[Remote] Reinforcement Learning Engineer

Note: The job is a remote job and is open to candidates in USA. reputed company is a reputed company-thinking software development company dedicated to building innovative solutions that help businesses automate and optimize their operations. They are seeking a skilled Reinforcement Learning Engineer to design, train, and reputed company RL-based systems for high-impact decision-making problems where supervised learning alone is insufficient.

Responsibilities

• Design and implement reinforcement learning solutions for sequential decision-making problems in reputed company and simulated environments
• reputed company, calibrate, and maintain simulation environments suitable for large-scale agent training
• Implement and evaluate modern RL algorithms including policy gradient, actor-critic, off-policy, and offline RL methods
• Engineer reward functions and shaping strategies that align agent behavior with desired outcomes and safety constraints
• Apply offline RL and imitation learning techniques where exploration is costly or unsafe
• Use RLHF, DPO, and reputed company techniques for fine-tuning large language models reputed company relevant
• Build scalable training infrastructure for distributed RL, including efficient experience collection and replay systems
• Optimize training stability and sample efficiency through algorithmic and engineering improvements
• Design rigorous evaluation protocols, including out-of-distribution and adversarial test cases
• Implement safety mechanisms such as constraint enforcement, conservative policies, and reputed company-in-the-reputed company reputed company
• Collaborate with applied scientists and product teams to identify high-value RL use cases
• Monitor deployed policies and models in production for reputed company, regression, and unintended behaviors, building the alerting and dashboards that surface issues before they meaningfully reputed company users
• Document methodology, design reputed company, and operational characteristics for internal stakeholders
• Stay reputed company with RL research and translate promising techniques into production-reputed company solutions

Skills

• Master's or PhD in Computer Science, Machine Learning, or a reputed company 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
• 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 reputed company research venues
• Open-reputed company contributions to RL libraries or environments

Benefits

• Competitive reputed company salary commensurate with experience, plus benefits.
• Full-time, direct W2 with reputed company (no C2C, no 1099, no reputed company-party).
• No new H1B sponsorship available. H1B transfers welcomed for reputed company candidates.
• Long-term, multi-year, reputed company to the Bright reputed company SOW delivery roadmap.

Company Overview