The Infra-Compute division builds large-scale, highly available cloud and AI infrastructure that powers our public cloud offerings and internal products.
Our US team develops technologies across AI training, inference, and agent infrastructure.
We are expanding this work into Physical AI: intelligent systems that perceive, reason, and act in the physical world.
The team focuses on infrastructure for Physical AI, including data and simulation platforms, distributed training and inference, and deployment on heterogeneous hardware.
We collaborate closely with customers, researchers, open-source communities, and hardware partners to turn emerging research into reliable, scalable systems.
Responsibilities
- Track advances in academia, industry, and open-source communities; contribute technical insights, software, and, where appropriate, publications.
- Own the technical strategy and multi-quarter roadmap for major Physical AI infrastructure areas, translating ambiguous research, product, and customer requirements into clear architecture and execution plans.
- Lead architecture and delivery across multiple engineers and partner teams, define system boundaries and interfaces, resolve cross-stack trade-offs, and remain accountable for end-to-end technical outcomes.
- Define interfaces across the Physical AI lifecycle—including data pipelines, simulation, model training, evaluation, inference, and deployment—while directly owning one or more major platform components.
- Mentor engineers, develop technical leaders, and raise the engineering bar across the team.