Position details

•         Division: Foundation AI Division, VinRobotics

•         Reports to: VinRobotics executive leadership (CEO office)

•         Direct reports: Head of Reinforcement Learning, Head of Edge AI Optimization, Head of Robot Foundation AI; about 50 people in the division, including talent programs

•         Location: Hanoi or Ho Chi Minh City

Purpose of the role

Lead the Foundation AI Division in building the Physical AI foundation for VinRobotics humanoid lines: foundation models (VLA, world models), RL-based control, edge optimization and deployment, and large-scale data infrastructure. The role turns research into product capability, brings robots into real Vingroup use cases, and builds VinRobotics' technology standing with partners and the international community.

Key responsibilities

1.       Technology strategy: set the division's Physical AI strategy and multi-year technology roadmap, tied to the robot product roadmap and business priorities; advise executive leadership on technology decisions, including build versus partner.

2.       Lead three departments: Reinforcement Learning, Edge AI Optimization and Robot Foundation AI; ensure an end-to-end integrated stack from VLAs and world models through RL whole-body control to inference on onboard hardware.

3.       Data and infrastructure: lead the Data Factory (egocentric, teleop, mocap and synthetic data), the data QC pipeline and training compute infrastructure; plan and manage the infrastructure budget.

4.       Deployment and productization: bring core technology into factory and service use cases across the Vingroup ecosystem; set and track field metrics (cycle time, success rate, reliability); work with the PMO, hardware and product divisions.

5.       Strategic partners and ecosystem: technical point of contact with NVIDIA, Qualcomm, Intel, universities and research institutes; set direction for open source, publications and intellectual property.

6.       Organization and talent: hire and develop department heads; design the org structure, KPIs and division budget; run the talent programs (interns, Young Engineers, Residents).

Requirements

•         PhD in Computer Science, Robotics, AI or a related field.

•         Strong AI or robotics R&D background, with experience leading multiple R&D teams or an organization of 20+ people.

•         Deep and broad knowledge of robot learning: foundation models (VLA, VLM, world models), RL and sim-to-real, imitation learning, and model deployment on edge hardware.

•         Track record of taking learning-based robot systems from research to real deployment or product.

•         Publications at top venues (CoRL, RSS, ICRA, NeurIPS, ICML, ICLR) and standing in the research community.

•         Strong strategy, budgeting and stakeholder skills with senior leadership and international partners; fluent English.

Preferred

•         Experience with humanoid or legged robots, whole-body control and loco-manipulation.

•         Has built large-scale robot data infrastructure (teleop, egocentric, synthetic) and distributed training pipelines.

•         Experience partnering with chip and AI platform companies, or leading impactful open-source projects.

•         Experience bridging academia and industry (teaching, PhD supervision) and a patent portfolio.