Senior Physical AI Infra Engineer — Scalable ML Infra

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

Benefits offered by this job

Medical insurance

401(k) with company match

Paid parental leave

Disability coverage

Wellbeing benefits

Paid holidays

Job summary

ByteDance is seeking a Senior Development Engineer for Physical AI Infra in Seattle. You will independently own major components across data pipelines, simulation, model training, and heterogeneous deployment, building scalable infrastructure for multimodal and robotics models.

Requirements include 5+ years in software/ML/robotics, deep engineering fundamentals, and expertise in robotic learning, AI training/inference, or robotics data/simulation systems.

Qualifications

• Bachelor's degree or above in CS, CE, robotics, EE, AI, or related field or equivalent practical experience.
• 5+ years of software engineering, ML systems, robotics, or related experience.
• Strong fundamentals in software and 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, training, evaluation, inference, and deployment.
• Develop scalable infrastructure for training and serving multimodal and robotics models.
• Translate research ideas into production capabilities with reliability, performance, and quality targets.
• Lead technical design for complex projects and drive production adoption.

Skills

Distributed systems

Robotics data & simulation

Machine learning systems

Production-scale software engineering

Education

Bachelor's degree in a related technical field

Tools

Isaac Sim

MuJoCo

Cosmos

vLLM-Omni

Job description

ByteDance is seeking a Senior Development Engineer for Physical AI Infra in Seattle. You will independently own major components across data pipelines, simulation, model training, and heterogeneous deployment, building scalable infrastructure for multimodal and robotics models.

Requirements include 5+ years in software/ML/robotics, deep engineering fundamentals, and expertise in robotic learning, AI training/inference, or robotics data/simulation systems.