2 days ago
Singapore, SingaporeStaff+
Responsibilities
- Design and implement end-to-end reinforcement learning systems incorporating model-based RL, offline RL, simulation, and online learning.
- Develop latent world models and marketplace state representations for supply-demand interactions, location patterns, and behavioral signals.
- Optimize pricing, dispatching, and supply repositioning decisions across multiple marketplace objectives.
- Create policy evaluation and monitoring frameworks for safe production deployment of decision-making policies.
- Fine-tune large language models for prediction, reasoning, and marketplace simulation using supervised and preference-based alignment methods.
- Design language-model training strategies and integrate RL and LLM systems into real-time production environments with data and backend engineers.
- Lead technical direction for a small team across research and production implementation.
Requirements
- PhD in Computer Science, Operations Research, Applied Mathematics, or a related field, with at least 10 years of experience.
- Proficiency in reinforcement learning fundamentals, including Markov Decision Processes, stochastic control, and reward design.
- Experience building production ML or RL systems using online learning or simulation-based optimization.
- Knowledge of world models, sequential modeling, latent dynamic models, and representation learning.
- Hands-on experience fine-tuning large language models in production, including supervised fine-tuning and RLHF, DPO, or GRPO.
- Experience with parameter-efficient methods such as LoRA, QLoRA, or PEFT and with generative-model evaluation frameworks.
- Experience with distributed training frameworks such as DeepSpeed, FSDP, or Megatron-LM.
- Proficiency in Python and PyTorch or TensorFlow.
- Experience with scalable computing platforms such as Spark or Ray.
- Ability to translate ambiguous business problems into concrete modeling tasks, data requirements, and success criteria.
Benefits
- Term Life Insurance and comprehensive Medical Insurance.
- GrabFlex benefits package customization.
- Parental leave, Birthday leave, and Love-all-Serve-all volunteering leave.
- Confidential Grabber Assistance Programme.
- FlexWork arrangements with differentiated hours.
- The role works from Grab’s One-North Singapore office.
Tech Stack
Categories
AI ResearchML Engineering
About Grab
Grab builds a Southeast Asia superapp for mobility, deliveries, and financial services, serving consumers, drivers, merchants, and enterprises. It monetizes via ride and delivery commissions, merchant services (such as ads and subscriptions), and payments and digital banking products. Founded in 2012 and headquartered in Singapore, Grab operates across multiple Southeast Asian markets and is publicly listed on NASDAQ.