grab. Responsibilities include proposing and implementing efficient foundation model architectures, scalable data and model pipelines. You have a good exposure to modern machine learning and foundation model techniques, including pretraining, multimodality and finetuning. You should also have substantial exposure in developing scalable machine learning solutions for complex problems and an understanding of the software development lifecycle and engineering practices.

The Critical Tasks You Will Perform

• You will design and implement efficient training pipelines for foundation models and multimodal models.
• You will develop model architectures for specific business use cases.
• You will create model compression techniques (quantization, pruning, distillation).
• You will build evaluation frameworks for model performance and quality assessment.
• You will collaborate with crossfunctional teams to understand their requirements and integrate foundation models into applications.
• You will participate in code and design reviews with peers to uphold high-standard engineering practices.

What Essential Skills You Will Need

• You can start from May 2026 onwards with a minimum duration of 3 months
• Your degree in Statistics, Mathematics, Computer Science, or a related field will support your technical insights needed for this role.
• You have interest in machine learning, with focus on deep learning and transformer architectures.
• You have good theoretical knowledge of recent machine learning developments, including foundational models, transformers, and data-centric AI.
• You have interest in learning to apply machine learning architectures to specific problems beyond mere fine-tuning, which are crucial for the role's responsibilities.
• You have exposure in programming skills like Python, PyTorch or TensorFlow in training large-scale models.
• You have understanding of engineering practices and design patterns, with experience writing readable, maintainable, and testable code.
• You have good exposure in ML deployment platforms and MLOps.

 

Life at Grab

We 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.
• Balancing personal commitments and life's demands are made easier with our FlexWork arrangements such as differentiated hours

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.