Reinforcement Learning Engineer

Job Summary

Joining a forward-thinking software development team, the full-time Reinforcement Learning Engineer will design, train, and deploy RL-based systems for high-impact decision-making problems, working remotely in a collaborative 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, including policy gradient and actor-critic methods

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