Reinforcement Learning Engineer

• 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.
• Experience designing and tuning reward functions in non-trivial environments.
• Familiarity with simulation environments and large-scale experience collection.
• Experience training neural network policies on GPU clusters.
• Strong written and verbal communication skills.
• Track record of shipping or publishing impactful RL work.

• Experience with RLHF for large language models.
• Familiarity with multi-agent RL or hierarchical RL.
• Exposure to robotics, control systems, or autonomous driving.
• Publications in RL or related research venues.
• Open-source contributions to RL libraries or environments.

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