强化学习工程师
RL Engineer
RL工程师 – 远程办公
Bright Vision Technologies是一家技术咨询和软件开发公司,为美国各地提供云、AI、数据和企业解决方案。这是一个加入一家知名且受人尊敬的组织的绝佳机会,提供巨大的职业发展潜力。
职位名称:RL工程师
工作地点:100%远程(美国)
职位类型:全职,直接W2
薪资范围:每年8万美元–10万美元
所需经验:6年以上
赞助:美国公民、绿卡持有者、EAD持有者以及H-1B转签候选人欢迎申请。我们无法为该职位的新H-1B签证申请提供赞助。
职位简介
我们正在寻找一名RL工程师,负责设计、训练和部署基于强化学习的系统,解决仅靠监督学习无法解决的高影响决策问题。该职位需要对现代强化学习算法、仿真环境、奖励建模以及在大规模上训练和评估策略的工程复杂性有深入了解。理想的候选人兼具研究深度和工程务实精神,有将RL解决方案从实验室带入生产环境的经验,其中稳定性、安全性和持续改进至关重要。
必备资格
· 计算机科学、机器学习或相关领域的硕士或博士学位;或同等的实际工作经验。
- 六年或以上强化学习研究和工程经验。
- 熟练掌握Python和现代深度学习框架。
- 至少一个主要RL库或内部RL堆栈的实际操作经验。
- 对概率、优化和强化学习的理论基础有扎实的理解。
- 在非简单环境中设计和调整奖励函数的经验。
- 熟悉仿真环境和大规模经验收集。
- 在GPU集群上训练神经网络策略的经验。
- 强大的书面和口头沟通能力。
- 有发布或推出有影响力的RL工作的记录。
优先考虑的资格
· 具备大型语言模型的RLHF经验。
- 熟悉多智能体RL或分层RL。
- 有机器人、控制系统或自动驾驶方面的经验。
- 在RL或相关研究领域有发表论文。
- 对RL库或环境有开源贡献。
申请方式
您想了解更多这个机会吗?如需立即考虑,请将简历发送至 。了解更多关于Bright Vision Technologies的信息。
查看英文原文
RL 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: RL Engineer
Location: 100% Remote (U.S.)
Position Type: Full-time, Direct W2
Salary Range: $80,000–$100,000 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 RL 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 . 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.
Originally posted on Himalayas