Senior Applied RL Engineer — Remote

Bright Vision Technologies; Wesley Chapel (FL); 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 systems for high-impact decision-making across the United States.

The role requires advanced degrees (MS/PhD) in CS/ML or equivalent experience, 6+ years in RL research and engineering, strong Python and DL framework skills, and experience with RL libraries, reward modeling, and scalable training on GPUs.

This is a 100% remote, direct-hire role with competitive compensation and strong growth opportunities.

Qualifications

• Master's or PhD in CS/ML or equivalent applied 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 theory.
• 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, train, and deploy RL models for production systems.
• Collaborate with researchers and engineers to scale RL solutions.
• Assess safety, reliability, and performance of RL deployments.

Skills

Python

Deep learning

RL libraries

GPU training

Reward modeling

Simulation envs

Communication

Publications

Education

Master's or PhD in CS/ML

Tools

OpenAI Gym

Stable Baselines

Job description

Bright Vision Technologies is seeking an Applied RL Engineer to design, train, and deploy RL systems for high-impact decision-making across the United States.

The role requires advanced degrees (MS/PhD) in CS/ML or equivalent experience, 6+ years in RL research and engineering, strong Python and DL framework skills, and experience with RL libraries, reward modeling, and scalable training on GPUs.

This is a 100% remote, direct-hire role with competitive compensation and strong growth opportunities.