Applied RL Engineer

📋 Description

• Design, train, evaluate, and deploy RL models for complex decisions.
• Develop RL systems beyond supervised learning for dynamic environments.
• Apply RL algorithms, simulation, and reward modeling methods.
• Design and optimize reward functions for challenging environments.
• Build and maintain simulation environments and large-scale data pipelines.
• Train neural network-based policies on GPU clusters and scalable infra.

🎯 Requirements

• MS/PhD in CS/ML/AI or related field or equivalent.
• 6+ years RL research and engineering experience.
• Python and modern deep learning framework skills.
• Hands-on RL libraries or platforms experience.
• Probability, optimization, and RL theory fundamentals.
• Experience designing and tuning reward functions.

🎁 Benefits

• Fully remote work within the United States.
• Full-time direct employment.
• Salary range $100,000–$150,000 USD.
• Work on advanced AI and reinforcement learning initiatives.
• Collaborative environment blending research and engineering.
• Career growth opportunities in a tech-focused organization.