Description
As a member of this team, you will use your background to: *Develop the core simulation engine with emphasis on robotics and physics simulation *Integrate simulation software with robotics algorithms *Design, implement and integrate sensor simulation and dynamics modeling for realistic robot simulation *Develop sim-to-real transfer techniques to bridge the gap between simulated and real-world robot behavior *Profile and optimize simulation engine for high-throughput RL training workloads *Design and implement reinforcement learning environments and training pipelines for robotic systems
Minimum Qualifications
Strong C++ development experience and Python experience Strong software engineering skills and practices in terms of performance and code quality Solid background in robotics fundamentals: perception, planning, kinematics, dynamics, control systems Familiarity with reinforcement learning, including policy optimization, model-based RL, and sim-to-real techniques Experience with physics simulation engines (e.g., MuJoCo, Isaac Sim, PyBullet, or similar) Excellent collaboration skills: strong verbal and written communication skills. BS/MS/PhD in Computer Science, Robotics, or a related field, or 3+ years of equivalent experience.
Preferred Qualifications
Experience with GPU-accelerated simulation and parallel RL training Experience with robot learning frameworks (e.g., Stable Baselines, RLlib, or custom implementations) Experience with GPU based computing Experience with sensor simulation Experience with traditional and ML-based simulation and rendering systems Experience with 3D rendering engine internals: geometry pipelines, shaders, materials, etc.
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