Reinforcement Learning Engineer

Job Summary

To support the development of innovative solutions, the full-time Reinforcement Learning Engineer will design, train, and deploy RL-based systems for decision-making problems in a remote work environment.

Key Responsibilities

• Design and implement reinforcement learning solutions for sequential decision-making problems in real and simulated environments
• Develop and maintain simulation environments suitable for large-scale agent training
• Implement and evaluate modern RL algorithms, optimizing training stability and sample efficiency

Required Qualifications

• Master's or PhD in Computer Science, Machine Learning, or a related field; or equivalent applied experience
• Six or more years of combined RL research and engineering experience
• Strong proficiency in Python and modern deep learning frameworks
• Hands-on experience with at least one major RL library or in-house RL stack
• Solid understanding of probability, optimization, and the theoretical foundations of RL