Additionalinformation

Additional Information

Life at Grab

We care about your well-being at Grab, here are some of the global benefits we offer:

• We have your back with Term Life Insurance and comprehensive Medical Insurance.
• With GrabFlex, create a benefits package that suits your needs and aspirations.
• Celebrate moments that matter in life with loved ones through Parental and Birthday leave, and give back to your communities through Love-all-Serve-all (LASA) volunteering leave
• We have a confidential Grabber Assistance Programme to guide and uplift you and your loved ones through life's challenges.
• Balancing personal commitments and life's demands are made easier with our FlexWork arrangements such as differentiated hours

What We Stand For At Grab

We are committed to building an inclusive and equitable workplace that provides equal opportunity for Grabbers to grow and perform at their best. We consider all candidates fairly and equally regardless of nationality, ethnicity, race, religion, age, gender, family commitments, physical and mental impairments or disabilities, and other attributes that make them unique.

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Company Description

About Grab and Our Workplace

Grab is Southeast Asia's leading superapp. From getting your favourite meals delivered to helping you manage your finances and getting around town hassle-free, we've got your back with everything. In Grab, purpose gives us joy and habits build excellence, while harnessing the power of Technology and AI to deliver the mission of driving Southeast Asia forward by economically empowering everyone, with heart, hunger, honour, and humility.

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Job Description

Get to Know the Team

The Fulfilment Tech Family builds distributed systems and machine learning platforms that power Grab's multi-sided marketplace across Southeast Asia. We process hundreds of millions of real-time requests each day to manage supply allocation, dispatch, order matching, and dynamic pricing across mobility and deliveries. Our mission is to balance customer reliability, driver-partner earnings, and operational efficiency under volatile real-world conditions. We foster a collaborative, research-to-production culture focused on scalable algorithmic impact.

Get to Know the Role

As Senior Principal Data Scientist, you will be the senior individual contributor lead architecting Grab's next generation of autonomous marketplace decisioning systems. Working at the intersection of reinforcement learning, latent world models, and generative AI, you will guide technical strategy and translate research into production systems serving millions of users. You will be the technical lead for a specialised team of scientists and engineers, reporting directly to the Head of Data Science. You will also base full-time onsite at Grab's One-North office in Singapore. If you are passionate about pioneering real-time, learning-driven marketplace systems at massive scale, join us!

The Critical Tasks You Will Perform

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

Qualifications

What Essential Skills You Will Need

• You have 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 Master's degree with at least 12 years of equivalent experience).
• You are proficient in reinforcement learning foundations, including Markov Decision Processes, stochastic control, offline RL, and reward shaping for sequential multi-objective decision systems.
• You have proven experience deploying production ML/RL systems operating under real-time constraints, non-stationary data, and distribution shifts.
• You have hands-on expertise with large language model adaptation and alignment, including supervised fine-tuning (SFT), parameter-efficient methods (LoRA/QLoRA), and preference tuning (RLHF, DPO, or GRPO).
• You have hands-on proficiency in Python, PyTorch, and distributed training/compute platforms such as Ray, DeepSpeed, FSDP, or Megatron-LM.
• You have experience engaging with AI tools and emerging technologies to enhance productivity, improve workflows, and contribute new ideas.