MTS - Research (Robotics Simulation Data)

Preferred

• Education: MS or PhD in Physics, Computer Science, Applied Math, Engineering, or equivalent hands-on industry experience in physics-based simulation.
• Physics Engine Expertise: Strong track record of developing or extending high-fidelity physics engines, rigid-body dynamics solvers, or constraint-based systems. Experience with deformables, fluids, soft bodies, or differentiable simulation is a plus.
• Numerical Methods & Dynamics: Deep understanding of classical mechanics, contact modeling, constraint solvers, integrators, and managing accuracy-vs-speed trade-offs for large-scale computation.
• GPU Programming: Advanced expertise in CUDA and GPU optimization, with a proven ability to accelerate numerical algorithms on parallel hardware architectures.
• Systems Engineering: High proficiency in C++ and Python, with a track record of building reliable, high-throughput software used in production data or ML pipelines.
• ML Infrastructure Familiarity: Strong grasp of how ML frameworks consume simulation outputs (e.g., vectorized environments, massively parallel rollouts, synthetic dataset generation).
• Fidelity Intuition: Deep intuition for physical realism and dataset distribution drift—understanding how synthetic physical data behaves and how to model environmental variance without relying on physical hardware collection.