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I'm leading the fastest growing technology, machine learning, for the fastest moving market segment, startups, at the largest cloud provider in the world, AWS. There's no better job.
Allie Miller, global head of machine learning business development for startups and venture capital for AWS

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59 results found
  • (Updated 4 days ago)
    As a research scientist, you will use your experience to initiate the design, development, execution and implementation of scientific research projects. Working closely with fellow research scientists and product managers, you will use your experience in modeling, statistics, and simulation to design models of new policies, simulate their performance, and evaluate their benefits and impacts to cost, reliability, and speed of our fulfillment network.Our teams are looking for experience in network and combinatorial optimization, algorithms, data structures, statistics, and/or machine learning. This position requires superior analytical thinking, and ability to apply their technical and statistical knowledge to identify opportunities for real world applications. You should be able to mine and analyze large data, and be able to use necessary programming and statistical analysis software/tools to do so.We are hiring for the following team in Berlin:Team Name: Berlin Alexa NLUDomain / Research Focus: Natural Language UnderstandingTeam Description: The Berlin Alexa AI team’s mission is to deliver a product that allows customers to build Natural Language Understanding (NLU) models fast and efficient, supported by a user-friendly environment that allows for experimentation. We own model builds and are working on multiple ongoing research science topics such as model accuracy improvement, model trustworthy and robustness assessment.
  • Are you a MS or PhD student interested in a 2022 Applied Science Internship in the field of Computer Vision, or Machine Learning/Deep Learning?Do you enjoy diving deep into hard technical problems and coming up with solutions that enable successful products that improve the lives of people in a meaningful way?If this describes you, come join our research teams at Amazon. As an Applied Science Intern, you will have access to large datasets with billions of images and video to build large-scale machine learning systems. Additionally, you will analyze and model terabytes of text, images, and other types of data to solve real-world problems and translate business and functional requirements into quick prototypes or proofs of concept.We are looking for smart scientists capable of using a variety of domain expertise combined with machine learning and statistical techniques to invent, design, evangelize, and implement state-of-the-art solutions for never-before-solved problems.We are hiring interns for the following team in Luxembourg:Team Name: Network Planning Research Science EU ATSDoman / Research Focus: Operations Research, Approximation Algorithms & Combinatorial OptimizationTeam Description: We design and implement scalable algorithms to solve combinatorial optimisation problems. Example problems are facility location, max coverage, network flows, scheduling, vehicle routing, network design, all with multiple millions of variables and constraints
  • (Updated 16 days ago)
    )As a research scientist, you will use your experience to initiate the design, development, execution and implementation of scientific research projects. Working closely with fellow research scientists and product managers, you will use your experience in modeling, statistics, and simulation to design models of new policies, simulate their performance, and evaluate their benefits and impacts to cost, reliability, and speed of our fulfillment network.Our teams are looking for experience in network and combinatorial optimization, algorithms, data structures, statistics, and/or machine learning. This position requires superior analytical thinking, and ability to apply their technical and statistical knowledge to identify opportunities for real world applications. You should be able to mine and analyze large data, and be able to use necessary programming and statistical analysis software/tools to do so.The following teams have intern positions in Luxembourg:Team Name: EU RME (Reliability Maintenance Engineering)Domain /Research Focus: Optimization & Simulation, Time Series Description: EU RME Predictive Analytics’ mission is to provide the technical expertise needed to drive the Spare Parts and Predictive Maintenance programs for over 2000 maintenance engineers, managers and administrators by supporting the entire network managed by EU RME, which may include non-EU locations (such as Singapore, Australia and Japan). Our vision is to use advanced Machine Learning models and software solutions to deploy predictive models that can be used to optimize equipment maintenance, reduce downtime costs, improve Spare Parts management and promote sustainability.
  • (Updated 17 days ago)
    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的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的合作,如Alex Smola、Stefano Soatto、Pietro Perona、Bernhard Schölkopf、George Karypis、Thomas Brox、David Wipf、李沐、张伟楠、严骏驰、黄增峰、邱锡鹏、付彦伟、张峥等。你将了解并学习图神经网络的前沿算法理论,参与并驱动关于图神经网络的算法与理论创新。
  • (Updated 9 days ago)
    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的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的合作,如Alex Smola、Stefano Soatto、Pietro Perona、Bernhard Schölkopf、George Karypis、Thomas Brox、David Wipf、李沐、张伟楠、严骏驰、黄增峰、邱锡鹏、付彦伟、张峥等。你将有机会参与将图神经网络算法运用到亚马逊图数据库服务的研究和开发工作,了解并学习如何将前沿科研成果运用到全球领先的云服务中。
  • LU, Luxembourg
    Job ID: 1751938
    (Updated 4 days ago)
    We are looking for motivated data scientists with excellent leadership skills, and the ability to develop, automate, and run analytical models of our systems. You will have strong modeling skills and are comfortable owning data and working from concept through to execution. This role will also build tools and support structures needed to analyze data, dive deep into data to resolve root cause of systems errors and changes, and present findings to business partners to drive improvements.Applicants have a demonstrated ability to manage medium-scale modeling projects, identify requirements, and build methodology and tools that are statistically grounded. You will have experience collaborating across organizational boundaries.
  • US, MA, North Reading
    Job ID: 1749008
    (Updated 4 days ago)
    Job summaryAre 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 image 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.We seek a talented and motivated engineer to tackle broad challenges in system-level analysis. You will work in a small team to quantify system performance at scale and to expand the breadth and depth of our analysis (e.g. increase the range of software components and warehouse processes covered by our models, develop our library of key performance indicators, construct experiments that efficiently root cause emergent behaviors). You will engage with growing teams of software development and warehouse design engineers to drive evolution of the AR system and of the simulation engine that supports our work.This role is a 6 month co-op to join AR full time (40 hours/week) from January-June 2022. Come join us in North Reading, MA, or in our newly expanded innovation hub in Westborough, MA!Both campuses provide a unique opportunity for co-ops to have direct access to robotics testing labs and manufacturing facilities.
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