- Singapore, Singapore
- Senior
- 10+ years
Lead the design and implementation of reinforcement learning and large language model systems for Grab's marketplace optimization, serving as a technical lead for a small team and reporting to the Head of Data Science.
Responsibilities
- Design and implement end-to-end RL systems that combine model-based RL, offline RL, simulation, and online learning into a unified training pipeline.
- Build latent world models and marketplace state representations that capture supply-demand interactions, location-based patterns, and behavioural signals from users and drivers.
- Develop systems that optimize across multiple marketplace levers simultaneously—pricing, dispatching, and supply repositioning.
- Create policy evaluation frameworks and establish monitoring systems that allow safe deployment of new decision-making policies in production.
- Fine-tune open-source large language models on domain-specific data to build capabilities for prediction, reasoning, and simulation within marketplace applications.
Requirements
- PhD in Computer Science, Operations Research, Applied Mathematics, or related field