Reinforcement Learning Engineer

Job Summary

Seeking a full-time Reinforcement Learning Engineer to design, train, and deploy RL-based systems for decision-making problems in a remote capacity, requiring expertise in modern reinforcement learning algorithms and simulation environments.

Key Responsibilities

• Design and implement reinforcement learning solutions for sequential decision-making in real and simulated environments
• Develop and maintain simulation environments for large-scale agent training and optimize training stability
• Collaborate with applied scientists and product teams to identify high-value RL use cases and monitor deployed models for performance issues

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 major RL libraries or in-house RL stacks
• Solid understanding of probability, optimization, and the theoretical foundations of RL