At Cadence, we hire and develop leaders and innovators who want to make an impact on the world of technology.
Internship Overview
We are seeking a passionate and technically skilled intern to join our R&D team as a Reinforcement Learning (Physical AI) Intern. This role is ideal for students with a strong foundation in reinforcement learning and robotics control, eager to apply their skills to real-world adaptive systems and intelligent automation.
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Key Responsibilities
• Develop RL prototypes using algorithms like Deep Q, PPO, and A3C for control and optimization tasks.
• Integrate RL into simulation environments and robotics simulators.
• Collaborate on adaptive systems that learn from feedback to improve performance over time.
• Support internal presentations and documentation for RL-based automation initiatives.
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Preferred Qualifications
• Pursuing a degree in Robotics, AI, Computer Science, or related field.
• Experience with Python, PyTorch, and RL libraries (e.g., Stable Baselines, RLlib).
• Hands-on experience with simulators (e.g., Gazebo, MuJoCo).
• Strong math optimization and control theory background.
We’re doing work that matters. Help us solve what others can’t.