Reinforcement Learning Engineer

Bright Vision Technologies • Hoffman Estates, IL

1d • $96,000 - $120,000 • Remote

About The Position

Bright Vision Technologies is seeking a Reinforcement Learning Engineer to design, train, and deploy reinforcement-learning systems for high-impact decision-making problems that cannot be adequately addressed by supervised learning alone. The role involves applying modern RL algorithms, developing simulation environments and reward models, and handling the engineering challenges of training and evaluating policies at scale. The successful candidate will bring research depth and practical engineering experience, including taking RL solutions from research into production and supporting their stability, safety, and ongoing improvement.

The position is full-time, direct W-2 employment and is 100% remote within the United States. The stated annual salary range is $96,000–$120,000. Candidates with at least eight years of experience are specified in the job overview; the qualifications section separately requires six or more years of combined RL research and engineering experience. The employer is unable to sponsor new H-1B visa petitions, while H-1B transfer candidates and certain other work-authorized applicants are encouraged to apply.

Requirements

• Master’s or PhD in Computer Science, Machine Learning, or a related field, or equivalent applied experience.
• Six or more years of combined reinforcement-learning research and engineering experience.
• Strong proficiency in Python and modern deep-learning frameworks.
• Hands-on experience with at least one major RL library or an in-house RL stack.
• Solid understanding of probability, optimization, and the theoretical foundations of reinforcement learning.
• 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 reinforcement-learning work.

Nice To Haves

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

Responsibilities

• Design, train, and deploy reinforcement-learning systems for high-impact decision-making problems.
• Develop and tune reward functions for non-trivial environments.
• Train and evaluate policies at scale using simulation environments and large-scale experience collection.
• Take RL solutions from research into production, supporting stability, safety, and ongoing improvement.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior