Remote RL AI Learning Systems Engineer

Bright Vision Technologies; United States; Remote; USD 100,000 - 150,000; Full time

Job summary

Bright Vision Technologies is seeking an AI Learning Systems Engineer to design, train, and deploy RL-based systems for high-impact decision-making problems where supervised learning alone is insufficient. The 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 has both research depth and engineering pragmatism, with experience

Qualifications

• Master’s or PhD in Computer Science, ML, or a related field, or equivalent applied experience.
• 6+ years of RL research and engineering experience.
• Strong proficiency in Python and modern deep learning frameworks.
• Experience training neural network policies on GPU clusters.
• Experience designing and tuning reward functions in non-trivial environments.
• Familiarity with simulation environments and large-scale experience collection.

Responsibilities

• Design and implement reinforcement learning solutions for sequential decision-making problems in real and simulated environments.
• Develop, calibrate, and maintain simulation environments suitable for large-scale agent training.
• Implement and evaluate modern RL algorithms including policy gradient, actor-critic, off-policy, and offline RL methods.
• Engineer reward functions and shaping strategies that align agent behavior with desired outcomes and safety constraints.
• Apply offline RL and imitation learning techniques where exploration is costly or unsafe.
• Use RLHF, DPO, and related techniques for fine-tuning large language models when relevant.
• Build scalable training infrastructure for distributed RL, including efficient experience collection and replay systems.
• Optimize training stability and sample efficiency through algorithmic and engineering improvements.
• Design rigorous evaluation protocols, including out-of-distribution and adversarial test cases.
• Implement safety mechanisms such as constraint enforcement, conservative policies, and human-in-the-loop oversight.
• Collaborate with applied scientists and product teams to identify high-value RL use cases.
• Monitor deployed policies and models in production for drift, regression, and unintended behaviors, building the alerting and dashboards that surface issues before they meaningfully affect users.
• Document methodology, design decisions, and operational characteristics for internal stakeholders.
• Stay current with RL research and translate promising techniques into production-ready solutions.

Skills

Python

Deep learning frameworks

Reinforcement learning

RL libraries

Probability & optimization

Simulation environments

GPU clusters

Reward design

Production RL

Communication

Education

Master's or PhD in Computer Science/ML or related

Tools

In-house RL stack

Major RL library

Job description

Bright Vision Technologies is seeking an AI Learning Systems Engineer to design, train, and deploy RL-based systems for high-impact decision-making problems where supervised learning alone is insufficient. The 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 has both research depth and engineering pragmatism, with experience