Social

Search results

18,541 results found
  • Alexa APIs for Java
    Jonathan Breedlove, James Siri, Nikhil Yogendra Murali, Olivia Sung, Mario Doiron
    2018
    The Alexa APIs for Java consists of Java POJOS that represent the request and response JSON of Alexa services. These models act as a core dependency for the Alexa Skills Kit Java SDK These model classes are auto-generated using the JSON schemas in the developer documentation.
    Conversational AI
  • FEVER: Fact Extraction and VERification
    James Thorne, Andreas Vlachos, Christos Christodoulopoulos, Arpit Mittal
    2018
    In this paper we introduce a new publicly available dataset for verification against textual sources, FEVER: Fact Extraction and VERification. It consists of 185,445 claims generated by altering sentences extracted from Wikipedia and subsequently verified without knowledge of the sentence they were derived from. The claims are classified as SUPPORTED, REFUTED or NOTENOUGHINFO by annotators achieving 0.6841
    Conversational AI
  • Alexa APIs for Python
    Nikhil Yogendra Murali, Shreyas Govinda Raju, Jacob Peddicord, Mario Doiron, Kaiming Tao
    2018
    The Alexa APIs for Python consists of python classes that represent the request and response JSON of Alexa services. These models act as a core dependency for the Alexa Skills Kit Python SDK. These model classes are auto-generated using the JSON schemas in the developer documentation.
    Conversational AI
  • Handwritten text recognition (OCR) with MXNet Gluon
    Thomas Delteil, Jonathan Chung
    2018
    This repository lets you train neural networks models for performing end-to-end full-page handwriting recognition using the Apache MXNet deep learning frameworks on the IAM Dataset.
    Cloud and systems
  • Firectl
    Noah Meyerhans, Samuel Karp, Austin Vazquez, Xibin Gao, Kern Walster, Arun Gupta, Michael Coulter, Stanislas Lange, Bobby Gammill , Yasin Turan, Volker Simonis, Henry Wang, Nikita Mochalov, Luminita Voicu, Kazuyoshi Kato, Cody Roseborough, Boris Popovschi, Antonio Ojea
    2018
    Firectl is a basic command-line tool that lets you run arbitrary Firecracker MicroVMs via the command line. This lets you run a fully functional Firecracker MicroVM, including console access, read/write access to filesystems, and network connectivity.
    Cloud and systems
  • A basic Go interface to the Firecracker API
    Kazuyoshi Kato, Xibin Gao, Samuel Karp, Noah Meyerhans, Erik Sipsma, Austin Vazquez, Maksym Pavlenko, Jerome Gravel-Niquet, David Son
    2018
    This package is a Go library to interact with the Firecracker API. It is designed as an abstraction of the OpenAPI-generated client that allows for convenient manipulation of Firecracker VM from Go programs. There are some Firecracker features that are not yet supported by the SDK. These are tracked as GitHub issues with the firecracker-feature label. Contributions to address missing features are welcomed
    Cloud and systems
  • Firecracker presentation website
    Radu Weiss, Raj Bennin, Takahiro Itazuri, Will Stewart, Edouard Bonlieu, Nikita Sobolev, Alexandra Iordache, Christopher Mayfield, Romaric Philogène, Alberto P. Martí
    2018
    This is the presentation website for Firecracker. We take pull request for content and FAQ improvements, as well as additons to the list of Firecracker integrations. When contributing to HTML pages in this repo, please format the entire file with the latest stable Prettier release, using the settings below for the HTML parser.
    Cloud and systems
  • Visual Search with Amazon SageMaker and AWS DeepLens
    Brent Rabowsky
    2018
    This repository provides resources for implementing a visual search engine. Visual search is the central component of an interface where instead of asking for something by voice or text, you show what you are looking for. When shown a real world, physical item, an AWS DeepLens device generates a feature vector representing that item. The feature vector generated by the AWS DeepLens device is sent to the
    Search and information retrieval
  • SPEKE reference server
    Jim Thario, Vinay Calastry, Jacob Peddicord, Yufei Gao, Jared Stewart, Shinya Kawaguchi, Ritchie Robershaw, Raees Iqbal, Tomohiro Matsuzawa
    2018
    Secure Packager and Encoder Key Exchange (SPEKE) is part of the AWS Elemental content encryption protection strategy for media services customers. SPEKE defines the standard for communication between AWS Media Services and digital rights management (DRM) system key servers. SPEKE is used to supply keys to encrypt video on demand (VOD) content through AWS Elemental MediaConvert and for live content through
    Cloud and systems
  • FEVER (2018)
    James Thorne, Andreas Vlachos, Christos Christodoulopoulos, Arpit Mittal
    2018
    FEVER (Fact Extraction and VERification) consists of 185,445 claims generated by altering sentences extracted from Wikipedia and subsequently verified without knowledge of the sentence they were derived from. The claims are classified as Supported, Refuted or NotEnoughInfo. For the first two classes, the annotators also recorded the sentence(s) forming the necessary evidence for their judgment.
    Conversational AI
  • Machine translation accelerates how Alexa learns new languages
    Penny Karanasou
    May 29, 2018
    Amazon Science Promo Image (Squid)
    As Alexa-enabled devices continue to expand into new countries, we propose an approach for quickly bootstrapping machine-learning models in new languages, with the aim of more efficiently bringing Alexa to new customers around the world.
    Conversational AI
  • Amazon scientists use transfer learning to accelerate development of new Alexa capabilities
    Angeliki Metallinou
    May 24, 2018
    Stacked multitask bi-LSTM model architecture
    Amazon scientists are continuously expanding Alexa’s natural-language-understanding (NLU) capabilities to make Alexa smarter, more useful, and more engaging.
    Conversational AI
  • Amazon Scientist Outlines Multilayer System For Smart Speaker Echo Cancellation And Voice Enhancement
    Jun Yang
    May 11, 2018
    The Proposed Multilayer Process
    Smart speakers, such as the Amazon Echo family of products, are growing in popularity among consumer and business audiences. In order to improve the automatic speech recognition (ASR) and full-duplex voice communication (FDVC) performance of these smart speakers, acoustical echo cancellation (AEC) and noise reduction systems are required. These systems reduce the noises and echoes that can impact operation, such as an Echo device accurately hearing the wake word “Alexa.”
    Conversational AI
  • Amazon and University of Sheffield researchers make large-scale fact extraction and verification dataset publicly available
    Arpit Mittal
    May 4, 2018
    Amazon and University of Sheffield researchers are addressing the fact verification challenge
    In recent years, the amount of textual information produced daily has increased exponentially. This information explosion has been accelerated by the ease with which data can be shared across the web. Most of the textual information is generated as free-form text, and only a small fraction is available in structured format (Wikidata, Freebase etc.) that can be processed and analyzed directly by machines.
    Search and information retrieval
  • Making Alexa more friction-free
    Ruhi Sarikaya
    April 25, 2018
    Amazon Echo Alexa.jpg
    This morning, I am delivering a keynote talk at the World Wide Web Conference in Lyon, France, with the title, Conversational AI for Interacting with the Digital and Physical World.
    Conversational AI
  • Alexa scientists present two new techniques that improve wake word performance
    Minhua Wu
    April 12, 2018
    Time Delayed Bottleneck Highway Networks
    The Amazon Echo is a hands-free smart home speaker you control with your voice. The first important step in enabling a delightful customer experience with an Echo or other Alexa-enabled device is wake word detection, so accurate detection of “Alexa” or substitute wake words is critical. It is challenging to build a wake word system with low error rates when there are limited computation resources on the device and it's in the presence of background noise such as speech or music.
    Conversational AI
  • Alexa scientists address challenges of end-pointing
    Roland Maas
    April 10, 2018
    Roland_Maas_EP2_._CB498703590_.png
    Just as Alexa can wake up without the need to press a button, she also automatically detects when a user finishes her query and expects a response. This task is often called “end-of-utterance detection,” “end-of-query detection,” “end-of-turn detection,” or simply “end-pointing.”
    Conversational AI
  • Alquist (2018)
    Czech Technical University in Prague
    ctu-alquist-team-650px.jpg
    We are the team Alquist from CTU, Prague, Czech Republic.
  • SlugBot (2018)
    University of California, Santa Cruz
    ucsc-slugbot-team-650x.jpg
    Team SlugBot is proud to represent the Natural Language and Dialogue Systems laboratory at UC Santa Cruz.
  • Alana
    Heriot-Watt University
    hw-alana-team-650px.jpg
    Our international team of 8 PhD students and faculty advisors has a wide range of experience from both academic and industrial research.
1
...
920
921
922
...
928

Work with us

See more jobs See more jobs
Applied Scientist, Prime Air Navigation
US, WA, Seattle
Here at Amazon, we embrace our differences. We are committed to furthering our culture of diversity and inclusion of our teams within the organization. How do you get items to customers quickly, cost-effectively, and—most importantly—safely, in less than an hour? And how do you do it in a way that can scale? Our teams of hundreds of scientists, engineers, aerospace professionals, and futurists have been working hard to do just that! We are delivering to customers, and are excited for what’s to come. Check out more information about Prime Air on the About Amazon blog (https://www.aboutamazon.com/news/transportation/amazon-prime-air-delivery-drone-reveal-photos). If you are seeking an iterative environment where you can drive innovation, apply state-of-the-art technologies to solve real world delivery challenges, and provide benefits to customers, Prime Air is the place for you. Come work on the Amazon Prime Air Team! We are seeking a highly skilled Navigation Scientist to help develop advanced algorithms and software for our Prime Air delivery drone program. In this role, you will conduct comprehensive navigation analysis to support cross-functional decision-making, define system architecture and requirements, contribute to the development of flight algorithms, and actively identify innovative technological opportunities that will drive significant enhancements to meet our customers' evolving demands. Export Control License: This position may require a deemed export control license for compliance with applicable laws and regulations. Placement is contingent on Amazon’s ability to apply for and obtain an export control license on your behalf.
Applied Scientist, Sponsored Products
US, NY, New York
About Sponsored Products and Brands The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. About our team The Targeting and Recommendations team within Sponsored Products and Brands empowers advertisers with intelligent targeting controls and one-click campaign recommendations that automatically populate optimal settings based on ASIN data. This comprehensive suite provides advanced targeting capabilities through AI-generated keyword and ASIN suggestions, sophisticated targeting controls including Negative Targeting, Manual Targeting with Product Attribute Targeting (PAT) and Keyword Targeting (KWT), and Automated Targeting (ATv2). Our vision is to build a revolutionary, highly personalized and context-aware agentic advertiser guidance system that seamlessly integrates Large Language Models (LLMs) with sophisticated tooling, operating across both conversational and traditional ad console experiences while scaling from natural language queries to proactive, intelligent guidance delivery based on deep advertiser understanding, ultimately enhancing both targeting precision and one-click campaign optimization. Through strategic partnerships across Ad Console, Sales, and Marketing teams, we identify high-impact opportunities spanning from strategic product guidance to granular keyword optimization and deliver them through personalized, scalable experiences grounded in state-of-the-art agent architectures, reasoning frameworks, sophisticated tool integration, and model customization approaches including tuning, MCP, and preference optimization. This presents an exceptional opportunity to shape the future of e-commerce advertising through advanced AI technology at unprecedented scale, creating solutions that directly impact millions of advertisers. Key job responsibilities * Design and build targeting and 1 click recommendation agents to guide advertisers in conversational and non-conversational experience. * Design and implement advanced model and agent optimization techniques, including supervised fine-tuning, instruction tuning and preference optimization (e.g., DPO/IPO). * Collaborate with peers across engineering and product to bring scientific innovations into production. * Stay current with the latest research in LLMs, RL, and agent-based AI, and translate findings into practical applications. * Develop agentic architectures that integrate planning, tool use, and long-horizon reasoning. A day in the life As an Applied Scientist on our team, your days will be immersed in collaborative problem-solving and strategic innovation. You'll partner closely with expert applied scientists, software engineers, and product managers to tackle complex advertising challenges through creative, data-driven solutions. Your work will center on developing sophisticated machine learning and AI models, leveraging state-of-the-art techniques in natural language processing, recommendation systems, and agentic AI frameworks. From designing novel targeting algorithms to building personalized guidance systems, you'll contribute to breakthrough innovations
Applied Scientist, Trust CX Innovations (TCI)
IN, KA, Bengaluru
Alexa+ is Amazon’s next-generation, AI-powered assistant. Building on the original Alexa, it uses generative AI to deliver a more conversational, personalized, and effective experience. The Trust CX Innovations team is looking for an Applied Scientist with strong background in Generative AI space to build solutions that help in upholding customer trust for Alexa+. As an Applied Scientist in Trust CX innovations, you will be at the forefront of developing innovative solutions to critical challenges in AI trust and privacy. You'll lead research in trust-preserving machine learning techniques. We are working on revolutionizing the way Amazonians work and collaborate. You will help us achieve new heights of productivity through the power of advanced generative AI technologies. Key job responsibilities - Lead research initiatives in generative AI, focusing on LLMs, multimodal models, and frontier AI capabilities - Develop innovative approaches for model optimization, including prompt engineering, few-shot learning, and efficient fine-tuning - Pioneer new methods for AI safety, alignment, and responsible AI development - Design and execute sophisticated experiments to evaluate model performance and behavior - Lead the development of production-ready AI solutions that scale efficiently - Collaborate with product teams to translate research innovations into practical applications - Guide engineering teams in implementing AI models and systems at scale - Author technical papers for top-tier conferences - File patents for novel AI technologies and applications A day in the life You will be working with a group of talented scientists on researching algorithm and running experiments to test scientific proposal/solutions to improve our trust-preserving experiences. This will involve collaboration with partner teams including engineering, PMs, data annotators, and other scientists to discuss data quality, policy, and model development. You work closely with partner teams across Alexa to deliver platform features that require cross-team leadership. About the team Who We Are: Trust CX Innovations is a strategic innovation team within Amazon Devices & Services that focuses on advancing AI technology while prioritizing customer trust and experience. Our team operates at the intersection of artificial intelligence, privacy engineering and customer-centric design. Our Mission: To pioneer trustworthy AI innovations that delight customers while setting new standards for privacy and responsible technology development. We aim to transform how Amazon builds AI products by creating solutions that balance innovation with customer trust.
Applied Scientist, Trust CX Innovations (TCI)
IN, KA, Bengaluru
Alexa+ is Amazon’s next-generation, AI-powered assistant. Building on the original Alexa, it uses generative AI to deliver a more conversational, personalized, and effective experience. The Trust CX Innovations team is looking for an Applied Scientist with strong background in Generative AI space to build solutions that help in upholding customer trust for Alexa+. As an Applied Scientist in Trust CX innovations, you will be at the forefront of developing innovative solutions to critical challenges in AI trust and privacy. You'll lead research in trust-preserving machine learning techniques. We are working on revolutionizing the way Amazonians work and collaborate. You will help us achieve new heights of productivity through the power of advanced generative AI technologies. Key job responsibilities - Lead research initiatives in generative AI, focusing on LLMs, multimodal models, and frontier AI capabilities - Develop innovative approaches for model optimization, including prompt engineering, few-shot learning, and efficient fine-tuning - Pioneer new methods for AI safety, alignment, and responsible AI development - Design and execute sophisticated experiments to evaluate model performance and behavior - Lead the development of production-ready AI solutions that scale efficiently - Collaborate with product teams to translate research innovations into practical applications - Guide engineering teams in implementing AI models and systems at scale - Author technical papers for top-tier conferences - File patents for novel AI technologies and applications A day in the life You will be working with a group of talented scientists on researching algorithm and running experiments to test scientific proposal/solutions to improve our trust-preserving experiences. This will involve collaboration with partner teams including engineering, PMs, data annotators, and other scientists to discuss data quality, policy, and model development. You work closely with partner teams across Alexa to deliver platform features that require cross-team leadership. About the team Who We Are: Trust CX Innovations is a strategic innovation team within Amazon Devices & Services that focuses on advancing AI technology while prioritizing customer trust and experience. Our team operates at the intersection of artificial intelligence, privacy engineering and customer-centric design. Our Mission: To pioneer trustworthy AI innovations that delight customers while setting new standards for privacy and responsible technology development. We aim to transform how Amazon builds AI products by creating solutions that balance innovation with customer trust.
Member of Technical Staff Intern (2026), Artificial General Intelligence (AGI)
US, CA, San Francisco
Amazon has launched a new research lab in San Francisco to develop foundational capabilities for useful AI agents. We’re enabling practical AI to make our customers more productive, empowered, and fulfilled. In particular, our work combines large language models (LLMs) with reinforcement learning (RL) to solve reasoning, planning, and world modeling in both virtual and physical environments. Our research builds on that of Amazon’s broader AGI organization, which recently introduced Amazon Nova, a new generation of state-of-the-art foundation models (FMs). Our lab is a small, talent-dense team with the resources and scale of Amazon. Each team in the lab has the autonomy to move fast and the long-term commitment to pursue high-risk, high-payoff research. We’re entering an exciting new era where agents can redefine what AI makes possible. We’d love for you to join our lab and build it from the ground up! Key job responsibilities You will contribute directly to AI agent development in a research engineering role: running experiments, building tools to accelerate scientific workflows, and scaling up AI systems. Key responsibilities include: * Design, maintain, and enhance tools and workflows that support cutting-edge research * Adapt quickly to evolving research priorities and team needs * Stay informed on the latest advancements in large language models and related research * Collaborate closely with researchers to develop new techniques and tools around emerging agent capabilities * Drive project execution, including scoping, prioritization, timeline management, and stakeholder communication * Thrive in a fast-paced, iterative environment, delivering high-quality software on tight schedules * Apply strong software engineering fundamentals to produce clean, reliable, and maintainable code About the team The Amazon AGI SF Lab is focused on developing new foundational capabilities for enabling useful AI agents that can take actions in the digital and physical worlds. In other words, we’re enabling practical AI that can actually do things for us and make our customers more productive, empowered, and fulfilled. The lab is designed to empower AI researchers and engineers to make major breakthroughs with speed and focus toward this goal. Our philosophy combines the agility of a startup with the resources of Amazon. By keeping the team lean, we’re able to maximize the amount of compute per person. Each team in the lab has the autonomy to move fast and the long-term commitment to pursue high-risk, high-payoff research.
Applied Scientist, Prime Video - Generative AI
US, CA, Sunnyvale
Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video subscriptions such as Apple TV+, HBO Max, Peacock, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video team member, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! Key job responsibilities As an Applied Scientist at Prime Video, you will have end-to-end ownership of the product, related research and experimentation, applying advanced machine learning techniques in computer vision (CV), Generative AI, multimedia understanding and so on. You’ll work on diverse projects that enhance Prime Video’s content localization, image/video understanding, and content personalization, driving impactful innovations for our global audience. Other responsibilities include: - Research and develop generative models for controllable synthesis across images, video, vector graphics, and multimedia - Innovate in advanced diffusion and flow-based methods (e.g., inverse flow matching, parameter efficient training, guided sampling, test-time adaptation) to improve efficiency, controllability, and scalability. - Advance visual grounding, depth and 3D estimation, segmentation, and matting for integration into pre-visualization, compositing, VFX, and post-production pipelines. - Design multimodal GenAI workflows including visual-language model tooling, structured prompt orchestration, agentic pipelines. A day in the life Prime Video is pioneering the use of Generative AI to empower the next generation of creatives. Our mission is to make world-class media creation accessible, scalable, and efficient. We are seeking an Applied Scientist to advance the state of the art in Generative AI and to deliver these innovations as production-ready systems at Amazon scale. Your work will give creators unprecedented freedom and control while driving new efficiencies across Prime Video’s global content and marketing pipelines. This is a newly formed team within Prime Video Science!
Applied Scientist, Prime Video - Generative AI
US, CA, Sunnyvale
Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video subscriptions such as Apple TV+, HBO Max, Peacock, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video team member, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! Key job responsibilities As an Applied Scientist at Prime Video, you will have end-to-end ownership of the product, related research and experimentation, applying advanced machine learning techniques in computer vision (CV), Generative AI, multimedia understanding and so on. You’ll work on diverse projects that enhance Prime Video’s content localization, image/video understanding, and content personalization, driving impactful innovations for our global audience. Other responsibilities include: - Research and develop generative models for controllable synthesis across images, video, vector graphics, and multimedia - Innovate in advanced diffusion and flow-based methods (e.g., inverse flow matching, parameter efficient training, guided sampling, test-time adaptation) to improve efficiency, controllability, and scalability. - Advance visual grounding, depth and 3D estimation, segmentation, and matting for integration into pre-visualization, compositing, VFX, and post-production pipelines. - Design multimodal GenAI workflows including visual-language model tooling, structured prompt orchestration, agentic pipelines. A day in the life Prime Video is pioneering the use of Generative AI to empower the next generation of creatives. Our mission is to make world-class media creation accessible, scalable, and efficient. We are seeking an Applied Scientist to advance the state of the art in Generative AI and to deliver these innovations as production-ready systems at Amazon scale. Your work will give creators unprecedented freedom and control while driving new efficiencies across Prime Video’s global content and marketing pipelines. This is a newly formed team within Prime Video Science!
Applied Scientist, Sponsored Products
US, WA, Seattle
The Sponsored Products and Brands (SPB) team at Amazon Ads is re-imagining the advertising landscape through the latest generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. Key job responsibilities This role will be pivotal in redesigning how ads contribute to a personalized, relevant, and inspirational shopping experience, with the customer value proposition at the forefront. Key responsibilities include, but are not limited to: - Contribute to the design and development of GenAI, deep learning, multi-objective optimization and/or reinforcement learning empowered solutions to transform ad retrieval, auctions, whole-page relevance, and/or bespoke shopping experiences. - Collaborate cross-functionally with other scientists, engineers, and product managers to bring scalable, production-ready science solutions to life. - Stay abreast of industry trends in GenAI, LLMs, and related disciplines, bringing fresh and innovative concepts, ideas, and prototypes to the organization. - Contribute to the enhancement of team’s scientific and technical rigor by identifying and implementing best-in-class algorithms, methodologies, and infrastructure that enable rapid experimentation and scaling. - Mentor and grow junior scientists and engineers, cultivating a high-performing, collaborative, and intellectually curious team. A day in the life As an Applied Scientist on the Sponsored Products and Brands Off-Search team, you will contribute to the development in Generative AI (GenAI) and Large Language Models (LLMs) to revolutionize our advertising flow, backend optimization, and frontend shopping experiences. This is a rare opportunity to redefine how ads are retrieved, allocated, and/or experienced—elevating them into personalized, contextually aware, and inspiring components of the customer journey. You will have the opportunity to fundamentally transform areas such as ad retrieval, ad allocation, whole-page relevance, and differentiated recommendations through the lens of GenAI. By building novel generative models grounded in both Amazon’s rich data and the world’s collective knowledge, your work will shape how customers engage with ads, discover products, and make purchasing decisions. If you are passionate about applying frontier AI to real-world problems with massive scale and impact, this is your opportunity to define the next chapter of advertising science. About the team The Off-Search team within Sponsored Products and Brands (SPB) is focused on building delightful ad experiences across various surfaces beyond Search on Amazon—such as product detail pages, the homepage, and store-in-store pages—to drive monetization. Our vision is to deliver highly personalized, context-aware advertising that adapts to individual shopper preferences, scales across diverse page types, remains relevant to seasonal and event-driven moments, and integrates seamlessly with organic recommendations such as new arrivals, basket-building content, and fast-delivery options. To execute this vision, we work in close partnership with Amazon Stores stakeholders to lead the expansion and growth of advertising across Amazon-owned and -operated pages beyond Search. We operate full stack—from backend ads-retail edge services, ads retrieval, and ad auctions to shopper-facing experiences—all designed to deliver meaningful value. Curious about our advertising solutions? Discover more about Sponsored Products and Sponsored Brands to see how we’re helping businesses grow on Amazon.com and beyond!
Applied Scientist, Artificial General Intelligence - Data Services
US, MA, Boston
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 an Applied 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 Applied 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
Member of Technical Staff, Artificial General Intelligence
US, CA, San Francisco
The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Member of Technical Staff with a strong deep learning background, to build industry-leading Generative Artificial Intelligence (GenAI) technology with Large Language Models (LLMs) and multimodal systems. Key job responsibilities As a Member of Technical Staff with the AGI team, you will lead the development of algorithms and modeling techniques, to advance the state of the art with LLMs. You will lead the foundational model development in an applied research role, including model training, dataset design, and pre- and post-training optimization. Your work will directly impact our customers in the form of products and services that make use of GenAI technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in LLMs. About the team The AGI team has a mission to push the envelope in GenAI with LLMs and multimodal systems, in order to provide the best-possible experience for our customers.
See more jobs
View from space of a connected network around planet Earth representing the Internet of Things.
Get more from Amazon Science
Subscribe to our monthly newsletter

Amazon.com | Conditions of Use | Privacy | © 1996-2025 Amazon.com, Inc. or its affiliates

Social