Research Engineer - AI/RL Infrastructure

The Robot Age; Sunnyvale (CA); Hybrid; USD 150,000 - 210,000; Full time

Job summary

Applied Intuition is hiring a research engineer to build the AI and reinforcement-learning infrastructure behind its physical AI research. The role supports researchers working on autonomous driving and robotic generalist systems.

The focus is not just model training in isolation. The listing emphasizes large-scale ML systems that help researchers develop, accelerate, and evaluate methods for autonomous and robotic systems. This onsite role is based in Sunnyvale.

Qualifications

• Strong engineering experience with large-scale ML, reinforcement learning, or research infrastructure
• Ability to partner closely with researchers on changing experimental needs
• Practical judgment about compute, data, evaluation, and deployment constraints
• Willingness to work onsite from Applied's Sunnyvale office

Responsibilities

• Design and operate infrastructure for AI, RL, and physical AI experiments
• Work closely with researchers to make training and evaluation faster
• Support research on autonomous driving, robotic generalists, and embodied systems
• Improve reliability and scale for experiments that need to feed deployed programs

Skills

Large-scale ML

RL infrastructure

Research collaboration

Job description

What the role actually is

Applied Intuition is hiring a research engineer to build the AI and reinforcement-learning infrastructure behind its physical AI research. The role supports researchers working on autonomous driving and robotic generalist systems.

The focus is not just model training in isolation. The listing emphasizes large-scale ML systems that help researchers develop, accelerate, and evaluate methods for autonomous and robotic systems.

What you would work on

• Design and operate infrastructure for AI, RL, and physical AI experiments
• Work closely with researchers to make training and evaluation faster
• Support research on autonomous driving, robotic generalists, and embodied systems
• Improve reliability and scale for experiments that need to feed deployed programs

What they are asking for

• Strong engineering experience with large-scale ML, reinforcement learning, or research infrastructure
• Ability to partner closely with researchers on changing experimental needs
• Practical judgment about compute, data, evaluation, and deployment constraints
• Willingness to work onsite from Applied's Sunnyvale office

Why this one is worth a look

Infrastructure roles can be especially valuable in physical AI because research velocity depends on whether experiments are easy to run and trust. This one is close to Applied's autonomy and robotics research agenda, not a generic platform seat.