远程工作雷达

自主学习工程师

Autonomous Learning Engineer

AI开发工程限定地区(需当地身份)
公司Bright Vision Technologies
薪资$130,000 - $180,000/年
工作地点United States
地域资格限定地区(需当地身份)
时区要求日间重叠约 9 小时,基本正常作息
用工类型Full Time
发布时间今天
数据来源Himalayas
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注意地域限制:该职位明确限定在 United States 招聘。如果你是位于中国大陆的求职者,通常需要当地工作身份才能投递,或需与雇主确认是否接受独立合同(Contractor)形式合作。

Bright Vision Technologies 是一家技术咨询和软件开发公司,为美国各地提供云计算、人工智能、数据和企业解决方案。加入一家知名且备受尊敬的组织,这是一个绝佳的机会,提供巨大的职业发展潜力。
职位名称
自主学习工程师
地点:100% 远程(美国)
职位类型:全职,直接 W2
薪资范围:每年 13 万至 18 万美元
经验要求:10 年以上
赞助:美国公民、绿卡持有者、EAD 持有者和 H-1B 转移候选人欢迎申请。我们无法为该职位提供新的 H-1B 签证申请。
职位简介
Bright Vision Technologies 正在寻找一位经验丰富的自主学习工程师,拥有 10 年以上人工智能、强化学习(RL)和深度学习经验,负责设计、训练和部署用于复杂现实应用的智能决策系统。理想的候选人应具备 Python、强化学习、深度学习、仿真环境、分布式训练和 RLHF(从人类反馈中学习强化)方面的深厚专业知识,同时推动可扩展、生产就绪的自主学习解决方案的架构和部署。
主要职责

  • 为复杂的决策和自主系统设计、开发和部署先进的强化学习解决方案。
  • 使用分布式计算和 GPU 加速基础设施构建可扩展的强化学习训练流水线。
  • 设计、构建和优化用于训练和验证强化学习代理的仿真环境。
  • 开发、实现和评估现代 RL 算法、奖励模型和策略优化技术。
  • 构建利用 RLHF、模仿学习、离线强化学习和多智能体学习方法的自主学习系统。
  • 提高模型收敛性、样本效率、训练稳定性、推理性能和生产可扩展性。
  • 将强化学习模型集成到生产应用程序中,同时确保可靠性、安全性、监控和持续改进。
  • 与 AI 研究人员、数据科学家、软件工程师和产品团队合作,交付企业级 AI 解决方案。
  • 指导工程师并提供强化学习架构、实验和工程最佳实践方面的技术领导力。
  • 评估新兴的强化学习框架
查看英文原文

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
Autonomous Learning Engineer
Location: 100% Remote (U.S.)
Position Type: Full-time, Direct W2
Salary Range: $130,000–$180,000 Annually
Experience Required:10+ 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
Bright Vision Technologies is seeking a highly experienced Autonomous Learning Engineer with 10+ years of experience in Artificial Intelligence, Reinforcement Learning (RL), and Deep Learning to design, train, and deploy intelligent decision-making systems for complex real-world applications. The ideal candidate will possess deep expertise in Python, reinforcement learning, deep learning, simulation environments, distributed training, and RLHF (Reinforcement Learning from Human Feedback) while driving the architecture and deployment of scalable, production-ready autonomous learning solutions.
Key Responsibilities

  • Design, develop, and deploy advanced reinforcement learning solutions for complex decision-making and autonomous systems.
  • Architect scalable reinforcement learning training pipelines using distributed computing and GPU-accelerated infrastructure.
  • Design, build, and optimize simulation environments for training and validating reinforcement learning agents.
  • Develop, implement, and evaluate modern RL algorithms, reward models, and policy optimization techniques.
  • Build autonomous learning systems leveraging RLHF, imitation learning, offline reinforcement learning, and multi-agent learning approaches.
  • Improve model convergence, sample efficiency, training stability, inference performance, and production scalability.
  • Integrate reinforcement learning models into production applications while ensuring reliability, safety, monitoring, and continuous improvement.
  • Collaborate with AI researchers, data scientists, software engineers, and product teams to deliver enterprise-scale AI solutions.
  • Mentor engineers and provide technical leadership on reinforcement learning architecture, experimentation, and engineering best practices.
  • Evaluate emerging reinforcement learning frameworks, algorithms, and research to drive continuous innovation.

Required Qualifications

  • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Robotics, Mathematics, or a related technical discipline.
  • 10+ years of professional experience in Artificial Intelligence, Machine Learning, Deep Learning, or Reinforcement Learning.
  • Expert-level programming skills in Python and extensive experience with deep learning frameworks such as PyTorch, TensorFlow, or JAX.
  • Strong experience with reinforcement learning libraries such as Ray RLlib, Stable-Baselines3, CleanRL, or Acme.
  • Hands-on experience developing simulation environments using tools such as Gymnasium/OpenAI Gym, Isaac Sim, MuJoCo, Unity ML-Agents, or NVIDIA Omniverse.
  • Experience with distributed training, GPU acceleration, model optimization, and large-scale AI infrastructure.
  • Strong understanding of reinforcement learning theory, optimization, probability, stochastic processes, and decision-making algorithms.
  • Experience deploying AI solutions on cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP).
  • Excellent analytical, communication, collaboration, and technical leadership skills.

Preferred Qualifications

  • Experience with RLHF, multi-agent reinforcement learning, robotics, autonomous systems, or control systems.
  • Hands-on experience with foundation models, LLM alignment, agentic AI, or autonomous AI agents.
  • Experience with MLOps, Kubernetes, Docker, CI/CD pipelines, and production AI deployment.
  • Publications in top AI conferences, open-source contributions, patents, or recognized technical leadership in reinforcement learning.
  • Knowledge of Responsible AI, AI safety, model governance, explainability, and regulatory compliance.
  • Ph.D. or Master's degree specializing in Artificial Intelligence, Machine Learning, Reinforcement Learning, Robotics, or Control Systems.

Interested in this opportunity? Apply today for immediate consideration!
Email your updated resume:
Call or Text: (908) 505-3545
Learn more:
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

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