Tech Lead, Physical AI Infrastructure

ByteDance; Seattle (WA); Presencial; USD 242.000 - 456.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Health insurance

401(k) savings plan

Paid parental leave

Descripción de la vacante

ByteDance's Infra-Compute division is expanding its Physical AI infrastructure, spanning data pipelines, simulation, distributed training, and deployment across heterogeneous hardware. The team collaborates with customers, researchers, open-source communities, and hardware partners to turn research into scalable, reliable systems.

The role focuses on owning multi-quarter roadmaps, guiding architecture across multiple engineers, and mentoring technical leaders to raise the engineering bar.

Formación

• Bachelor's degree in a technical field or equivalent practical experience.
• 5+ years in software engineering, ML systems, robotics, or related industry experience.
• 3+ years as a tech lead.
• Deep expertise in robotic learning, AI training/inference infrastructure, or robotics data & simulation systems.
• Experience taking complex systems from prototype to production deployment.
• Strong communication and cross-functional collaboration skills.

Responsabilidades

• Own the technical strategy and multi-quarter roadmap for major Physical AI infrastructure areas, translating requirements into architecture and execution plans.
• Lead architecture and delivery across engineers and partner teams, define interfaces and resolve cross-stack trade-offs.
• Define interfaces across the Physical AI lifecycle including data pipelines, simulation, model training, evaluation, inference, and deployment.
• Mentor engineers and develop technical leaders to raise the engineering bar.

Conocimientos

Robotics ML

Distributed training

AI infrastructure

Leadership

System design

Educación

Bachelor's degree in Computer Science/Engineering or related

Herramientas

GPU kernels

Simulation platforms

Multimodal datasets

Descripción del empleo

ByteDance's Infra-Compute division is expanding its Physical AI infrastructure, spanning data pipelines, simulation, distributed training, and deployment across heterogeneous hardware. The team collaborates with customers, researchers, open-source communities, and hardware partners to turn research into scalable, reliable systems.

The role focuses on owning multi-quarter roadmaps, guiding architecture across multiple engineers, and mentoring technical leaders to raise the engineering bar.