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职位：Applied scientist 应用科学家实习生 毕业时间：2025年10月 - 2026年9月之间毕业的应届毕业生 · 入职日期：2025年6月及之前 · 实习时间：保证一周实习4-5天全职实习，至少持续3个月 · 工作地点：北京朝阳区酒仙桥路恒通商务园区 · 校招信息请参考校园招聘申请手册： https://amazonexteu.qualtrics.com/CP/File.php?F=F_55YI0e7rNdeoB6e 投递须知： 1 填写简历申请时，请把必填和非必填项都填写完整。提交简历之后就无法修改了哦！ 2 学校的英文全称请准确填写。 如果您正在攻读NLP，IR或搜索领域专业的博士或硕士研究生，而且对应用科学家的实习工作感兴趣。如果您也喜爱深入研究棘手的技术问题并提出解决方案，用成功的产品显著地改善人们的生活。 那么，我们诚挚邀请您加入亚马逊的International Technology搜索团队改善Amazon的产品搜索服务。我们的目标是帮助亚马逊的客户找到他们所需的产品，并发现他们感兴趣的新产品。 这会是一份收获满满的工作。您每天的工作都与全球数百万亚马逊客户的体验紧密相关。您将提出和探索NLP和IR领域的创新，基于TB级别的产品和流量数据设计机器学习模型。您将集成这些模型到搜索引擎中为客户提供服务，通过数据，建模和客户反馈来完成闭环。您对模型的选择需要能够平衡业务指标和响应时间的需求。

Amazon Games is seeking a highly effective Senior Machine Learning Scientist to build and integrate novel ML, RL and Generative AI (Gen AI) approaches into our game pipelines and customer experiences. In this role, you will work closely with our game development studios and operations teams to research and develop generative AI-powered tools, pipelines and features across Amazon Games. At Amazon Games, our ambition is to create bold new experiences that foster community in and around our games. Our team of game industry veterans develops AAA multiplayer games and original IPs, with teams in Seattle, Orange County, San Diego, Montreal, and Bucharest. Amazon Games, through its Studios, Publishing, and Prime Gaming divisions collaborating with external partners, aims to develop, publish, and deliver compelling AAA games and content experiences for gamers to discover. Key job responsibilities - Drive the research, implementation, and productionizing for ambitious and complex AI/ML initiatives for Amazon Games. - Collaborate with game team engineers, designers and artists to design, develop, and integrate new generative AI tools into developer workflows. - Proactively identify and solve problems that affect the quality of life for players, operations, and other developers. - Stay up to date with and analyze the latest advancements, in generative AI technology, and continuously improve product features where meaningful improvements in cost, scalability, quality, or functionality can be achieved. - Consult and contribute to evaluations of other internal or 3rd party ML, RL and Gen AI services that could be leveraged by the project or the organization. A day in the life - You thrive in a collaborative environment where your decisions have significant impact and influence. - You are passionate about building game experiences that delight players. - You deliver great workflows, tools, and game innovations to your fellow developers and constantly seek improvement. - You want to be part of something exciting and unique in the gaming ecosystem. About the team The Amazon Games Studio AI Research team focuses on artificial intelligence innovation in gaming. Our highly skilled, multi-discipline team works across Machine Learning, Reinforcement Learning, and Generative AI to reimagine game development. We work closely with first-party game developers and partner studios to bring creative visions to life. Our mission is to use AI responsibly to transform gameplay experiences, enrich narratives, and provide creators with practical tools to optimize their production pipelines.

We are a part of Amazon Alexa Devices organization with the mission “delight customers through contextual and personalized proactive experiences that keep customers informed, engaged, and productive without cognitive burden”. We are developing an advanced system using Large Language Model (LLM) technologies to deliver engaging, intuitive, and adaptive content recommendations across all Amazon surfaces. We aim to facilitate seamless reasoning and customer experiences, surpassing the capabilities of previous machine learning models. We are looking for a passionate, talented, and resourceful Applied Scientist in the field of Natural Language Processing (NLP), Recommender Systems and/or Information Retrieval, to invent and build scalable solutions for a state-of-the-art context-aware speech assistant. A successful candidate will have strong machine learning background and a desire to push the envelope in one or more of the above areas. The ideal candidate would also enjoy operating in dynamic environments, be self-motivated to take on challenging problems to deliver big customer impact, shipping solutions via rapid experimentation and then iterating on user feedback and interactions. Key job responsibilities As an Applied Scientist on the team, you will collaborate with other applied scientists and engineers to develop novel algorithms to enable timely, relevant and delightful recommendations and conversations. Your work will directly impact our customers in the form of products and services that make use of various machine learning, deep learning and language model technologies. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in the state of art.

Do you want to join an innovative team of scientists who develop Agentic AI, LLM, and deep learning based solutions to help Amazon provide the best seller experience across the entire Seller life cycle, including recruitment, growth, support, risk mitigation and provide the best customer and seller experience? Do you want to build advanced algorithmic systems that help manage the trust and safety of millions of customer interactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data and creating state-of-the-art algorithms to solve real world problems? Are you excited by the opportunity to leverage GenAI and innovate on top of the state-of-the-art large language models to improve customer and seller experience? Do you like to build end-to-end business solutions and directly impact the profitability of the company? Do you like to innovate and create solutions that have cross-organizational impacts? If yes, then you may be a great fit to join the Machine Learning Accelerator team. Key job responsibilities The scope of a Senior Applied Scientist in the Selling Partner Services (SPS) Machine Learning Accelerator (MLA) team is to research and prototype Machine Learning applications that solve strategic business problems across SPS domains. Additionally, the scientist collaborates with engineers and business partners to design and implement solutions at scale that are of broad benefit to SPS organizations. They develop large-scale solutions for high impact projects, introduce tools and other techniques that can be used to solve problems from various perspectives, and show depth and competence in more than one area. They influence the team’s technical strategy by making insightful contributions to the team’s priorities, approach and planning. They develop and introduce tools and practices that streamline the work of the team, and they mentor junior team members and participate in hiring.

The Amazon Postdoctoral Science Program offers recent PhD graduates an exciting opportunity to gain hands-on industry experience, apply their specialized knowledge, and collaborate with Amazon's leading scientists. This program is designed for researchers who have completed their PhD within the past two years and are eager to bridge academia and industry, driving innovation at scale. “This program provides an excellent and fun opportunity to work on cutting-edge customer-obsessed research and learn from and collaborate with some of the brightest researchers and leading experts at Amazon,” said Sareh Nabi, a postdoctoral scientist in Amazon Ads who is participating in a postdoc pilot program. “It also provides a great platform to take the skillset I learned and apply it to a wide range of real-world applications on a large scale.” “This is an opportunity for outstanding researchers to work with us on our hardest scientific challenges,” said Jeremy Wyatt, senior manager of Amazon Robotics AI. “Amazon postdoctoral scientists will pursue exploratory work on our hardest problems, gaining industry experience and publishing the results in the best scientific venues.” Postdoctoral scientists will contribute to high-impact research initiatives, advance cutting-edge scientific developments, and publish their work in top-tier scientific journals. Participants will benefit from mentorship, access to Amazon's world-class resources, and exposure to real-world challenges with immediate customer impact. **Focus Areas** We are seeking candidates with expertise in foundational and applied research, particularly in: - Large Language Models (LLMs): Experience developing, fine-tuning, and scaling LLMs for diverse applications. - Graph Databases: Strong understanding of graph theory, data modeling, and implementation of graph database technologies in complex systems. - Mathematical Optimization: Good understanding of mathematical optimization, including mixed-integer optimization, combinatorial optimization, and robust optimization. **Basic Qualifications** - PhD in a relevant field (e.g., Computer Science, Operations Research, Mathematics, Statistics) received within 2 years of program start date. - Proven publication record in areas such as LLM, NLP, Generative AI, Graph Database, or other relevant domains. - Hands-on experience with technologies related to large language models, graph databases, and mathematical optimization. Preferred qualifications Postdocs demonstrate the following preferred job qualifications: - Ability to independently deliver results in a fast-paced environment - Publications at top-tier, peer-reviewed conferences and/or journals such as NurIPS, ICML, ICLR, CIKM, ICDE - Exceptional verbal and written communication skills - Expert knowledge in modeling and performance, operationalization, and scalability of scientific techniques and establishing decision strategies Required application materials: - CV, which lists all peer-reviewed publications and conferences - Research statement that outlines your research achievements and future research interests, and - A journal article or book chapter that demonstrates your domain expertise

AI is the most transformational technology of our time, capable of tackling some of humanity’s most challenging problems. That is why Amazon is investing in generative AI (GenAI) and the responsible development and deployment of large language models (LLMs) across all of our businesses. Come build the future of human-technology interaction with us. We are looking for a Research Scientist with strong technical skills which includes coding and natural language processing experience in dataset construction, training and evaluating models, and automatic processing of large datasets. You will play a critical role in driving innovation and advancing the state-of-the-art in natural language processing and machine learning. You will work closely with cross-functional teams, including product managers, language engineers, and other scientists. Key job responsibilities Specifically, the Research Scientist will: • Ensure quality of speech/language/other data throughout all stages of acquisition and processing, including data sourcing/collection, ground truth generation, normalization, transformation, cross-lingual alignment/mapping, etc. • Clean, analyze and select speech/language/other data to achieve goals • Build and test models that elevate the customer experience • Collaborate with colleagues from science, engineering and business backgrounds • Present proposals and results in a clear manner backed by data and coupled with actionable conclusions • Work with engineers to develop efficient data querying infrastructure for both offline and online use cases

Our customers have immense faith in our ability to deliver packages timely and as expected. A well planned network seamlessly scales to handle millions of package movements a day. It has monitoring mechanisms that detect failures before they even happen (such as predicting network congestion, operations breakdown), and perform proactive corrective actions. When failures do happen, it has inbuilt redundancies to mitigate impact (such as determine other routes or service providers that can handle the extra load), and avoids relying on single points of failure (service provider, node, or arc). Finally, it is cost optimal, so that customers can be passed the benefit from an efficiently set up network. Amazon Shipping is hiring Applied Scientists to help improve our ability to plan and execute package movements. As an Applied Scientist in Amazon Shipping, you will work on multiple challenging machine learning problems spread across a wide spectrum of business problems. You will build ML models to help our transportation cost auditing platforms effectively audit off-manifest (discrepancies between planned and actual shipping cost). You will build models to improve the quality of financial and planning data by accurately predicting ship cost at a package level. Your models will help forecast the packages required to be pick from shipper warehouses to reduce First Mile shipping cost. Using signals from within the transportation network (such as network load, and velocity of movements derived from package scan events) and outside (such as weather signals), you will build models that predict delivery delay for every package. These models will help improve buyer experience by triggering early corrective actions, and generating proactive customer notifications. Your role will require you to demonstrate Think Big and Invent and Simplify, by refining and translating Transportation domain-related business problems into one or more Machine Learning problems. You will use techniques from a wide array of machine learning paradigms, such as supervised, unsupervised, semi-supervised and reinforcement learning. Your model choices will include, but not be limited to, linear/logistic models, tree based models, deep learning models, ensemble models, and Q-learning models. You will use techniques such as LIME and SHAP to make your models interpretable for your customers. You will employ a family of reusable modelling solutions to ensure that your ML solution scales across multiple regions (such as North America, Europe, Asia) and package movement types (such as small parcel movements and truck movements). You will partner with Applied Scientists and Research Scientists from other teams in US and India working on related business domains. Your models are expected to be of production quality, and will be directly used in production services. You will work as part of a diverse data science and engineering team comprising of other Applied Scientists, Software Development Engineers and Business Intelligence Engineers. You will participate in the Amazon ML community by authoring scientific papers and submitting them to Machine Learning conferences. You will mentor Applied Scientists and Software Development Engineers having a strong interest in ML. You will also be called upon to provide ML consultation outside your team for other problem statements. If you are excited by this charter, come join us!

Amazon is looking for a passionate, talented, and inventive Scientist with a strong machine learning background to help build industry-leading Speech and Language technology. Our mission is 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. As a Speech and Language Scientist, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art in spoken language understanding. 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. We are hiring in the area of speech recognition (ASR) and associated technologies.

At Amazon, we believe that scientific innovation is essential to being the most customer-centric company in the world. Our scientists' ability to have an impact at scale allows us to attract some of the brightest minds in machine learning, artificial intelligence and related fields. Amazon scientists employ the company's working backwards method to identify problems to solve on behalf of customers in research areas ranging from machine learning to operations, GenAI, robotics, quantum computing, computer vision, economics, search, sustainability and more. Learn more about Amazon Science here: https://www.amazon.science/ We are hiring across multiple businesses and in many locations across the US. Apply here to learn more about open roles that could be a compelling fit for your background. Key job responsibilities You will be responsible for defining key research directions, adopting or inventing new machine learning techniques, conducting rigorous experiments, publishing results, and ensuring that research is translated into practice. You will develop long-term strategies, persuade teams to adopt those strategies, propose goals and deliver on them. You will also participate in organizational planning, hiring, mentorship and leadership development. You will be technically fearless and with a passion for building scalable science and engineering solutions. You will serve as a key scientific resource in full-cycle development (conception, design, implementation, testing to documentation, delivery, and maintenance).

Do you want to join an innovative team of scientists who invent and apply the most advanced machine learning and NLP techniques to create the best customer engagement experience on the earth? Do you want to revolutionize the way how customers solve their issues and get their questions answered? At Customer Engagement Technology (CET), we develop peculiar products that help customers solve problems. We innovate on behalf of customers, developing Bot, self-service, and associate-facing products that delight customers and support our world class customer service workforce. We are looking for talented Postdoctoral Scientists to join our CET Machine Learning team in Seattle, WA for a one-year, full-time research position to work on research and development of task oriented dialogue agents for the customer support domain. We utilize Large Language Models (LLMs) to address challenges within TOD systems, such as Natural Language Generation for generating system responses based, state tracking, decision making etc. We publish our research in top tier NLP and AI venues (EMNLP, ACL, AAAI, etc), and deploy ML powered chatbots primarily in the customer returns domain. Key job responsibilities In this role you will: • Work closely with a senior science advisor, collaborate with other scientists and engineers, and be part of Amazon’s vibrant and diverse global science community. • Publish your innovation in top-tier academic venues and hone your presentation skills. • Be inspired by challenges and opportunities to invent cutting-edge techniques in your area(s) of expertise.