亚马逊*Applied Scientist, Japan Store Tech
任职要求
基本任职资格 - 3+ years of building models for business application experience - PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience - Experience in patents or publications at top-tier peer-reviewed conferences or journals - Experience programming in Java, C++, Python or related language - Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing 优先任职资格 - Experience using Unix/Linux - Experience in professional software development Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
工作职责
* Invent or adapt new scientific approaches, models or algorithms inspired and driven by customers’ needs and benefits at the project level. * Analyze data and identify the gaps in existing solutions, and propose innovative science solutions. * Contribute to research papers that are published at peer-reviewed internal and/or external venues, and contribute to the wider scientific community. * Working with teams worldwide on global projects.
* Invent or adapt new scientific approaches, models or algorithms inspired and driven by customers’ needs and benefits at the project level. * Analyze data and identify the gaps in existing solutions, and propose innovative science solutions. * Contribute to research papers that are published at peer-reviewed internal and/or external venues, and contribute to the wider scientific community. * Working with teams worldwide on global projects.
As a Software Development Engineer, you will be responsible for designing, developing, testing, and deploying large-scale data mining solutions, distributed machine learning systems, and/or modern client experiences across webpages, mobile applications, and other shopping mediums. You will collaborate closely with teams of software engineers, applied machine learning scientists, product managers, user interface designers, and others in order to influence our overall strategy, and define the team’s roadmap. You will also drive the system architecture, spearhead best practices, and develop junior engineers. A successful candidate will have an established background in engineering large scale software systems, a strong technical ability, great communication skills, and a motivation to achieve results in a fast-paced environment.
• Build benchmarks, evaluation datasets, metrics, and methods to assess and improve the performance and effectiveness of language models and prompts and drive iterative enhancements. • Deliver high-impact analyses that generate actionable insights to steer product and business decisions and improve user satisfaction. • Collaborate closely with engineering, research, product, and other teams to ensure AI-driven experiences meet quality and user experience standards. • Analyze latest AI innovations and explore opportunities to apply cutting-edge techniques for building scalable, high-impact solutions that enhance product capabilities and deliver exceptional user experiences.
职位：Applied scientist 应用科学家实习生（博士生） 毕业时间：不限，实习期间需保持在校生身份 · 入职日期：2025年Q3 · 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。