Senior Research Scientist, Physical AI Infrastructure

Bytedance; San Jose (CA); On-site; USD 218,000 - 388,000; Full time

Benefits offered by this job

Medical insurance

Dental & Vision insurance

401(k) with company match

Parental leave

Disability coverage

Life insurance

Wellbeing benefits

Paid holidays

Sick days

Personal time off

Job summary

ByteDance is seeking a Senior Research Scientist to drive the Physical AI Infra platform in San Jose. This role leads design, implementation, and operation of core components across data pipelines, simulation, model training, and deployment on heterogeneous hardware.

You will advance scalable infrastructure for multimodal and robotics models, translate research into production capabilities, and guide complex project design with a focus on reliability and performance.

Qualifications

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

Responsibilities

• Own design, implementation, validation, and operation of major components within a Physical AI platform.
• Develop scalable infrastructure for training and serving multimodal and robotics models.
• Translate research ideas into production-ready capabilities with reliability and performance targets.
• Lead technical design for complex projects, balancing performance, reliability, cost, and delivery speed.
• Collaborate with teams, mentor engineers, and contribute to shared architecture and standards.

Skills

Software engineering

ML systems

Robotics

Distributed systems

Education

Bachelor's degree or higher in CS/CE/Robotics/EE/AI

Job description

ByteDance is seeking a Senior Research Scientist to drive the Physical AI Infra platform in San Jose. This role leads design, implementation, and operation of core components across data pipelines, simulation, model training, and deployment on heterogeneous hardware.

You will advance scalable infrastructure for multimodal and robotics models, translate research into production capabilities, and guide complex project design with a focus on reliability and performance.