Applied RL Engineer

Bright Vision Technologies; Orlando (FL); À distance; USD 100 000 - 150 000; Plein temps

Résumé du poste

Bright Vision Technologies is seeking an Applied RL Engineer to design, train, and deploy reinforcement learning systems for high‑impact decision-making problems. The role requires deep familiarity with modern RL algorithms, simulation environments, reward modeling, and engineering pipelines capable of training and evaluating policies at scale.

The ideal candidate combines research depth with engineering pragmatism and will bring RL solutions from lab to production where stability, safety, and

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.

Responsabilités

• Design reinforcement learning systems for high-impact decision tasks.
• Train RL models and evaluate performance at scale.
• Deploy RL solutions into production with focus on stability and safety.
• Model reward structures and optimize learning signals.
• Collaborate with teams to integrate RL into end-to-end pipelines.

Connaissances

Python

Deep Learning

Reinforcement Learning

RL Libraries

GPU Clusters

Reward Modeling

Simulation Environments

Research Experience

Communication

Publications

Formation

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

Equivalent applied experience

Outils

RL Library

In-house RL Stack

Description du poste

Job Title:

Applied RL Engineer

Location:

100% Remote (United States)

Position Type:

Full-time, Direct W2

Salary Range:

$100,000–$150,000 Annually

Experience:

6+ years

Sponsorship:

U.S. Citizens, Green CardHolders, EADHolders, and H-1B transfer candidates are encouraged to apply. We are unable to sponsor new H-1B visa petitions for this position.

Job Summary

We are looking for a Reinforcement Learning Engineer to design, train, and deploy RL-based systems for high-impact decision-making problems where supervised learning alone is insufficient. The role requires deep familiarity with modern reinforcement learning algorithms, simulation environments, reward modeling, and the engineering complexity of training and evaluating policies at scale. The ideal candidate has both research depth and engineering pragmatism, with experience taking RL solutions out of the lab and into production where stability, safety, and ongoing improvement are critical.

Required 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.

Preferred Qualifications

• Experience with RLHF for large language models.
• Familiarity with multi‑agent RL or hierarchical RL.
• Exposure to robotics, control systems, or autonomous driving.
• Publications in RL or related research venues.
• Open‑source contributions to RL libraries or environments.

Equal Employment Opportunity (EEO) Statement

Bright Vision Technologies (BV Teck) is committed to equal employment opportunity (EEO) for all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other protected status as defined by applicable federal, state, or local laws. This commitment extends to all aspects of employment, including recruitment, hiring, training, compensation, promotion, transfer, leaves of absence, termination, layoffs, and recall.

BV Teck expressly prohibits any form of workplace harassment or discrimination. Any improper interference with employees' ability to perform their job duties may result in disciplinary action up to and including termination of employment.