Tech Lead, Physical AI Infrastructure & Systems

Bytedance; Seattle (WA); On-site; USD 242,000 - 456,000; Full time

Job summary

ByteDance seeks a Tech Lead Research Scientist to lead the Physical AI Infra initiatives in Seattle. You will own architecture, roadmaps, and end-to-end delivery for large-scale AI infrastructure spanning data pipelines, simulation, and deployment on heterogeneous hardware.

You will mentor engineers, drive cross-team collaboration, and translate ambitious research into reliable, scalable systems. Requires deep ML/robotics expertise and strong communication skills.

Qualifications

• Bachelor's degree or above in CS, CE, robotics, EE, AI, or related field.
• 5 years of software engineering, ML systems, robotics, or related industry experience.
• 3+ years of experience as a tech lead.
• Deep expertise in robotic learning, AI training/inference infra, or robotics data/simulation systems.
• Experience taking complex systems from prototype to production deployment.
• Strong communication, motivation, and cross-team collaboration.

Responsibilities

• Own the technical strategy and multi-quarter roadmap for major Physical AI infrastructure areas.
• Translate research, product, and customer requirements into architecture and plans.
• Lead architecture and delivery across engineers and partner teams with clear interfaces.
• Define interfaces across the Physical AI lifecycle including data, simulation, training, eval, inference, and deployment.
• Mentor engineers and raise the engineering bar across the team.

Skills

Software engineering

Leadership

Machine learning systems

Robotics

AI training & inference

Education

Bachelor's degree or above in a technical field

Tools

Isaac Lab

MuJoCo

MuJoCo/Isaac Sim

Cosmos

vLLM-Omni

Job description

ByteDance seeks a Tech Lead Research Scientist to lead the Physical AI Infra initiatives in Seattle. You will own architecture, roadmaps, and end-to-end delivery for large-scale AI infrastructure spanning data pipelines, simulation, and deployment on heterogeneous hardware.

You will mentor engineers, drive cross-team collaboration, and translate ambitious research into reliable, scalable systems. Requires deep ML/robotics expertise and strong communication skills.