Reinforcement Learning Engineer

Job Summary

To support a growing team, the full-time Reinforcement Learning Engineer will design, train, and deploy reinforcement learning systems for high-impact decision-making problems in a remote environment.

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
• Implement and evaluate modern reinforcement learning algorithms and engineer reward functions to align agent behavior with desired outcomes

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 reinforcement learning research and engineering experience
• Strong proficiency in Python and modern deep learning frameworks
• Hands-on experience with at least one major reinforcement learning library or in-house RL stack
• Solid understanding of probability, optimization, and theoretical foundations of reinforcement learning