Senior Reinforcement Learning Engineer - Remote

Bright Vision Technologies; Sugar Land (TX); 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 problems. The role emphasizes production-ready RL with safety, scalability, and robust evaluation.

Candidates should demonstrate research depth plus pragmatic engineering skills, and be prepared to work on in-house SOW deliverables as a full-time W2 employee. The ideal candidate has 6+ years in RL research/engineering, strong Python and DL framework skills,

Qualifications

• Advanced degree in CS/ML or equivalent experience.
• 6+ years of 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 RL foundations.
• Experience designing and tuning reward functions in non-trivial environments.
• Familiarity with simulation environments and large-scale data 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 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 and unintended behaviors, building alerts and dashboards.
• 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

Reinforcement Learning

RL algorithms

GPU clusters

Education

Master’s or PhD in CS/ML

Tools

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 problems. The role emphasizes production-ready RL with safety, scalability, and robust evaluation.

Candidates should demonstrate research depth plus pragmatic engineering skills, and be prepared to work on in-house SOW deliverables as a full-time W2 employee. The ideal candidate has 6+ years in RL research/engineering, strong Python and DL framework skills,