Member of Technical Staff – Simulation

General Intuition & Medal • New York City, NY

8d • Onsite

About The Position

General Intuition is a frontier lab focused on acting in space and time. The company builds large action models and world models that perceive, predict, and act across virtual and physical environments. Building on the gaming-clips platform Medal, General Intuition trains models on games that act across multiple embodiments and is expanding its use of simulation.

In this role, you will develop low-level robot controllers using reinforcement learning in simulation and build realistic environments for model training. You will own work across the simulation stack, from physics and environments to integrating controllers with the company’s models. This is an in-person role based in one of the New York, Geneva, or Zurich offices.

Requirements

• At least 6 years of hands-on experience with robot learning in simulation, such as contact-rich manipulation, legged locomotion, or whole-body control.
• Strong fundamentals in reinforcement learning and sim-to-real transfer.
• Deep, hands-on simulation experience in production, including ownership of environments, assets, and domain randomization in a major simulator.
• Experience making decisions about physics fidelity, including contact models, actuator dynamics, and solver settings.
• Experience deploying simulation-trained policies on real robots across more than one embodiment.
• A track record of building simulation from scratch and evidence that others depended on the resulting systems.
• Experience leading simulation work, setting technical direction, and raising the bar of other engineers while continuing to write code.

Nice To Haves

• Experience as the first simulation engineer on a team.
• Experience hiring engineers.
• Experience with Isaac Sim and MuJoCo; the posting states the company uses these simulators.

Responsibilities

• Train low-level controllers for robots using reinforcement learning in simulation.
• Build realistic simulation environments suitable for training, not just evaluation.
• Own simulation work across physics, environments, assets, domain randomization, and integration of controllers with models.
• Set technical direction for simulation while remaining hands-on and writing code.
• Bridge simulation and real-world robotic systems by deploying simulation-trained policies on real robots.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed