AI Research Engineer Reinforcement Learning
- Kpr sugar apperals
- 1 to 5 Yrs
- All India
- 3 months ago
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Job Description
- Role Overview We are seeking a highly motivated AI Research Engineer specializing in Reinforcement Learning (RL) to develop and deploy learning-based control systems for machines, robotics, and autonomous processes in manufacturing. This role involves applying RL algorithms to optimize complex decision-making problems, robotic automation, and predictive control. Key Responsibilities Develop RL-based models for industrial robotics, autonomous systems, and smart manufacturing. Implement model-free and model-based RL algorithms for real-time applications. Optimize control policies using deep reinforcement learning (DQN, PPO, SAC, TD3, etc.). Integrate RL with simulated environments (e.g., MuJoCo, PyBullet, Isaac Gym) and real-world deployment. Work on multi-agent RL, imitation learning, and curriculum learning for robotic applications. Collaborate with cross-functional teams (hardware, software, and automation engineers) to deploy AI-driven robotics in production environments. Develop scalable RL frameworks, leveraging cloud, edge computing, and digital twin technologies. Contribute to research and innovation in intelligent control, adaptive learning, and human-AI collaboration. Qualifications & Experience Masters or Ph.D. in Computer Science, Robotics, AI, or a related field. Over 1 year of experience in RL research, AI-driven control systems, or robotics. Strong background in deep reinforcement learning (DQN, PPO, SAC, A3C, etc.). Proficiency in Python, TensorFlow/PyTorch, Gym, Stable-Baselines3, or RLlib. Experience in robotic simulation environments (MuJoCo, PyBullet, Isaac Gym). Familiarity with digital twins, real-time control systems, and industrial automation. Hands-on experience in deploying RL models in real-world machines or robotics. Bonus Skills Experience in hardware-in-the-loop (HIL) testing for AI-driven control. Knowledge of MLOps for RL (model monitoring, retraining, deployment automation). Strong mathematical foundation in optimal control, Bayesian RL, and multi-agent learning. Experience working with edge computing for AI in robotics and IoT applications.,
Employement Category:
Employement Type: Full timeIndustry: Manufacturing
Role Category: Not Specified
Functional Area: Not Specified
Role/Responsibilies: AI Research Engineer Reinforcement Learning
Contact Details:
Company: Tata ElectronicsLocation(s): All India
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Keyskills: Reinforcement Learning PPO Python Gym Industrial Automation Optimal Control IoT TensorFlow PyTorch
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