Director, Machine Learning Engineering

Reinforcement Learning Engineer

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.

• Company:
  Bright Vision Technologies
• Location:
  
  100% Remote (Continental United States)
• Position Type:
  Full‑time, direct W2
• Compensation: $100k – $150k base salary, benefits included
• No new H1B sponsorship available; existing H1B transfers welcomed

• Design and implement reinforcement learning solutions for sequential decision‑making problems in real and simulated environments.
• Develop, calibrate, and maintain large‑scale simulation environments for agent training.
• Implement modern RL algorithms including policy gradient, actor‑critic, off‑policy, and offline RL methods.
• Engineer reward functions and shaping strategies aligning agent behavior with desired outcomes and safety constraints.
• Apply offline RL, imitation learning, and RLHF/DPO techniques where appropriate.
• Build scalable training infrastructure for distributed RL, efficient experience collection and replay systems.
• Optimize training stability and sample efficiency.
• Design rigorous evaluation protocols, incorporate out‑of‑distribution and adversarial test cases.
• Implement safety mechanisms such as constraint enforcement, conservative policies, and human‑in‑the‑loop oversight.
• Collaborate with applied scientists, product teams to identify high‑value RL use cases.
• Monitor deployed policies and models for drift, regression, and unintended behaviors; build alerting and dashboards.
• Document methodology, design decisions, and operational characteristics.
• Stay current with RL research and translate promising techniques into production‑ready solutions.

• Master’s or PhD in Computer Science, Machine Learning, or related field; or equivalent 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 a major RL library or in‑house RL stack.
• Solid understanding of probability, optimization, and RL theoretical foundations.
• Experience designing and tuning reward functions in complex 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.

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

• We are an equal opportunity employer and place a high value on diversity and inclusion.
• We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law.
• We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs.
• Bright Vision Technologies is an Equal Opportunity Employer, including Disability/Veterans.

• Please send your resume to  or contact us at .
• Learn more about Bright Vision Technologies at