Machine Learning Engineer, Foundation Models

Get to Know the Team

At the AI Automation Team, we strive 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 innovative ML and experiment platforms.

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 as well as scalable data and model pipelines. The ideal candidate should have a strong background in modern machine learning and foundation model techniques, including pretraining, multimodality and finetuning. They should also have substantial experience in developing scalable machine learning solutions for complex problems and a solid 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 and optimize model architectures for specific business use cases.
• You will create and implement model compression techniques (quantization, pruning, distillation).
• You will build evaluation frameworks for model performance and quality assessment.
• You will collaborate with cross-functional teams to understand their requirements and integrate foundation models into applications.
• You will engage in code and design reviews with peers to uphold high-standard engineering practices.