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Grab

On-demand parcel delivery in Southeast Asia

Senior Principal Data Scientist - Fulfilment

Applied Machine LearningPosted on Nov 10
Full-timeSingaporeNo salary listed

About the Job

Requirements

  • A PhD in Computer Science, Operations Research, Applied Mathematics, or a related quantitative discipline with at least 10 years of post-degree experience leading complex machine learning research and production initiatives, or a Master's degree with at least 12 years of equivalent experience.
  • Proficiency in reinforcement learning foundations, including Markov Decision Processes, stochastic control, offline reinforcement learning, and reward shaping for sequential multi-objective decision systems.
  • Proven experience deploying production machine learning or reinforcement learning systems operating under real-time constraints, non-stationary data, and distribution shifts.
  • Hands-on expertise with large language model adaptation and alignment, including supervised fine-tuning, parameter-efficient methods such as LoRA and QLoRA, and preference tuning such as RLHF, DPO, or GRPO.
  • Hands-on proficiency in Python, PyTorch, and distributed training or compute platforms such as Ray, DeepSpeed, FSDP, or Megatron-LM.
  • Experience engaging with AI tools and emerging technologies to enhance productivity, improve workflows, and contribute new ideas.

Responsibilities

  • Architect and implement end-to-end reinforcement learning pipelines, including offline reinforcement learning, model-based reinforcement learning, and simulation, to jointly automate pricing, dispatch, and supply repositioning decisions.
  • Design latent world models and spatio-temporal marketplace state representations that capture complex supply-demand interactions and multi-temporal levers.
  • Establish formal off-policy evaluation frameworks, conservative value estimation baselines, and safety guardrails to de-risk live production deployment.
  • Build behavioural simulation systems using fine-tuned open-source large language models to forecast and simulate user and partner decision dynamics.
  • Partner with backend, streaming, and platform engineering teams to deploy low-latency, closed-loop decision agents into high-throughput production environments.
  • Leverage modern generative AI development tools and AI-assisted workflows to accelerate prototyping, code quality, testing, and technical documentation across the team.

About the Company

Grab

On-demand parcel delivery in Southeast Asia

Grab operates a range of services in Southeast Asia, including ride-hailing, food delivery, and logistics. Its GrabExpress on-demand parcel delivery lets customers and businesses send documents and packages through the Grab app, with real-time tracking, options for up to 10 concurrent deliveries, and islandwide coverage (with some restricted areas). The service relies on a large network of delivery partners and charges fees based on distance, time, and item type. Its advantage comes from offering an integrated, all-in-one platform for transportation, meals, and parcel delivery to support the region’s growing e-commerce and urban activity.

Company size
10,001+
Company stage
IPO
Headquarters
Singapore, Singapore
Founded
2012

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