Reinforcement Learning Engineer
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Reinforcement Learning Engineer
96,000–120,000 / Year
Location
Remote
Experience
Senior
Posted
Jul 30, 2026
Apply by
August 29, 2026
Applicants
0
Early applicantEasy applyFull-timeWork from Home
Job Description
Reinforcement Learning Engineer – Remote
Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States.
This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential.
Job Title: Reinforcement Learning Engineer
Location: 100% Remote (U.S.)
Position Type: Full-time, Direct W2
Salary Range: $96,000–$120,000 Annually
Experience Required: 6+ years
Sponsorship: U.S. Citizens, Green Card Holders, EAD Holders, 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.
How to Apply
Would you like to know more about this opportunity? For immediate consideration, please send your resume to [\[email protected\]](/cdn-cgi/l/email-protection). Learn more about Bright Vision Technologies at www.bvteck.com.
Bright Vision Technologies is an Equal Opportunity Employer.
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.
Key Responsibilities
- Design, train, and deploy reinforcement learning-based systems for high-impact decision-making problems.
- Develop and tune reward functions in non-trivial environments.
- Train neural network policies on GPU clusters.
- Evaluate policies at scale and ensure stability, safety, and ongoing improvement.
- Take RL solutions out of the lab and into production environments.
Requirements
- Master’s or PhD in Computer Science
- Machine Learning
- or a related field
Skills Required
PythonDeep Learning FrameworksReinforcement LearningProbabilityOptimizationReward ModelingSimulation EnvironmentsGPU ClustersNeural Network PoliciesWritten CommunicationVerbal CommunicationRLHFMulti-agent RLHierarchical RLRoboticsControl SystemsAutonomous DrivingOpen-source Contributions
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