Senior AI Engineer / Manager Reinforcement Learning & Intelligent Machine Control

You will be responsible for designing and developing intelligent machine control systems using deep reinforcement learning (DRL) for automation, robotics, and adaptive decision-making in semiconductor and advanced manufacturing. This includes applying model-free (e.g., DQN, PPO, SAC, TD3) and model-based RL to optimize complex, real-time control systems for precision tools and autonomous processes. You will also need to develop and integrate RL agents within simulated environments such as MuJoCo, Isaac Gym, and digital twins, scaling toward real-world deployment. Furthermore, you will combine traditional control (PLC, motion, CNC) with AI/ML approaches for predictive maintenance, anomaly detection, and adaptive process tuning. Collaboration with software, automation, hardware, and manufacturing teams to deploy AI-driven systems in production environments is essential. Additionally, building and maintaining scalable RL frameworks using cloud, edge computing, and real-time digital twin integration will be part of your role. You will lead experimentation with multi-agent learning, imitation learning, and curriculum learning for complex coordinated systems while mentoring junior engineers and contributing to the company's AI-first vision by embedding intelligence into core manufacturing operations. - Design and develop intelligent machine control systems using deep reinforcement learning (DRL) - Apply model-free and model-based RL techniques to optimize complex, real-time control systems - Develop and integrate RL agents within simulated environments such as MuJoCo, Isaac Gym, and digital twins - Combine traditional control with AI/ML approaches for predictive maintenance, anomaly detection, and adaptive process tuning - Collaborate with cross-functional teams to deploy AI-driven systems in production environments - Build and maintain scalable RL frameworks using cloud, edge computing, and real-time digital twin integration - Lead experimentation with multi-agent learning, imitation learning, and curriculum learning - Mentor junior engineers and contribute to the company's AI-first vision You should possess the following qualifications: - Masters or Ph.D. in Computer Science, Robotics, AI, Mechatronics, Electrical, or Mechanical Engineering - 5+ years of experience in industrial automation, machine control, or AI-driven system design - Strong expertise in deep reinforcement learning and control system development - Experience with PLC/motion control/CNC systems and hardware-in-the-loop (HIL) testing - Exposure to digital twin integration, edge AI deployment, and real-time systems - Strong foundation in control theory, optimal control, and adaptive systems,