Senior Physical AI Infra Engineer

ByteDance; Seattle (WA); On-site; USD 207,000 - 368,000; Full time

Job summary

ByteDance's Infra-Compute division in the US builds large-scale cloud and AI infrastructure powering our public cloud offerings and internal products.

The US team develops technologies across AI training, inference, and agent infrastructure, expanding into Physical AI with data and simulation platforms, distributed training, and deployment on heterogeneous hardware. You will help design reliable, scalable systems used across teams.

Qualifications

• Bachelor's degree or above in a technical field or equivalent practical experience.
• 5 years of software engineering, machine learning systems, robotics, or related industry experience.
• Strong fundamentals in software/systems engineering for distributed or data-intensive systems.
• Deep expertise in robotic learning, AI training/inference infrastructure, or robotics data/simulation systems.

Responsibilities

• Own design, implementation, validation, and operation of major components within a Physical AI platform across data pipelines, simulation, model training, evaluation, inference, and heterogeneous deployment.
• Develop scalable infrastructure for training and serving multimodal and robotics models (vision-language-action, world models, robot policies).
• Translate research ideas into production-ready capabilities with clear reliability, performance, and quality targets.
• Lead technical design for complex projects, balancing performance, reliability, cost, and delivery speed for production adoption.
• Collaborate with adjacent teams, mentor engineers, and contribute to shared architecture and standards.

Education

Bachelor's degree or above in Computer Science, Computer Engineering, Robotics, Electrical Engineering, Artificial Intelligence, or a related technical field, or equivalent practical experience.

Job description

ByteDance's Infra-Compute division in the US builds large-scale cloud and AI infrastructure powering our public cloud offerings and internal products.

The US team develops technologies across AI training, inference, and agent infrastructure, expanding into Physical AI with data and simulation platforms, distributed training, and deployment on heterogeneous hardware. You will help design reliable, scalable systems used across teams.