Remote Reinforcement Learning Engineer — Scale & Deploy AI

Bright Vision Technologies; Hoffman Estates (IL); Remote; USD 96,000 - 120,000; Full time

Job summary

Bright Vision Technologies is seeking a Reinforcement Learning Engineer to design, train, and deploy RL-based systems that solve high‑impact decision problems where supervised learning falls short. You will work across research and engineering to bring RL from lab to production.

The ideal candidate has a PhD or equivalent experience, 6+ years in RL, strong Python and modern DL framework skills, experience with RL libraries, reward modeling, simulation environments, GPU training, and a proven

Qualifications

• Master’s or PhD in CS/ML or related field, or equivalent applied experience.
• Six+ years of RL research and engineering experience.
• Proficiency in Python and modern deep learning frameworks.
• Hands-on experience with a major RL library or in-house RL stack.
• Solid understanding of probability, optimization, and RL theory.
• Experience designing 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-based systems for decision-making problems.
• Collaborate with research and engineering to productionize RL solutions.
• Evaluate stability, safety, and performance of deployed policies.

Skills

RL algorithm expertise

Python

DL frameworks

Reward modeling

Simulation environments

GPU training

Communication

Shipping RL work

Education

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

Tools

Major RL library / in-house RL stack

Job description

Bright Vision Technologies is seeking a Reinforcement Learning Engineer to design, train, and deploy RL-based systems that solve high‑impact decision problems where supervised learning falls short. You will work across research and engineering to bring RL from lab to production.

The ideal candidate has a PhD or equivalent experience, 6+ years in RL, strong Python and modern DL framework skills, experience with RL libraries, reward modeling, simulation environments, GPU training, and a proven