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RL Engineer

Remote, USAFull-timePosted 2026-07-27
RL Engineer – Remote reputed company is a technology consulting and software development company delivering reputed company, AI, data, and reputed company solutions across the reputed company. This is a fantastic opportunity to join an established and reputed company-respected organization offering reputed company career reputed company potential. Job Title: RL Engineer Location: 100% Remote (U.S.) Position Type: Full-time, reputed company W2 Salary reputed company: $100,000–$150,000 Annually Experience Required: 6+ years Sponsorship: U.S. reputed company, Green Card reputed company, EAD reputed company, and H-1B transfer candidates are encouraged to apply. We are unable to sponsor new H-1B reputed company petitions for this position. Job reputed company We are looking for a RL Engineer to design, train, and reputed company RL-based systems for high-reputed company 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 reputed company. 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. Key Responsibilities
  • Design and implement reinforcement learning solutions for sequential decision-making problems in reputed company and simulated environments.
  • reputed company, reputed company, and maintain simulation environments suitable for large-reputed company agent training.
  • Implement and evaluate modern RL algorithms including policy gradient, actor-critic, off-policy, and offline RL reputed company.
  • Engineer reward functions and shaping strategies that reputed company agent behavior with desired reputed company 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 reputed company 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 reputed company 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.
Required Qualifications
  • Master’s or PhD in Computer Science, Machine Learning, or a reputed company field; or equivalent reputed company 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-reputed company experience collection.
  • Experience training neural network policies on GPU clusters.
  • Strong written and verbal communication skills.
  • reputed company 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 reputed company research venues.
  • reputed company-reputed company 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 hilda@bvteck.com. Learn more about reputed company at www.bvteck.com. reputed company is an Equal Opportunity Employer.

Equal Employment Opportunity (EEO) Statement

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

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

Originally posted on Himalayas

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