Remote RL Engineer - Production-Grade Reinforcement Learning

pofft Technology Inc.; United States; Remote; USD 100,000 - 150,000; Full time

Job summary

Bright Vision Technologies is seeking an Applied RL Engineer to design, train, and deploy RL-based systems for high-impact decision problems. The role requires deep familiarity with modern reinforcement learning algorithms, simulation environments, reward modeling, and scalable training and evaluation of policies.

The position is 100% remote within the United States, full-time on a direct W2 basis, with a salary range of $100,000 to $150,000 per year.

Qualifications

• Master’s or PhD in CS/ML or equivalent experience.
• 6+ years of RL research and engineering experience.
• Strong 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 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, train, and deploy RL-based systems for decision-making.
• Develop simulation environments and reward modeling.
• Scale training and evaluate policies for production-ready deployment.

Skills

Python

Deep learning frameworks

RL research & engineering

RL libraries

Probability & optimization

Reward modeling

GPU training

Written and verbal communication

Shipping RL work

Education

Master’s/PhD in CS/ML

Tools

In‑house RL stack

Simulation environments tooling

Job description

Bright Vision Technologies is seeking an Applied RL Engineer to design, train, and deploy RL-based systems for high-impact decision problems. The role requires deep familiarity with modern reinforcement learning algorithms, simulation environments, reward modeling, and scalable training and evaluation of policies.

The position is 100% remote within the United States, full-time on a direct W2 basis, with a salary range of $100,000 to $150,000 per year.