Earth image smaller
In September 2019, Amazon and Global Optimism co-founded The Climate Pledge, a commitment to reach net-zero carbon emissions by 2040 – 10 years ahead of the Paris Agreement.
Credit: Abrill/Getty Images/iStockphoto

Amazon's scientific approach to meeting – and measuring – its climate goals

How Amazon is aligning its decarbonization goals with the best available science.

Urgent actions — major investments and innovations — are needed across virtually every business sector to respond to climate change. In September 2019, Amazon and Global Optimism co-founded The Climate Pledge, a commitment to reach net-zero carbon emissions by 2040 – 10 years ahead of the Paris Agreement.

Reaching this goal means measuring emissions, setting aggressive reduction targets based in science, and investing in transformative decarbonization solutions. Amazon joined the Science Based Targets Initiative (SBTi) to align our decarbonization goals with the best available science, and measures and reports carbon emissions following the GHG Protocol and an independent verification process.

Dara O'Rourke
Dara O'Rourke
Credit: UCal Berkeley

The most aggregate metric used to report emissions is total — or absolute — emissions. For a complex company like Amazon, even this “absolute” metric is complicated to calculate. And the aggregate, company-wide carbon number does not tell the full story of the company’s performance, or provide the insights needed by businesses and individual teams to drive decarbonization initiatives. To help gain deeper insights, Amazon also tracks carbon intensity per dollar of gross merchandise sales (GMS), and more detailed metrics for individual business units.

High-growth companies such as Amazon need to measure their carbon intensity to track, in detail, whether they are making the right investments needed to decarbonize a business, and to decouple their business growth from greenhouse gas emissions. As companies invest in new products and services, the metric should not be whether the company’s footprint simply shrank, but whether and how fast it is lowering its carbon intensity and decoupling business operations from carbon emissions.

A recent whitepaper by Miguel Jaller, associate professor of Civil and Environmental Engineering at UC Davis, and Scott Matthews, professor of Civil and Environmental Engineering at Carnegie Mellon University, provides important insights on the importance of carbon intensity metrics, particularly for high-growth companies:

For high growth entities, tracking carbon intensity of overall activity, or for key components, may be a critical part of analyzing progress towards meeting reduction goals. During periods of fast growth and innovation-driven market disruption, carbon intensity improvements may be expected to catch up to or outpace economic growth, and result in net total emissions reductions. In most cases, fast growing companies are not tied to legacy systems and infrastructure. This offers the opportunity to focus investments in new processes, assets, systems, and infrastructure that can achieve substantial intensity reductions at lower costs, with minimal disruptions to day-to-day operations. These new technologies and business models help achieve direct and internal improvements, and may provide system-level benefits as they allow substituting entire processes (e.g., traditional shopping) with more efficient ones (e.g., online shopping). They may also enable behavioral changes that further help decarbonization efforts.”

The whitepaper explains the relationship between developing complementary absolute and intensity metrics, and how together they enable the transition to more efficient processes:

“Carbon intensity-based targets can also enable innovative improvement pathways, as efforts can be spent identifying efficient processes or making the necessary changes and upgrades to existing processes to reduce their intensity. For example, replacing grid electricity with renewable electricity in a building will reduce its carbon footprint. This is a great outcome, but if the building can also be redesigned through the use of innovative technologies to increase revenue in a subsequent year, the footprint would remain unchanged, but the intensity would continue to decrease. The same is true for the use of fleet vehicles, which can be decarbonized to reduce the overall footprint, but can also have delivery routes better optimized to reduce intensity. If packaging volume can be reduced, total emissions decrease, and if more packages can fit in a vehicle, then intensity is further reduced. Making such systems more efficient can have further overall benefits to financial and carbon performance, but those efficiency gains might only be recognized with intensity-based metrics.”

As Jaller and Matthews argue, we need companies and countries to continuously lower carbon intensity per unit of economic activity. And we need better ways to evaluate investments in the low-carbon technologies and infrastructure needed today to get to net-zero carbon by 2040.

Amazon releases 2020 sustainability report

Amazon's 2020 sustainability report, released today, details the company's progress in measuring and reducing the carbon intensity of its business operations. Amazon's overall carbon intensity decreased 16% in 2020. Read the full report.

Amazon’s 2020 sustainability report shows the start of this progress towards measuring and reducing the carbon intensity of business activities, following a number of investments in large-scale decarbonization initiatives (such as electric vans). Amazon’s overall carbon intensity decreased 16%, from 122.8 grams of CO2 per dollar of GMS in 2019 to 102.7 grams of CO2 per dollar of GMS in 2020. This year-over-year carbon intensity comparison reflects early progress to decarbonize operations as the company continues to grow and invest in innovations.

It is still early days in our sustainability journey. And there are still a number of technical challenges for which no single company has an answer. Amazon will continue to look to academics like Jaller and Matthews for insights into these technologies and measurement challenges.

As Amazon continues to decarbonize operations and accelerate toward The Climate Pledge commitment, it will be critical to continue to engage the latest science to create actionable metrics for target setting, investment decisions, and accountability on bending carbon curves.

If you would like to learn more about Amazon’s carbon methodology, please visit our Sustainability reporting website.

Research areas

Related content

  • A new approach to reducing carbon emissions reveals previously hidden emission “hotspots” within value chains, helping organizations make more detailed and dynamic decisions about their future carbon footprints.
  • Staff writer
    December 29, 2025
    From foundation model safety frameworks and formal verification at cloud scale to advanced robotics and multimodal AI reasoning, these are the most viewed publications from Amazon scientists and collaborators in 2025.
  • Staff writer
    December 29, 2025
    From quantum computing breakthroughs and foundation models for robotics to the evolution of Amazon Aurora and advances in agentic AI, these are the posts that captured readers' attention in 2025.
US, NY, New York
The Sponsored Products and Brands (SPB) team at Amazon Ads is re-imagining the advertising landscape through state-of-the-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. 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! 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, WA, Seattle
MULTIPLE POSITIONS AVAILABLE Employer: AMAZON.COM SERVICES LLC Offered Position: Data Scientist III Job Location: Seattle, Washington Job Number: AMZ9674365 Position Responsibilities: Own the data science elements of various products to help with data-based decision making, product performance optimization, and product performance tracking. Work directly with product managers to help drive the design of the product. Work with Technical Product Managers to help drive the build planning. Translate business problems and products into data requirements and metrics. Initiate the design, development, and implementation of scientific analysis projects or deliverables. Own the analysis, modelling, system design, and development of data science solutions for products. Write documents and make presentations that explain model/analysis results to the business. Bridge the degree of uncertainty in both problem definition and data scientific solution approaches. Build consensus on data, metrics, and analysis to drive business and system strategy. Position Requirements: Master's degree or foreign equivalent degree in Statistics, Applied Mathematics, Economics, Engineering, Computer Science or a related field and two years of experience in the job offered or a related occupation. Employer will accept a Bachelor's degree or foreign equivalent degree in Statistics, Applied Mathematics, Economics, Engineering, Computer Science, or a related field and five years of progressive post-baccalaureate experience in the job offered or a related occupation as equivalent to the Master's degree and two years of experience. Must have one year of experience in the following skills: (1) building statistical models and machine learning models using large datasets from multiple resources; (2) building complex data analyses by leveraging scripting languages including Python, Java, or related scripting language; and (3) communicating with users, technical teams, and management to collect requirements, evaluate alternatives, and develop processes and tools to support the organization. Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation. 40 hours / week, 8:00am-5:00pm, Salary Range $162,752/year to $215,300/year. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, visit: https://www.aboutamazon.com/workplace/employee-benefits.#0000
US, WA, Seattle
Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the extreme. We focus on creating entirely new products and services with a goal of positively impacting the lives of our customers. No industries or subject areas are out of bounds. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have thirteen employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We are constantly learning through programs that are local, regional, and global. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. Our team highly values work-life balance, mentorship and career growth. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We care about your career growth and strive to assign projects and offer training that will challenge you to become your best.
US, CA, Sunnyvale
Amazon Devices is an inventive research and development company that designs and engineer high-profile devices like Echo, Fire Tablets, Fire TV, and other consumer devices. We are looking for exceptional scientists to join our Applied Science team to help build industry-leading technology with multimodal language models for various edge applications. This role is for a Sr. Applied Scientist to lead science efforts for on-device inference pipelines and orchestration, working closely with cross-functional product and engineering teams to invent, design, develop, and validate new AI features for our devices. Key job responsibilities * Lead cross-functional efforts to invent, design, develop, and validate new AI features for our devices * Invent, build, and evaluate model inference and orchestrations to enable new customer experiences * Drive partnerships with product and engineering teams to implement algorithms and models in production * Train and optimize state-of-the-art multimodal models for resource-efficient deployment * Work closely with compiler engineers, hardware architects, data collection, and product teams A day in the life As an Applied Scientist with the Silicon and Solutions Group Edge AI team, you'll contribute to science solution design, conduct experiments, explore new algorithms, develop embedded inference pipelines, and discover ways to enrich our customer experiences. You'll have opportunities to collaborate across teams of engineers and scientists to bring algorithms and models to production. About the team Our Devices team specializes in inventing new-to-world, category creating products using advanced machine learning technologies. This role is on a new cross-functional team, whose cadence and structure resembles an efficient and fast-paced startup, with rapid growth and development opportunities.
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, N.reading
Amazon Industrial Robotics is seeking exceptional talent to help develop the next generation of advanced robotics systems that will transform automation at Amazon's scale. We're building revolutionary robotic systems that combine cutting-edge AI, sophisticated control systems, and advanced mechanical design to create adaptable automation solutions capable of working safely alongside humans in dynamic environments. This is a unique opportunity to shape the future of robotics and automation at an unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic dexterous manipulation, locomotion, and human-robot interaction. This role presents an opportunity to shape the future of robotics through innovative applications of deep learning and large language models. At Amazon Industrial Robotics we leverage advanced robotics, machine learning, and artificial intelligence to solve complex operational challenges at an unprecedented scale. Our fleet of robots operates across hundreds of facilities worldwide, working in sophisticated coordination to fulfill our mission of customer excellence. The ideal candidate will contribute to research that bridges the gap between theoretical advancement and practical implementation in robotics. You will be part of a team that's revolutionizing how robots learn, adapt, and interact with their environment. Join us in building the next generation of intelligent robotics systems that will transform the future of automation and human-robot collaboration. Key job responsibilities - Collaborate with simulation and robotics experts to translate physical modeling needs into robust, scalable, and maintainable simulation solutions. - Design and implement high-performance simulation modeling and tools for rigid and deformable body simulation. - Identify and optimize performance bottlenecks in simulation pipelines to support real-time and batch simulation workflows. - Help build validation and unit testing pipelines to ensure correctness and physical fidelity of simulation results. - Identify potential sources of sim-to-real gaps and propose modeling and numerical approximations to reduce them. - Stay current with the latest advances in numerical methods, parallel computing, and GPU architectures, and incorporate them into our tools.
IN, KA, Bengaluru
Amazon Devices is an inventive research and development company that designs and engineer high-profile devices like the Kindle family of products, Fire Tablets, Fire TV, Health Wellness, Amazon Echo & Astro products. This is an exciting opportunity to join Amazon in developing state-of-the-art techniques that bring Gen AI on edge for our consumer products. We are looking for exceptional scientists to join our Applied Science team and help develop the next generation of edge models, and optimize them while doing co-designed with custom ML HW based on a revolutionary architecture. Work hard. Have Fun. Make History. Key job responsibilities Quantize, prune, distill, finetune Gen AI models to optimize for edge platforms Fundamentally understand Amazon’s underlying Neural Edge Engine to invent optimization techniques Analyze deep learning workloads and provide guidance to map them to Amazon’s Neural Edge Engine Use first principles of Information Theory, Scientific Computing, Deep Learning Theory, Non Equilibrium Thermodynamics Train custom Gen AI models that beat SOTA and paves path for developing production models Collaborate closely with compiler engineers, fellow Applied Scientists, Hardware Architects and product teams to build the best ML-centric solutions for our devices Publish in open source and present on Amazon's behalf at key ML conferences - NeurIPS, ICLR, MLSys.
IN, KA, Bengaluru
You will be working with a unique and gifted team developing exciting products for consumers. The team is a multidisciplinary group of engineers and scientists engaged in a fast paced mission to deliver new products. The team faces a challenging task of balancing cost, schedule, and performance requirements. You should be comfortable collaborating in a fast-paced and often uncertain environment, and contributing to innovative solutions, while demonstrating leadership, technical competence, and meticulousness. Your deliverables will include development of thermal solutions, concept design, feature development, product architecture and system validation through to manufacturing release. You will support creative developments through application of analysis and testing of complex electronic assemblies using advanced simulation and experimentation tools and techniques. Key job responsibilities In this role, you will: - Lead end-to-end thermal design for SoC and consumer electronics, spanning package, board, system architecture, and product integration - Perform advanced CFD simulations using tools such as Star-CCM+ or FloEFD to assess feasibility, risks, and mitigation strategies - Plan and execute thermal validation for devices and SoC packages, ensuring compliance with safety, reliability, and qualification requirements - Partner with cross-functional and cross-site teams to influence product decisions, define thermal limits, and establish temperature thresholds - Develop data processing, statistical analysis, and test automation frameworks to improve insight quality, scalability, and engineering efficiency - Communicate thermal risks, trade-offs, and mitigation strategies clearly to engineering leadership to support schedule, performance, and product decisions About the team Amazon Lab126 is an inventive research and development company that designs and engineers high-profile consumer electronics. Lab126 began in 2004 as a subsidiary of Amazon.com, Inc., originally creating the best-selling Kindle family of products. Since then, we have produced innovative devices like Fire tablets, Fire TV and Amazon Echo. What will you help us create?
CA, BC, Vancouver
Success in any organization begins with its people and having a comprehensive understanding of our workforce and how we best utilize their unique skills and experience is paramount to our future success. WISE (Workforce Intelligence powered by Scientific Engineering) delivers the scientific and engineering foundation that powers Amazon's enterprise-wide workforce planning ecosystem. Addressing the critical need for precise workforce planning, WISE enables a closed-loop mechanism essential for ensuring Amazon has the right workforce composition, organizational structure, and geographical footprint to support long-term business needs with a sustainable cost structure. We are looking for a Sr. Applied Scientist to join our ML/AI team to work on Advanced Optimization and LLM solutions. You will partner with Software Engineers, Machine Learning Engineers, Data Engineers and other Scientists, TPMs, Product Managers and Senior Management to help create world-class solutions. We're looking for people who are passionate about innovating on behalf of customers, demonstrate a high degree of product ownership, and want to have fun while they make history. You will leverage your knowledge in machine learning, advanced analytics, metrics, reporting, and analytic tooling/languages to analyze and translate the data into meaningful insights. You will have end-to-end ownership of operational and technical aspects of the insights you are building for the business, and will play an integral role in strategic decision-making. Further, you will build solutions leveraging advanced analytics that enable stakeholders to manage the business and make effective decisions, partner with internal teams to identify process and system improvement opportunities. As a tech expert, you will be an advocate for compelling user experiences and will demonstrate the value of automation and data-driven planning tools in the People Experience and Technology space. Key job responsibilities * Engineering execution - drive crisp and timely execution of milestones, consider and advise on key design and technology trade-offs with engineering teams * Priority management - manage diverse requests and dependencies from teams * Process improvements – define, implement and continuously improve delivery and operational efficiency * Stakeholder management – interface with and influence your stakeholders, balancing business needs vs. technical constraints and driving clarity in ambiguous situations * Operational Excellence – monitor metrics and program health, anticipate and clear blockers, manage escalations To be successful on this journey, you love having high standards for yourself and everyone you work with, and always look for opportunities to make our services better.
RO, Bucharest
Amazon's Compliance and Safety Services (CoSS) Team is looking for a smart and creative Applied Scientist to apply and extend state-of-the-art research in NLP, multi-modal modeling, domain adaptation, continuous learning and large language model to join the Applied Science team. At Amazon, we are working to be the most customer-centric company on earth. Millions of customers trust us to ensure a safe shopping experience. This is an exciting and challenging position to drive research that will shape new ML solutions for product compliance and safety around the globe in order to achieve best-in-class, company-wide standards around product assurance. You will research on large amounts of tabular, textual, and product image data from product detail pages, selling partner details and customer feedback, evaluate state-of-the-art algorithms and frameworks, and develop new algorithms to improve safety and compliance mechanisms. You will partner with engineers, technical program managers and product managers to design new ML solutions implemented across the entire Amazon product catalog. Key job responsibilities As an Applied Scientist on our team, you will: - Research and Evaluate state-of-the-art algorithms in NLP, multi-modal modeling, domain adaptation, continuous learning and large language model. - Design new algorithms that improve on the state-of-the-art to drive business impact, such as synthetic data generation, active learning, grounding LLMs for business use cases - Design and plan collection of new labels and audit mechanisms to develop better approaches that will further improve product assurance and customer trust. - Analyze and convey results to stakeholders and contribute to the research and product roadmap. - Collaborate with other scientists, engineers, product managers, and business teams to creatively solve problems, measure and estimate risks, and constructively critique peer research - Consult with engineering teams to design data and modeling pipelines which successfully interface with new and existing software - Publish research publications at internal and external venues. About the team The science team delivers custom state-of-the-art algorithms for image and document understanding. The team specializes in developing machine learning solutions to advance compliance capabilities. Their research contributions span multiple domains including multi-modal modeling, unstructured data matching, text extraction from visual documents, and anomaly detection, with findings regularly published in academic venues.