Five ways Amazon is preparing for the energy demands of the future

From investing in new carbon-free energy projects to advocating for grid modernization and collaborating with key stakeholders around the world, Amazon is working toward a cleaner energy future.

As our society relies on technology more than ever, from consumer electronics to large-scale infrastructure in both public and private sectors, global energy demands are continuing to grow. At Amazon, we’re working to meet the future energy demands of our customers and our business while remaining committed to our Climate Pledge to become net-zero carbon by 2040. We know the path forward is changing, and our work to decarbonize our operations won’t be linear, so we’re constantly experimenting, learning, and evolving.

Here are five ways Amazon is innovating to ensure our energy needs are met with sustainability and efficiency in mind:

  1. Matching 100% of the electricity consumed by our operations with renewable energy

    Amazon achieved our goal to match all of the electricity consumed by our operations with 100% renewable energy. We originally pledged to reach this goal in 2030, and achieved it seven years early in 2023. In order to achieve this ambitious goal, we’ve invested in more than 600+ solar and wind projects around the world, representing more than 34 gigawatts (GW) of new energy capacity once operational. Once all of these projects become operational, they’re expected to produce enough energy to power more than 8.3 million average U.S. homes each year. We’ve also been the world’s largest corporate purchaser of renewable energy every year since 2020.

    Looking ahead, increasing energy demands—including those driven by generative AI—will require us to add more sources of carbon-free energy, including nuclear, offshore wind, green hydrogen, and more. In addition, Amazon’s $2 billion Climate Pledge Fund is investing in the next generation of emerging low-carbon energy technologies, including green ammonia, renewable transportation fuels, portable battery storage, and other innovations that can help power the future energy needs of our business and the transition to a lower-carbon economy.

  2. Advocating for grid modernization

    In most cases, when we invest in new carbon-free energy projects like wind and solar farms, that energy goes into the public power grids in those areas—meaning those communities are also benefitting. We want electric grids where we operate to be net-zero carbon for everyone. But right now, grids across the country are limited in how much energy they can accept. While we’re working with utilities and energy companies to fast-forward new solar, wind, and other carbon-free energy projects to meet rising demand, the grid also needs to be modernized so it can handle that demand. More than 70% of the U.S. grid is 25 years old or older, and across the United States, there are currently more than 2.6 million megawatts (MW) of renewable energy and storage projects waiting to come online—nearly double the current amount of U.S. generation capacity, or enough carbon-free energy to power 63.3 million US homes. To help address this, Amazon teams are engaging with energy regulators and other officials at the federal and state levels to help support grid modernization, remove permitting obstacles, and deploy grid-enhancing technologies.

    We’re also working with grid operators and utilities to help ensure grid modernization is funded in the markets where we do business. Like all ratepayers, Amazon pays transmission costs for the energy we use, and those rates are established by utility regulators. Those costs help cover infrastructure upgrades and other grid modernization needs required to support the needs of all energy users.

  3. Deploying renewable energy where it’s needed most

    To have the biggest impact, we focus most of our investments on the grids where our operations are concentrated, as well as regions where the existing grid is most carbon intensive. For example, we have a large AWS presence in Oregon, so we’re working with utility company Umatilla Electric to procure new sources of renewable energy, such as electricity purchased from a local wind farm, to help increase the amount of renewable energy to the local grid.

    We also make a point to invest in renewables projects in places that otherwise rely heavily on fossil fuels like coal, oil, and natural gas to power their grids, such as India, Poland, and the southeastern U.S. To support this effort, Amazon cofounded the Emissions First Partnership, a coalition of companies committed to modernizing the greenhouse gas accounting standards for the power sector, which will encourage companies to invest in renewable and carbon-free energy in more carbon-intensive grids. Both of these approaches help reduce energy-related emissions and match the electricity used by our operations with renewable energy, a win-win for people and the planet.

  4. Taking steps to run our data centers more efficiently

    We’re constantly reevaluating how our data centers operate and determining ways to help them run on less energy and be more efficient. And as the world scales our use of AI, it's important to also minimize its environmental footprint. A new study by Accenture shows that an effective way to do that is by moving IT workloads from on-premises infrastructure to AWS data centers around the globe. The research estimates AWS’s infrastructure is up to 4.1 times more efficient than on-premises, and when workloads are optimized on AWS, the associated carbon footprint can be reduced by up to 99%. This type of impact is possible by AWS optimizing our data center design, investing in purpose-built chips, and innovating with new cooling technologies. For example, we’ve taken steps to design our data centers to use natural air flow to lower server temperatures, which can heat up while in use. This allows us to use less air conditioning when possible. We’ve also designed our AWS machine learning chips, which power millions of workloads daily, to be more energy efficient. For example, AWS’s Graviton processor delivers high performance with high levels of energy efficiency. Graviton4 provides up to 30% better computing performance, 50% more cores, and 75% more memory bandwidth than current-generation Graviton3 processors, delivering the best price performance and energy efficiency for a broad range of workloads running on Amazon EC2. We’re also keeping technologies in use longer by increasing the lifespan of our servers from five to six years.

  5. Incorporating sustainability practices into the design and construction of our buildings

    We’re working to design our corporate buildings in ways that support the transition to net-zero carbon, including by constructing new buildings using low-carbon concrete and electrified HVAC systems. One of our newest Same-Day fulfillment centers in California is set to make history as the world’s first fulfillment facility to achieve Zero Carbon Certification status. The electricity used by our HQ2 headquarters is matched with 100% renewable energy from a local solar farm and has achieved the highest level of LEED green building certification. We’ve also installed energy-efficient lighting, low-flow water fixtures, and implemented recycling and composting in our corporate offices. In Europe and in the U.S., our data centers are transitioning to renewable diesel in our generators, which can result in as much as 90% fewer greenhouse gas emissions over the fuel’s life cycle compared to diesel.

    Amazon is continuing to work toward transitioning our business and our society to a cleaner energy future.

Research areas

Related content

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
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.
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!
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!
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!
US, WA, Seattle
About Sponsored Products and Brands: The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry leading 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 Sponsored Brands Impressions-based Offerings team is responsible for evolving the value proposition of Sponsored Brands to drive brand advertising in retail media at scale, helping brands get discovered, acquire new customers and sustainably grow customer lifetime value. We build end-to-end solutions that enable brands to drive discovery, visibility and share of voice. This includes building advertiser controls, shopper experiences, monetization strategies and optimization features. We succeed when (1) shoppers discover, engage and build affinity with brands and (2) brands can grow their business at scale with our advertising products. About This Role: As an Applied Scientist on our team, you will: * Develop AI solutions for Sponsored Brands advertiser and shopper experiences. Build monetization and optimization systems that leverage generative models to value and improve campaign performance. * Define a long-term science vision and roadmap for our Sponsored Brands advertising business, driven from our customers' needs, translating that direction into specific plans for applied scientists and engineering teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. * Design and conduct A/B experiments to evaluate proposed solutions based on in-depth data analyses. * Effectively communicate technical and non-technical ideas with teammates and stakeholders; * Stay up-to-date with advancements and the latest modeling techniques in the field. * 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. #GenAI
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
US, WA, Seattle
About Sponsored Products and Brands: The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry leading 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 Sponsored Brands Impressions-based Offerings team is responsible for evolving the value proposition of Sponsored Brands to drive brand advertising in retail media at scale, helping brands get discovered, acquire new customers and sustainably grow customer lifetime value. We build end-to-end solutions that enable brands to drive discovery, visibility and share of voice. This includes building advertiser controls, shopper experiences, monetization strategies and optimization features. We succeed when (1) shoppers discover, engage and build affinity with brands and (2) brands can grow their business at scale with our advertising products. About This Role: As an Applied Scientist on our team, you will: * Develop AI solutions for Sponsored Brands advertiser and shopper experiences. Build monetization and optimization systems that leverage generative models to value and improve campaign performance. * Define a long-term science vision and roadmap for our Sponsored Brands advertising business, driven from our customers' needs, translating that direction into specific plans for applied scientists and engineering teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. * Design and conduct A/B experiments to evaluate proposed solutions based on in-depth data analyses. * Effectively communicate technical and non-technical ideas with teammates and stakeholders; * Stay up-to-date with advancements and the latest modeling techniques in the field. * 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. #GenAI
US, WA, Seattle
About Sponsored Products and Brands The Sponsored Products and Brands (SPB) team at Amazon Ads is re-imagining the advertising landscape through state-of-art 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.
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