Senior Data Scientist (Integrity)

Get to Know the Team

The Integrity team is the guardians of all our users on Grab. Our mission is to be the most trusted platform in the world for protecting individuals and businesses in the domain of fraud, risk, digital identity and safety. The data science team uses rich datasets to build AI solutions to solve these tough problems. We're a hands-on team involved in the entire modelling lifecycle: from data exploration and model development to production deployment and model refresh.

Get to Know the Role

We are looking for Senior Data Scientist specialising in Computer Vision and Multimodal LLMs post-training. This role reports into the Senior Data Science Manager and is based in Grab Singapore One North office.

You'll focus on developing advanced models for precise OCR, KYC verification, and document/image information extraction. This work directly supports enhanced user onboarding, verification workflows, and several downstream applications. You'll use modern technologies, including Multimodal LLMs, to improve visual intelligence capabilities.

The Critical Tasks You Will Perform

You will:

• Build at Massive Scale: Design, train, and fine-tune state-of-the-art models, including OCR and Vision LLMs, to analyse and extract information from complex documents. Your work will be at the core of Grab's ability to scale KYC and onboarding operations.
• Architect and Own End-to-End Solutions: Architect, design, and own the document processing pipelines that solve critical business challenges like identity verification, from initial concept to live production models.
• Productionize and Optimize: Deploy your models into our high-throughput production environment, implement monitoring for production metrics, and iterate to improve performance, latency, and efficiency.
• Drive Innovation: Research and prototype with the latest advancements in AI, translating cutting-edge academic research into tangible product impact.
• Influence Through Clarity: Explain technical concepts, model trade-offs, and experimental findings to stakeholders in product, policy, and operations.