Applied Scientist II
Core
Develop physics-based simulation methodologies, sim-to-real transfer methods, and machine learning approaches to enable rapid development and validation of advanced robotics systems.
Role type
Applied Scientist (Robotics Simulation & ML)
Builds
High-fidelity physics-based simulation tools, digital twin pipelines, and sim-to-real transfer frameworks for robotic manipulation and locomotion.
Domain
Robotics, Physics Simulation, Machine Learning
Deliverable
production ML models | product features
Required skills
Physics-based simulation (rigid/deformable dynamics, contact mechanics), C++, Python, high-performance computing, modern physics engines (MuJoCo, Isaac Lab, Drake, Newton)
Preferred skills
Reinforcement learning, differentiable physics, neural physics engines, legged locomotion, GPU-accelerated computing, robotics model formats (URDF, SDF, USD)
Technologies
MuJoCo, Isaac Lab, Drake, Newton, C++, Python, CUDA
Responsibilities
Advance simulation fidelity for contact-rich manipulation and locomotion; design high-performance simulation tools; translate research into verifiable data; quantify simulation-to-reality gaps; architect scalable simulation solutions; build pipelines optimized for digital twin fidelity; establish frameworks for continuous simulation improvement.
Seniority
Mid-Senior, hands-on IC