Vienna, Austria
ICLR 2024
May 7 - 11, 2024
Vienna, Austria

Overview

The International Conference on Learning Representations (ICLR) is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence called representation learning, but generally referred to as deep learning.

Sponsorship Details

Gold
Booth #12

Accepted publications

Workshops

ICLR 2024 Workshop on AI4DifferentialEquations in Science
May 11
ICLR 2024 Workshop on Data-centric Machine Learning Research
May 11
ICLR 2024 Workshop on Generative Models for Decision Making
May 11
ICLR 2024 Workshop on LLM Agents
May 11
ICLR 2024 Workshop on Practical ML for Low Resource Settings (PML4LRS)
May 11
ICLR 2024 Workshop on Secure and Trustworthy Large Language Models (SET LLM)
May 11
ICLR 2024 Tiny Papers
May 11

Latest news

Work with us

GB, London
This role is available across multiple locations (United Kingdom, Luxembourg, Italy, Spain, Austria, Ireland, Poland and France). Amazon Internships have start dates throughout the year and can vary in length from 3-6 months for full-time. Please note these are not remote internships. Are you a MS or PhD student interested in a 2024 Internship in the field of Applied Sciences? Are you interested in machine learning, deep learning, speech, robotics, computer vision, optimization, quantum computing, automated reasoning, or formal methods? If so, we want to hear from you! We are looking for scientists with interest in using a variety of domain expertise to invent, design and implement state-of-the-art solutions for never-before-solved problems. At Amazon, you will grow into the high impact, visionary person you know you’re ready to be. Every day will be filled with developing new skills and achieving personal growth. How often can you say that your work changes the world? At Amazon, you’ll say it often. Join us and define tomorrow. For more information on the Amazon Science community please visit the Science hub page: https://www.amazon.science/ If you’re interested in hearing more or have questions about Amazon Science internships, please feel free to join us for one of our upcoming informational sessions which you can sign up for via the ‘Events Calendar’ in our EMEA Science Intern landing page; https://amazonscienceopportunities.splashthat.com/ Key job responsibilities As an Applied Science Intern, you will own the design and development of end-to-end systems. You’ll have the opportunity to write technical white papers, 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. You will have the opportunity to design new algorithms, models, or other technical solutions whilst experiencing Amazon’s customer focused culture. The ideal scientist must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. We are open to hiring candidates to work out of one of the following locations: Cambridge, GBR | Edinburgh, MLN, GBR | London, GBR
US, WA, Seattle
Do you have a strong science background and want to help build new technologies? Do you have a physics background and want to help build and test superconducting circuits? Would you love to help develop the algorithms and models that power computer vision services at Amazon, such as Amazon Rekognition, Amazon Go, Visual Search, etc? We are looking for builders, innovators, and entrepreneurs who want to bring their ideas to reality and improve the lives of millions of customers. Research interns at Amazon work passionately to apply cutting-edge advances in technology to solve real-world problems. As an intern, you will be challenged to apply theory into practice through experimentation and invention, develop new algorithms using modeling software and programming techniques for complex problems, implement prototypes and work with massive datasets. We hire research science interns to work in a number of domains including: • Quantum Computing • Computer Vision • Robotics • Operations Research • Speech Technologies • Machine Learning • Network Design/Cloud Our science recruitment team is looking for graduate students in several research fields to work as an intern with teams across Amazon including: AWS, Alexa, Advertising, IMDb, Grand Challenge, Consumer, Operations, HR and more! We are open to hiring candidates to work out of one of the following locations: Bellevue, WA, USA | New York, NY, USA | Pasadena, CA, USA | Seattle, WA, USA | Tuscon, AZ, USA
US, NY, New York
The Reinforcement Learning (RL) team within Amazon's Supply Chain is at the cutting edge of applying machine learning to real-world problems. We are seeking a talented Senior Applied Scientist with RL experience to join our team. Here you will be focused on making significant contributions to the field, through hands-on research in RL. If you are driven by innovation, we want to hear from you. In this role you'll have the opportunity to make meaningful advancements in machine learning and AI, contributing to both theoretical and applied aspects of ML and RL. Key job responsibilities - Design, implement, and evaluate innovative models, agents, and software prototypes. - Collaborate with a team of experienced scientists to drive technological advancements. - Develop novel solutions to complex business problems in collaboration with partner teams. - Contribute to Amazon's global science community through collaboration and publication of groundbreaking research. - Engage in research projects that contribute to the wider scientific community, sharing findings through publications in top-tier journals and conferences. A day in the life As part of our team, you will work alongside thought leaders like Sham Kakade and Dean Foster, contributing to academic research and complex, real-world applications. Your work will directly influence Amazon's global inventory planning systems, shaping decisions that affect billions of dollars worth of inventory and a wide array of product lines. You will tackle complex inventory planning challenges using RL, contributing both to the theoretical aspect of the field and its practical applications. We value creative thinking and the ability to approach problems from new perspectives. About the team Our team is at the forefront of machine learning research; we are dedicated to developing novel RL algorithms and applying them to complex, real-world challenges in Amazon's global inventory and supply chain network. Our focus is on both advancing theoretical knowledge and implementing these insights to optimize operations and enhance customer satisfaction. We foster a collaborative environment where exploration of new ideas and tackling complex problems is encouraged. The supply chain spans a wide range of operations, managing decisions that impact billions of dollars worth of inventory. For scientists passionate about impactful research in machine learning and AI, our team offers a dynamic and fulfilling environment to make a tangible difference in the field and Amazon's operations. We are open to hiring candidates to work out of one of the following locations: New York, NY, USA
US, CA, Santa Clara
AWS AI Research and Engineering (AIRE) is looking for world class scientists and engineers to work on the development of autonomous AI agents. At AWS AI/ML you will invent, implement, and deploy state of the art machine learning algorithms and systems. You will build prototypes and innovate on new learning techniques. You will interact closely with our customers and with the academic and research communities. You will be at the heart of a growing and exciting focus area for AWS and work with other acclaimed engineers and world famous scientists. Large-scale foundation models have been the powerhouse in many of the recent advancements in computer vision, natural language processing, automatic speech recognition, recommendation systems, and time series modeling. Developing such models requires not only skillful modeling in individual modalities, but also understanding of how to seamlessly combine them, and how to scale the modeling methods to learn with huge models and on large datasets. We seek a strong technical leader with domain expertise in machine learning, large language models and multimodal models, reinforcement learning and setting up simulation environments to benchmark and evaluate. AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS. Within AWS UC, Amazon Dedicated Cloud (ADC) roles engage with AWS customers who require specialized security solutions for their cloud services. A day in the life Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Hybrid Work We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices. About the team We are open to hiring candidates to work out of one of the following locations: Santa Clara, CA, USA
CN, Shanghai
DESCRIPTION The AWS Shanghai AI Lab is looking for a passionate, talented, and inventive staff in all AI domains with a strong machine learning background as a Senior Applied Scientist. Founded in 2018, the Shanghai Lab has been an innovation center of for long-term research projects across domains as machine learning, computer vision, natural language processing, and open-source AI system. Meanwhile, these incubated projects power products across various AWS services. As part of the lablet, you will take a leadership role and join a vibrant team with a diverse set of expertise in both machine learning and applicational domains. You will work on state-of-the-art solutions on fundamental research problems with other world-class scientists and engineers in AWS around the globe and across the boarders. You will have the responsibility to design and innovate solutions to our customers. You will build models to tame large amount of data, achieve industry-level scalability and efficiency, and along the way rapidly grow and build the team. BASIC QUALIFICATIONS * 5+ years of experience after PhD in Electrical Engineering, Computer Science, or related disciplines. Strong expertise in machine learning. * World-class track record in one of the sub-application domains of machine learning (e.g. NLP, CV, speech, graph machine learning, etc); publication record in top ML conferences/journals such as NeurIPS, ICML, ICLR, etc. * Experience in building full-stack machine learning solutions from scratch, including training, debugging and performance optimization. * Proficient in Python. Experiences with AI/ML frameworks and open-source projects (e.g., PyTorch, TensorFlow) are preferred. * Good English written and spoken communication skills. PREFERRED QUALIFICATIONS * Familiar with recent advances in domains as computer vision, natural language processing, multi-modality. * Critical and scientific thinking and the ability to invent, a track record of thought leadership and contributions that have advanced the field. * Sharp research taste. Experiences serving reviewers for top conferences/journals, AC/PC experiences are even better. * Experience in engineering practice of scalable, efficient, and highly optimized AI/ML production projects. We are open to hiring candidates to work out of one of the following locations: Shanghai, CHN
CN, 31, Shanghai
The AWS Shanghai AI Lab is looking for a passionate, talented, and inventive staff in all AI domains with a strong machine learning background as an Applied Scientist. Founded in 2018, the Shanghai Lab has been an innovation center of for long-term research projects across domains as machine learning, computer vision, natural language processing, and open-source AI system. Meanwhile, these incubated projects power products across various AWS services. As part of the lablet, you will take a leadership role and join a vibrant team with a diverse set of expertise in both machine learning and applicational domains. You will work on state-of-the-art solutions on fundamental research problems with other world-class scientists and engineers in AWS around the globe and across the boarders. You will have the responsibility to design and innovate solutions to our customers. You will build models to tame large amount of data, achieve industry-level scalability and efficiency, and along the way rapidly grow and build the team. We are open to hiring candidates to work out of one of the following locations: Shanghai, 31, CHN
CN, Shanghai
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 We are open to hiring candidates to work out of one of the following locations: Shanghai, CHN
CN, Shanghai
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. We are open to hiring candidates to work out of one of the following locations: Shanghai, CHN
CN, Shanghai
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 We are open to hiring candidates to work out of one of the following locations: Shanghai, CHN
CN, Shanghai
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) We are open to hiring candidates to work out of one of the following locations: Shanghai, CHN
US, MA, Boston
The Artificial General Intelligence (AGI) team is looking for a highly-skilled Senior Applied Scientist, to lead the development and implementation of cutting-edge algorithms and push the boundaries of efficient inference for Generative Artificial Intelligence (GenAI) models. As a Senior Applied Scientist, you will play a critical role in driving the development of GenAI technologies that can handle Amazon-scale use cases and have a significant impact on our customers' experiences. Key job responsibilities - Design and execute experiments to evaluate the performance of different decoding algorithms and models, and iterate quickly to improve results - Develop deep learning models for compression, system optimization, and inference - Collaborate with cross-functional teams of engineers and scientists to identify and solve complex problems in GenAI - Mentor and guide junior scientists and engineers, and contribute to the overall growth and development of the team We are open to hiring candidates to work out of one of the following locations: Bellevue, WA, USA | Boston, MA, USA | New York, NY, USA
US, CA, Sunnyvale
The Artificial General Intelligence (AGI) team is looking for a highly skilled and experienced Senior Applied Scientist, to lead the development and implementation of cutting-edge algorithms and models for supervised fine-tuning and reinforcement learning through human feedback; with a focus across text, image, and video modalities. As a Senior Applied Scientist, you will play a critical role in driving the development of Generative AI (Gen AI) technologies that can handle Amazon-scale use cases and have a significant impact on our customers' experiences. Key job responsibilities - Collaborate with cross-functional teams of engineers, product managers, and scientists to identify and solve complex problems in Gen AI - Design and execute experiments to evaluate the performance of different algorithms and models, and iterate quickly to improve results - Think big about the arc of development of Gen AI over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems - Communicate results and insights to both technical and non-technical audiences, including through presentations and written reports - Mentor and guide junior scientists and engineers, and contribute to the overall growth and development of the team We are open to hiring candidates to work out of one of the following locations: Bellevue, WA, USA | Cambridge, MA, USA | New York, NY, USA | Sunnyvale, CA, USA
US, CA, Sunnyvale
The Artificial General Intelligence (AGI) team is looking for a highly skilled and experienced Applied Scientist, to support the development and implementation of cutting-edge algorithms and models for supervised fine-tuning and reinforcement learning through human feedback; with a focus across text, image, and video modalities. As an Applied Scientist, you will play a critical role in supporting the development of Generative AI (Gen AI) technologies that can handle Amazon-scale use cases and have a significant impact on our customers' experiences. Key job responsibilities - Collaborate with cross-functional teams of engineers, product managers, and scientists to identify and solve complex problems in Gen AI - Design and execute experiments to evaluate the performance of different algorithms and models, and iterate quickly to improve results - Think big about the arc of development of Gen AI over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems - Communicate results and insights to both technical and non-technical audiences, including through presentations and written reports We are open to hiring candidates to work out of one of the following locations: Bellevue, WA, USA | Cambridge, MA, USA | New York, NY, USA | Sunnyvale, CA, USA
US, WA, Seattle
The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Senior Applied Scientist with a strong deep learning background, to build industry-leading technology with Large Language Models (LLMs) and multimodal systems. Key job responsibilities As a Senior Applied Scientist with the AGI team, you will work with talented peers to lead the development of novel algorithms and modeling techniques, to advance the state of the art with LLMs. Your work will directly impact our customers in the form of products and services that make use of speech and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in spoken language understanding. About the team The AGI team has a mission to push the envelope in Automatic Speech Recognition (ASR), Natural Language Understanding (NLU), and Audio Signal Processing, in order to provide the best-possible experience for our customers. We are open to hiring candidates to work out of one of the following locations: Bellevue, WA, USA | Cambridge, MA, USA | New York, NY, USA | Seattle, WA, USA | Sunnyvale, CA, USA
US, CA, San Francisco
The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Senior Applied Scientist with a strong deep learning background, to lead the development of industry-leading technology with multimodal systems. Key job responsibilities As a Senior Applied Scientist with the AGI team, you will lead the development of novel algorithms and modeling techniques to advance the state of the art with multimodal systems. Your work will directly impact our customers in the form of products and services that make use of vision and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate development with multimodal Large Language Models (LLMs) and Generative Artificial Intelligence (GenAI) in Computer Vision. About the team The AGI team has a mission to push the envelope with multimodal LLMs and GenAI in Computer Vision, in order to provide the best-possible experience for our customers. We are open to hiring candidates to work out of one of the following locations: San Francisco, CA, USA | Seattle, WA, USA