Careers

亚马逊云科技上海人工智能实验室OpenSearch 研发团队正在招募应用科学实习生-多模态检索与生成方向实习生。OpenSearch是一个开源的搜索和数据分析套件, 它旨在为数据密集型应用构建解决方案,内置高性能、开发者友好的工具,并集成了强大的机器学习、数据处理功能,可以为客户提供灵活的数据探索、丰富和可视化功能,帮助客户从复杂的数据中发现有价值的信息。OpenSearch是现有AWS托管服务(AWS OpenSearch)的基础，OpenSearch核心团队负责维护OpenSearch代码库,他们的目标是使OpenSearch安全、高效、可扩展、可扩展并永远开源。 点击下方链接查看申请手册获得更多信息： https://amazonexteu.qualtrics.com/CP/File.php?F=F_55YI0e7rNdeoB6e Key job responsibilities 在这个实习期间,你将有机会: 1. 研究最新的搜索相关性人工智能算法。 2. 探索大模型技术在数据分析与可视化上的应用。 3. 了解主流搜索引擎Lucene的原理和应用。深入了解前沿自然语言处理技术和底层索引性能调优的结合。 4. 学习亚马逊云上的各种云服务。 5. 参与产品需求讨论,提出技术实现方案。 6. 与国内外杰出的开发团队紧密合作,学习代码开发和审查的流程。

Are you a PhD student interested in machine learning, natural language processing, computer vision, automated reasoning, or robotics? We are looking for skilled scientists capable of putting theory into practice through experimentation and invention, leveraging science techniques and implementing systems to work on massive datasets in an effort to tackle never-before-solved problems. A successful candidate will be a self-starter comfortable with ambiguity, strong attention to detail, and the ability to work in a fast-paced, ever-changing environment. As an Applied Science Intern, you will own the design and development of end-to-end systems. You’ll have the opportunity to create technical roadmaps, and drive production level projects that will support Amazon Science. You will work closely with Amazon scientists, and other science interns to develop solutions and deploy them into production. The ideal scientist must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. Amazon Science gives insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists use our working backwards method to enrich the way we live and work. To ensure a great internship experience, please keep these things in mind. This is a full time internship and requires an individual to work 40 hours a week for the duration of the internship. Amazon requires an intern to be located where their assigned team is. Amazon is happy to provide relocation and housing assistance if you are located 50 miles or further from the office location. For more information on the Amazon Science community please visit https://www.amazon.science. We are open to hiring candidates to work out of one of the following locations: Arlington, WA, USA | Bellevue, WA, USA | Boston, MA, USA | New York, NY, USA | Oceanside, CA, USA | Palo Alto, CA, USA | Quincy, MA, USA | Santa Clarita, CA, USA | Seattle, WA, USA | Tucson, AZ, USA

The Amazon Economics Team is hiring Economist Interns. We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to work with large and complicated data sets to solve real-world business problems. Some knowledge of econometrics, as well as basic familiarity with Stata, R, or Python is necessary. Experience with SQL, UNIX, Sawtooth, and Spark would be a plus. These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis. You will learn how to build data sets and perform applied econometric analysis at Internet speed collaborating with economists, data scientists and MBAʼs. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with future job market placement. Roughly 85% of interns from previous cohorts have converted to full-time economics employment at Amazon. If you are interested, please send your CV to our mailing list at econ-internship@amazon.com. We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA

The Amazon Economics Team is hiring Economist Interns. We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to work with large and complicated data sets to solve real-world business problems. Some knowledge of econometrics, as well as basic familiarity with Stata, R, or Python is necessary. Experience with SQL, UNIX, Sawtooth, and Spark would be a plus. These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis. You will learn how to build data sets and perform applied econometric analysis at Internet speed collaborating with economists, data scientists and MBAʼs. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with future job market placement. Roughly 85% of interns from previous cohorts have converted to full-time economics employment at Amazon. If you are interested, please send your CV to our mailing list at econ-internship@amazon.com. We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA

Are you inspired by invention? Is problem solving through teamwork in your DNA? Do you like the idea of seeing how your work impacts the bigger picture? Answer yes to any of these and you’ll fit right in here at Amazon Robotics. We are a smart team of doers that work passionately to apply cutting edge advances in robotics and software to solve real-world challenges that will transform our customers’ experiences in ways we can’t even imagine yet. We invent new improvements every day. We are Amazon Robotics and we will give you the tools and support you need to invent with us in ways that are rewarding, fulfilling and fun. Amazon Robotics is seeking Applied Science Interns and Co-ops with a passion for robotic research to work on cutting edge algorithms for robotics. Our team works on challenging and high-impact projects within robotics. Examples of projects include allocating resources to complete a million orders a day, coordinating the motion of thousands of robots, autonomous navigation in warehouses, identifying objects and damage, and learning how to grasp all the products Amazon sells. As an Applied Science Intern/Co-op at Amazon Robotics, you will be working on one or more of our robotic technologies such as autonomous mobile robots, robot manipulators, and computer vision identification technologies. The intern/co-op project(s) and the internship/co-op location are determined by the team the student will be working on. Please note that by applying to this role you would be considered for Applied Scientist summer intern, spring co-op, and fall co-op roles on various Amazon Robotics teams. These teams work on robotics research within areas such as computer vision, machine learning, robotic manipulation, navigation, path planning, perception, optimization and more. Learn more about Amazon Robotics: https://amazon.jobs/en/teams/amazon-robotics

The Amazon Economics Team is hiring Economist Interns. We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to work with large and complicated data sets to solve real-world business problems. Some knowledge of econometrics, as well as basic familiarity with Stata, R, or Python is necessary. Experience with SQL, UNIX, Sawtooth, and Spark would be a plus. These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis. You will learn how to build data sets and perform applied econometric analysis at Internet speed collaborating with economists, data scientists and MBAʼs. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with future job market placement. Roughly 85% of interns from previous cohorts have converted to full-time economics employment at Amazon. If you are interested, please send your CV to our mailing list at econ-internship@amazon.com. We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA

Internship Direction: Multi-Modal Retrieval and Generation 深度学习技术的进步正在推动人工智能领域的快速发展，将多个学科领域如计算机视觉、自然语言处理、图与网络数据理解、系统工程以及优化理论等紧密结合。同时，众多深度学习开源项目，不仅加速了学术研究的进程，也推动了技术的商业化和社会化应用。 亚马逊上海人工智能研究院是深度学习研究的领军团队之一。我们的研究包括但不限于以下方向：深度学习基础理论、自然语言处理、计算机视觉、图机器学习、高性能计算、智能推荐系统、反欺诈与风控、知识图谱构建以及智能决策系统等。研究院积极推进深度学习的开源生态建设，其主攻的深度图网络DGL（Deep Graph Library）开源库是该领域的领跑平台。我们致力于通过跨领域的研究和合作，推进人工智能技术的边界，并通过开源项目的贡献，促进全球研究社区的共同进步。 我们诚邀对深度学习和人工智能充满热情的实习生加入我们的团队。我们希望通过你的智慧和努力，共同探索深度学习在各研究方向和应用领域的新算法和模型，进一步扩大我们研究的深度和广度。在实习期间，你将有机会在资深mentor的指导下深入研究深度学习的子领域或具体应用场景，掌握该领域的发展趋势和关键技术，实现创新模型，并有可能通过开源贡献或学术发表，向全球科研和工业界展示你的成果。 除了每天能与亚马逊上海人工智能研究院的同事们交流外，实习生还将有机会和亚马逊其他部门的同事、上海一流高校的顶级教授、和来自世界各地的一流专家合作，如Alon Halevy, Christos Faloutsos、Stefano Soatto、Pietro Perona、George Karypis、Thomas Brox、 David Wipf、付彦伟、张伟楠、张牧涵、邱锡鹏、张岳、张峥等。 点击下方链接查看申请手册获得更多信息： https://amazonexteu.qualtrics.com/CP/File.php?F=F_55YI0e7rNdeoB6e The advancements in deep learning technology are driving rapid development in the field of artificial intelligence, closely integrating multiple disciplines such as computer vision, natural language processing, graph and network processing, systems engineering, and optimization theory. Moreover, numerous deep learning open-source projects have not only accelerated the pace of academic research but also promoted the commercialization and social application of technology. The AWS Shanghai AI Lab is one of the leading institutes in deep learning research. Our research areas include, but are not limited to, the foundational theory of deep learning, natural language processing, computer vision, graph machine learning, high-performance computing, intelligent recommendation systems, fraud detection and risk control, knowledge graph construction, and intelligent decision-making systems. The institute actively promotes the construction of an open-source ecosystem for deep learning, highlighting the Deep Graph Library (DGL) as a leading platform in its field. We are committed to pushing the boundaries of AI technology through interdisciplinary research and collaboration, and by contributing to open-source projects, we aim to promote progress with the global research community altogether. We warmly invite interns who are passionate about deep learning and artificial intelligence to join our team. We hope to explore new algorithms and models in various research directions and application areas of deep learning together, further expanding the depth and breadth of our research. During the internship, you will have the opportunity to delve into subfields or specific application scenarios of deep learning under the guidance of experienced mentors, grasp the development trends and key technologies of the field, create innovative models, and showcase your results to the global scientific and industrial communities through open-source contributions or academic publications. In addition to daily interactions with colleagues at the AWS Shanghai AI Lab, interns will also have the opportunity to collaborate with colleagues from other departments of Amazon, top professors from leading universities in Shanghai, and world-class experts from around the globe, such as Alon Halevy, Christos Faloutsos, Stefano Soatto, Pietro Perona, George Karypis, Thomas Brox, David Wipf, Yanwei Fu, Weinan Zhang, Muhan Zhang, Xipeng Qiu, Yue Zhang, Zheng Zhang, and others.

Internship Direction: Open Source Development 深度学习是当前人工智能领域最热门的研究方向，它将机器学习、统计学、优化和系统工程紧密地结合在一起。深度学习成功的关键因素之一便是在计算机视觉、自然语言处理、时间序列、深度图学习和强化学习等领域里出现的众多开源项目。这些项目既可以被用来复现研究成果，也可以帮助实际应用的快速部署落地。 亚马逊上海人工智能研究院主攻的深度图网络DGL（Deep Graph Library）开源库是该领域的领跑平台。基于深度图计算的研究内容非常丰富，涵盖：1）基础理论研究；2）高性能、高容量核心引擎开发；3）重要的子领域模型研发（推荐系统、反欺诈和风控、知识图谱、制药、时域深度图计算、计算机视觉、自然语言处理、自动知识抽取）；4）客户的应用场景落地。 我们正在招募聪明努力的实习生，希望一起为开源生态添砖加瓦。我们期望能实现更多图神经网络在各个研究方向与应用领域的高级算法，让DGL在前沿研究与应用落地上越来越强大称手。在实习期间，你将在mentor的指导下深入调研图神经网络的具体子研究或应用领域，了解该领域发展脉络与重要工作，实现重要的模型快速进入该领域的最前沿，在此基础上提出更新的算法，通过开源发布让全世界的科研人员受益，也通过合作发表论文分享给整个学术圈。 除了每天能与亚马逊上海人工智能研究院的同事们交流外，实习生还将有机会和亚马逊其他部门的同事、上海一流高校的顶级教授、和来自世界各地的一流专家合作，如Matthias Bethge、Stefano Soatto、Pietro Perona、George Karypis、Thomas Brox、David Wipf、付彦伟、张伟楠、邱锡鹏、张岳、张峥等。 The advancements in deep learning technology are driving rapid development in the field of artificial intelligence, closely integrating multiple disciplines such as computer vision, natural language processing, graph and network processing, systems engineering, and optimization theory. Moreover, numerous deep learning open-source projects have not only accelerated the pace of academic research but also promoted the commercialization and social application of technology. The AWS Shanghai AI Lab is one of the leading institutes in deep learning research. Our research areas include, but are not limited to, the foundational theory of deep learning, natural language processing, computer vision, graph machine learning, high-performance computing, intelligent recommendation systems, fraud detection and risk control, knowledge graph construction, and intelligent decision-making systems. The institute actively promotes the construction of an open-source ecosystem for deep learning, highlighting the Deep Graph Library (DGL) as a leading platform in its field. We are committed to pushing the boundaries of AI technology through interdisciplinary research and collaboration, and by contributing to open-source projects, we aim to promote progress with the global research community altogether. We warmly invite interns who are passionate about deep learning and artificial intelligence to join our team. We hope to explore new algorithms and models in various research directions and application areas of deep learning together, further expanding the depth and breadth of our research. During the internship, you will have the opportunity to delve into subfields or specific application scenarios of deep learning under the guidance of experienced mentors, grasp the development trends and key technologies of the field, create innovative models, and showcase your results to the global scientific and industrial communities through open-source contributions or academic publications. In addition to daily interactions with colleagues at the AWS Shanghai AI Lab, interns will also have the opportunity to collaborate with colleagues from other departments of Amazon, top professors from leading universities in Shanghai, and world-class experts from around the globe, such as Alon Halevy, Christos Faloutsos, Stefano Soatto, Pietro Perona, George Karypis, Thomas Brox, David Wipf, Yanwei Fu, Weinan Zhang, Muhan Zhang, Xipeng Qiu, Yue Zhang, Zheng Zhang, and others. 点击下方链接查看申请手册获得更多信息： https://amazonexteu.qualtrics.com/CP/File.php?F=F_55YI0e7rNdeoB6e Key job responsibilities 使用Python/C++ 开发并维护广受欢迎的开源机器学习系统Deep Graph Library (DGL)

Internship Direction: Relational Machine Learning 深度学习技术的进步正在推动人工智能领域的快速发展，将多个学科领域如计算机视觉、自然语言处理、图与网络数据理解、系统工程以及优化理论等紧密结合。同时，众多深度学习开源项目，不仅加速了学术研究的进程，也推动了技术的商业化和社会化应用。 亚马逊上海人工智能研究院是深度学习研究的领军团队之一。我们的研究包括但不限于以下方向：深度学习基础理论、自然语言处理、计算机视觉、图机器学习、高性能计算、智能推荐系统、反欺诈与风控、知识图谱构建以及智能决策系统等。研究院积极推进深度学习的开源生态建设，其主攻的深度图网络DGL（Deep Graph Library）开源库是该领域的领跑平台。我们致力于通过跨领域的研究和合作，推进人工智能技术的边界，并通过开源项目的贡献，促进全球研究社区的共同进步。 我们诚邀对深度学习和人工智能充满热情的实习生加入我们的团队。我们希望通过你的智慧和努力，共同探索深度学习在各研究方向和应用领域的新算法和模型，进一步扩大我们研究的深度和广度。在实习期间，你将有机会在资深mentor的指导下深入研究深度学习的子领域或具体应用场景，掌握该领域的发展趋势和关键技术，实现创新模型，并有可能通过开源贡献或学术发表，向全球科研和工业界展示你的成果。 除了每天能与亚马逊上海人工智能研究院的同事们交流外，实习生还将有机会和亚马逊其他部门的同事、上海一流高校的顶级教授、和来自世界各地的一流专家合作，如Alon Halevy, Christos Faloutsos、Stefano Soatto、Pietro Perona、George Karypis、Thomas Brox、 David Wipf、付彦伟、张伟楠、张牧涵、邱锡鹏、张岳、张峥等。 The advancements in deep learning technology are driving rapid development in the field of artificial intelligence, closely integrating multiple disciplines such as computer vision, natural language processing, graph and network processing, systems engineering, and optimization theory. Moreover, numerous deep learning open-source projects have not only accelerated the pace of academic research but also promoted the commercialization and social application of technology. The AWS Shanghai AI Lab is one of the leading institutes in deep learning research. Our research areas include, but are not limited to, the foundational theory of deep learning, natural language processing, computer vision, graph machine learning, high-performance computing, intelligent recommendation systems, fraud detection and risk control, knowledge graph construction, and intelligent decision-making systems. The institute actively promotes the construction of an open-source ecosystem for deep learning, highlighting the Deep Graph Library (DGL) as a leading platform in its field. We are committed to pushing the boundaries of AI technology through interdisciplinary research and collaboration, and by contributing to open-source projects, we aim to promote progress with the global research community altogether. We warmly invite interns who are passionate about deep learning and artificial intelligence to join our team. We hope to explore new algorithms and models in various research directions and application areas of deep learning together, further expanding the depth and breadth of our research. During the internship, you will have the opportunity to delve into subfields or specific application scenarios of deep learning under the guidance of experienced mentors, grasp the development trends and key technologies of the field, create innovative models, and showcase your results to the global scientific and industrial communities through open-source contributions or academic publications. In addition to daily interactions with colleagues at the AWS Shanghai AI Lab, interns will also have the opportunity to collaborate with colleagues from other departments of Amazon, top professors from leading universities in Shanghai, and world-class experts from around the globe, such as Alon Halevy, Christos Faloutsos, Stefano Soatto, Pietro Perona, George Karypis, Thomas Brox, David Wipf, Yanwei Fu, Weinan Zhang, Muhan Zhang, Xipeng Qiu, Yue Zhang, Zheng Zhang, and others. 点击下方链接查看申请手册获得更多信息： https://amazonexteu.qualtrics.com/CP/File.php?F=F_55YI0e7rNdeoB6e

Internship Direction: Agent for Data Analytics 深度学习技术的进步正在推动人工智能领域的快速发展，将多个学科领域如计算机视觉、自然语言处理、图与网络数据理解、系统工程以及优化理论等紧密结合。同时，众多深度学习开源项目，不仅加速了学术研究的进程，也推动了技术的商业化和社会化应用。 亚马逊上海人工智能研究院是深度学习研究的领军团队之一。我们的研究包括但不限于以下方向：深度学习基础理论、自然语言处理、计算机视觉、图机器学习、高性能计算、智能推荐系统、反欺诈与风控、知识图谱构建以及智能决策系统等。研究院积极推进深度学习的开源生态建设，其主攻的深度图网络DGL（Deep Graph Library）开源库是该领域的领跑平台。我们致力于通过跨领域的研究和合作，推进人工智能技术的边界，并通过开源项目的贡献，促进全球研究社区的共同进步。 我们诚邀对深度学习和人工智能充满热情的实习生加入我们的团队。我们希望通过你的智慧和努力，共同探索深度学习在各研究方向和应用领域的新算法和模型，进一步扩大我们研究的深度和广度。在实习期间，你将有机会在资深mentor的指导下深入研究深度学习的子领域或具体应用场景，掌握该领域的发展趋势和关键技术，实现创新模型，并有可能通过开源贡献或学术发表，向全球科研和工业界展示你的成果。 除了每天能与亚马逊上海人工智能研究院的同事们交流外，实习生还将有机会和亚马逊其他部门的同事、上海一流高校的顶级教授、和来自世界各地的一流专家合作，如Alon Halevy, Christos Faloutsos、Stefano Soatto、Pietro Perona、George Karypis、Thomas Brox、 David Wipf、付彦伟、张伟楠、张牧涵、邱锡鹏、张岳、张峥等。 The advancements in deep learning technology are driving rapid development in the field of artificial intelligence, closely integrating multiple disciplines such as computer vision, natural language processing, graph and network processing, systems engineering, and optimization theory. Moreover, numerous deep learning open-source projects have not only accelerated the pace of academic research but also promoted the commercialization and social application of technology. The AWS Shanghai AI Lab is one of the leading institutes in deep learning research. Our research areas include, but are not limited to, the foundational theory of deep learning, natural language processing, computer vision, graph machine learning, high-performance computing, intelligent recommendation systems, fraud detection and risk control, knowledge graph construction, and intelligent decision-making systems. The institute actively promotes the construction of an open-source ecosystem for deep learning, highlighting the Deep Graph Library (DGL) as a leading platform in its field. We are committed to pushing the boundaries of AI technology through interdisciplinary research and collaboration, and by contributing to open-source projects, we aim to promote progress with the global research community altogether. We warmly invite interns who are passionate about deep learning and artificial intelligence to join our team. We hope to explore new algorithms and models in various research directions and application areas of deep learning together, further expanding the depth and breadth of our research. During the internship, you will have the opportunity to delve into subfields or specific application scenarios of deep learning under the guidance of experienced mentors, grasp the development trends and key technologies of the field, create innovative models, and showcase your results to the global scientific and industrial communities through open-source contributions or academic publications. In addition to daily interactions with colleagues at the AWS Shanghai AI Lab, interns will also have the opportunity to collaborate with colleagues from other departments of Amazon, top professors from leading universities in Shanghai, and world-class experts from around the globe, such as Alon Halevy, Christos Faloutsos, Stefano Soatto, Pietro Perona, George Karypis, Thomas Brox, David Wipf, Yanwei Fu, Weinan Zhang, Muhan Zhang, Xipeng Qiu, Yue Zhang, Zheng Zhang, and others. 点击下方链接查看申请手册获得更多信息： https://amazonexteu.qualtrics.com/CP/File.php?F=F_55YI0e7rNdeoB6e