Remote Reinforcement Learning Engineer — Scale & Safety

Bright Vision Technologies; Glastonbury (CT); Remote; USD 100,000 - 150,000; Full time

Job summary

Bright Vision Technologies is seeking a Reinforcement Learning Engineer for a 100% remote U.S. position. The role focuses on designing scalable RL solutions for real and simulated environments and advancing state-of-the-art methods.

You will build and maintain simulation environments, implement modern RL algorithms, and collaborate with scientists and product teams to ship robust models. Requires 6+ years in RL with strong Python and GPU experience.

Qualifications

• 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.

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

RL theory

Reward design

GPU training

Communication

Publication track

Education

Master’s or PhD in CS/ML or related field

Tools

RL library

Job description

Bright Vision Technologies is seeking a Reinforcement Learning Engineer for a 100% remote U.S. position. The role focuses on designing scalable RL solutions for real and simulated environments and advancing state-of-the-art methods.

You will build and maintain simulation environments, implement modern RL algorithms, and collaborate with scientists and product teams to ship robust models. Requires 6+ years in RL with strong Python and GPU experience.