Lead Product Manager, Physical AI

About the role

Grab's Geo and IoT team builds the location capabilities behind its services, and its Physical AI initiative is building a platform for embodied and egocentric AI training data across Southeast Asia, connecting labs that need high-quality data with people who collect it in the field. As a senior individual contributor, you will own the platform from pilot to scale, shaping product and business strategy, building a trusted collector experience and turning partner requirements into reliable, compliant data delivery. The role is based onsite in Singapore.

Key responsibilities

• Set the platform strategy across lab demand, field collection and data curation, defining partner priorities, build-versus-partner choices, pricing, incentives and unit economics.
• Work with AI labs and Partnerships to turn training needs into dataset specifications, quality criteria, delivery timelines and service commitments.
• Own the collector experience, including field tooling, clear instructions, incentives and reliable payments.
• Prioritize the platform for collection, annotation, labeling, quality assurance and delivery, and turn model feedback into improved data and workflows with Engineering and Data Science.
• Build a roadmap with clear milestones and trade-offs, and work with Operations and country teams to assess field readiness, visit sites, resolve risks early and scale successful pilots.
• Partner with Legal, Data Privacy, Procurement and country stakeholders on consent, site and vendor terms, data handling and cross-border delivery before scaling.

Required profile

• At least 4 years of product management experience, owning a significant product from ambiguous opportunity through launch and iteration.
• Experience shipping an AI-native product, with fluency in training data, evaluation and feedback loops.
• Experience building a multi-sided platform connecting demand, field operations, data quality and user experience.
• Commercial judgment on partner prioritization, pricing, incentives and unit economics.
• Ability to write clear product requirements and evaluate trade-offs across technical, operational, quality, cost and time constraints.
• Experience working across Engineering, Data Science, commercial and operations teams, including privacy and legal specialists.

Nice to have

• Embodied AI, robotics, world models, egocentric or geospatial data, or sensor-based collection.
• AI-lab partnerships, annotation workflows or large-scale multi-country field operations.

What we offer

• Term life insurance and comprehensive medical insurance.
• Parental and birthday leave, plus volunteering leave.
• A confidential assistance programme for you and your loved ones.
• FlexWork arrangements such as differentiated hours.