Remote Reinforcement Learning Systems Engineer

United States Digital Space LLC; United States; Remote; USD 100,000 - 150,000; Full time

Job summary

Bright Vision Technologies is seeking an experienced AI Learning Systems Engineer to design, train, and deploy RL-based systems for decision-making in real and simulated environments. The role emphasizes production-ready RL solutions with safety, stability, and scalability in mind.

The ideal candidate will have deep RL knowledge, strong Python and DL framework skills, and experience taking RL from research to production across GPU clusters. Remote work is supported in the U.S.

Qualifications

• Masters 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.

Responsibilities

• Design and implement reinforcement learning solutions for sequential decision-making in real and simulated environments.
• Develop, calibrate, and maintain simulation environments 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 to align agent behavior with outcomes and safety constraints.
• Apply offline RL and imitation learning 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 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 tests.
• Implement safety mechanisms such as constraint enforcement and human-in-the-loop oversight.
• Collaborate with applied scientists and product teams to identify high-value RL use cases.
• Monitor deployed policies for drift and unintended behaviors, and surface issues via dashboards.
• Document methodology and decisions for internal stakeholders.
• Stay current with RL research and translate techniques into production-ready solutions.

Skills

Python

RL algorithms

Deep learning

GPU training

Communication skills

Education

Masters/PhD in CS/ML or related field

Tools

RL libraries

Job description

Bright Vision Technologies is seeking an experienced AI Learning Systems Engineer to design, train, and deploy RL-based systems for decision-making in real and simulated environments. The role emphasizes production-ready RL solutions with safety, stability, and scalability in mind.

The ideal candidate will have deep RL knowledge, strong Python and DL framework skills, and experience taking RL from research to production across GPU clusters. Remote work is supported in the U.S.