Intern, Machine Learning Engineer

Descripción del puesto:

Job Description

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

Requerimientos del candidato/a:

Qualifications

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