Applied RL Engineer

Bright Vision Technologies • Ashburn, VA

20h • $100,000 - $150,000 • Remote

About The Position

Bright Vision Technologies is seeking a Reinforcement Learning Engineer to design, train, and deploy RL-based systems for high-impact decision-making problems where supervised learning alone is insufficient. This role requires deep familiarity with modern reinforcement learning algorithms, simulation environments, reward modeling, and the engineering complexity of training and evaluating policies at scale. The ideal candidate will possess both research depth and engineering pragmatism, with experience in taking RL solutions from the lab into production, emphasizing stability, safety, and ongoing improvement.

Requirements

• 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.

Nice To Haves

• 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.

Responsibilities

• Design, train, and deploy RL-based systems for high-impact decision-making problems.
• Utilize modern reinforcement learning algorithms, simulation environments, and reward modeling.
• Address the engineering complexity of training and evaluating policies at scale.
• Take RL solutions from the lab into production, ensuring stability, safety, and ongoing improvement.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior