Senior Machine Learning Engineer (Fulfillment)

Get to Know the Team

The Fulfilment Tech Family is a foundational part of Grab, enabling seamless coordination between our diverse marketplaces across Southeast Asia. We design real-time, distributed systems and machine learning solutions to process hundreds of millions of requests per day, driving efficient supply allocation, pricing, and order matching. Our mission:

• Deliver best-in-class products for our driver-partners.
• Maximise efficiency in fulfilling consumer demand – rain or shine.
• Create sustainable, efficient marketplaces that balance experience and cost for all stakeholders.

We're looking for a Senior Data Scientist to join our Fulfilment team and take the lead in Fulfilment strategy optimization – bringing existing optimisation and automation of our pricing, dispatch and supply management policies to the next level.

Get to Know the Role

You'll optimize cross-system fulfilment strategies, and lead model development with user and driver behavioural prediction, optimisation and reinforcement learning (RL) techniques. Your primary objective will be to enhance marketplace operations by constructing interpretable, adaptable multi-agent RL systems or decision agents that can manage diverse objectives and disruptions.

You'll report to the Head of Data Science and work onsite at Grab's One North Singapore office.

The Critical Tasks You Will Perform

• You'll design and implement cross-system strategies to improve operational efficiency in fulfilling user demands and boosting driving utilisation.
• You'll build advanced DL and LLM models to capture the spatial-temporal patterns of dynamic marketplace conditions.
• You'll develop advanced ML/DL models to predict user and driver behaviours, and use the behavioural insights to inform decision-making and platform interventions.
• You'll build and deploy interpretable, adaptable optimisation models, RL systems or decision agents, that can handle multi-objectives and real-world disruptions.
• You'll collaborate with machine learning engineers and backend engineers to integrate the ML/DL, optimization or RL models into real-time production systems.
• You'll create technical documents outlining the methodologies and findings of your work. You'll also present solutions to non-technical stakeholders.