Responsibilities

• Build RL environments, simulation interfaces, and evaluation workflows for complex physical processes.
• Develop verifiers, safety checks, and automated evaluation tools for learning systems interacting with real or simulated hardware.
• Work across robotics, controls, simulation, and ML teams to integrate hardware intuition into learning-based systems.
• Prototype, test, and refine physical workflows, combining real hardware data with learned models.
• Own cross-stack engineering tasks spanning robotics, software, ML frameworks, and system-level integration.

Qualifications

• Strong background in robotics, physical system modeling, controls, or high-performance automation.
• Experience building RL environments, evaluators, or simulation-based training systems.
• Ability to work across the full stack of physical engineering, from prototypes to software abstractions.
• Comfort integrating ML models with real-world hardware and designing verification tools.
• High-agency engineer who thrives in interdisciplinary, hands-on environments.

Above all, we look for candidates who can demonstrate world-class excellence.

Compensation We offer competitive salary, meaningful equity, and benefits.