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Mô Tả Công Việc
Key Responsibilities:• Develop, train, and deploy reinforcement learning algorithms for robotic motion and manipulation tasks.• Build and optimize simulation infrastructure to support large-scale policy training for general-purpose robots.• Collaborate with the controls team to integrate learned policies into the robot’s existing control stack.• Define performance metrics, test learned policies, and evaluate their effectiveness in real-world scenarios.
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Yêu Cầu Công Việc
• Bachelor’s or Master’s, PhD’s degree in computer science, AI, Mechatronics, Control Engineering – Automation, or a related field• Proficiency in writing production-quality code using PyTorch/Tensorflow/JAX.• Familiarity with online and offline RL algorithms, such as PPO and SAC.• Familiarity with simulation technologies (e.g., IsaacGym, IsaacLab, Mujoco)• Experience in tuning hyperparameters, reward engineering, and optimizing RL training processes.• Knowledge of RL techniques, including domain randomization, curriculum learning, and reward shaping.• Familiarity with machine learning evaluation tools like TensorBoard or Weights & Biases.• Understanding of the latestest development and framework in RL for locomotion, manipulation and navigation
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Hình thức
Full-time
Mức lương
Thỏa thuận
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