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Grafton Sciences

Senior Robotics Simulation Engineer

Posted 2 Days Ago
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In-Office
Menlo Park, CA
Senior level
In-Office
Menlo Park, CA
Senior level
The Senior Robotics Simulation Engineer will develop high-fidelity simulation environments for robotic training and validation, integrating real data and improving sim-to-real transfer.
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About Grafton Sciences

We’re building physical general intelligence — autonomous systems that can experiment, reason, and discover in the physical world. With deep technical roots and real-world progress at scale (e.g., a $42M NIH project), we’re pushing the frontier of physical AI. Joining us means inventing from first principles, owning real systems end-to-end, and helping build a capability the world has never had before.


About the Role

We’re seeking a Senior Robotics Simulation Engineer to build high-fidelity simulation environments that power robotic policy training, safety validation, digital twins, and long-horizon planning. You’ll develop and calibrate simulation frameworks using MuJoCo, Isaac Gym, Drake, or similar platforms; implement domain randomization strategies; integrate real system data; and ensure accurate sim-to-real transfer for complex manipulation and automation tasks. This role blends physics simulation, robotics engineering, and ML-driven evaluation.


Responsibilities

• Build and maintain high-fidelity robotic simulation environments using MuJoCo, Isaac Gym, Drake, or equivalent frameworks.
• Develop domain randomization, parameter perturbation, and sensor/actuator modeling strategies to improve sim-to-real transfer.
• Integrate simulation with digital twins, RL environments, and evaluation pipelines for policy development and safety testing.
• Collaborate closely with robotics, controls, RL, and digital twin teams to align simulation fidelity with real-world system behavior.


Qualifications

• Strong experience building robotic simulation environments, including physics modeling, contact dynamics, or manipulation simulation.
• Familiarity with domain randomization, calibration techniques, and methods for improving sim-to-real alignment.
• Ability to integrate simulation with ML pipelines, RL environments, and real hardware telemetry.
• Comfortable working across simulation tools, robotics engineering, and ML systems in fast-moving, interdisciplinary settings.

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


Compensation

We offer competitive salary, meaningful equity, and benefits.

Top Skills

Drake
Isaac Gym
Ml-Driven Systems
Mujoco
Robotics Engineering

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