Reinforcement Learning (Physical AI) Intern

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.

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