Decarbonizing paper packaging

Amazon teams up with RTI International, Schlumberger, and International Paper on a project selected by the US Department of Energy to scale carbon capture and storage for the pulp and paper industry.

Amazon delivers billions of packages each year, and for these deliveries, we aim to use as little additional packaging as possible while still ensuring products arrive safely. When additional packaging is necessary, the majority of the packaging materials we use are made from paper. This includes boxes, paper mailers, and in some cases, paper bags. One of the sustainability benefits of using paper over other packaging materials, such as conventional plastics, is that paper is generally easier to recycle for our customers. However, as with any material produced at scale today, the production processes result in carbon emissions.

Related content
Amazon joins the US DOE’s Bio-Optimized Technologies to keep Thermoplastics out of Landfills and the Environment (BOTTLE™) Consortium, focusing on materials and recycling innovation.

The carbon emissions associated with paper packaging depend heavily on the type of paper mill, the processes and fuels used, and the grade of paper products produced. Currently, the most common type of containerboard paper mill in the US is a mixed paper mill that uses both virgin and recycled fiber. The recycled fiber generally comes from “old corrugated containers (OCC)”, which is a recycling stream that includes recycled boxes such as the Amazon boxes recycled by our customers. The virgin fiber is produced from wood chips that go through a chemical pulping process that breaks the bonds between the cellulose fibers in the wood and a glue-like substance called lignin that holds the fibers together. Containerboard paper mills that use both recycled and virgin fiber are the most common because of reduced energy demands, raw-material flexibility, cost effectiveness, and the regulatory environment.

For mills that use at least some virgin fiber to make paper, the process used to make the virgin fiber generates waste biomass that can be used as a fuel to reduce the reliance on fossil fuels. This waste biomass includes wood waste from debarking and chipping the wood and residual lignin (often called black liquor), a byproduct of the pulping process. When this waste biomass is used as a fuel for generating on-site steam and electricity, it generates what is called biogenic carbon emissions. Biogenic emissions are defined as CO2 emissions related to the natural carbon cycle, which include emissions resulting from the combustion of biological materials.

Biogenic emissions from the combustion of biomass release CO2 that was recently (in geological timeframes) sequestered by biological materials, such as plants. The US Environmental Protection Agency (EPA) does not include biogenic emissions in greenhouse gas (GHG) reporting and considers these emissions carbon neutral because of their negligible net contribution to atmospheric CO2 concentrations. This is in contrast to the carbon emissions associated with the burning of fossil fuels, which do contribute to reported GHG emissions.

Related content
Pioneering web-based PackOpt tool has resulted in an annual reduction in cardboard waste of 7% to 10% in North America, saving roughly 60,000 tons of cardboard annually.

In 2021, about 74% of the direct carbon emissions reported by the US pulp and paper sector were biogenic, with the remaining emissions coming from the use of fossil fuels. If these biogenic emissions are captured and permanently stored, instead of being released to the atmosphere, it enables the production of lower-carbon paper compared to traditional methods. By capturing and permanently storing biogenic carbon emissions, it is technically possible to sequester more biogenic carbon than the amount of fossil-based carbon released to the atmosphere as a result of the various industrial processes associated with paper production. This approach is generally referred to as bioenergy with carbon capture and storage (BECCS) and is considered by the Intergovernmental Panel on Climate Change (IPCC) as one of the key carbon dioxide removal technologies needed to limit global warming to 1.5°C above pre-industrial levels.

Stylized representations of a forest, cut logs, a paper mill, an energy plant, and decarbonized packaging boxes, showing (1) carbon flowing from the atmosphere to the forest and logs; (2) pulpwood, recycled boxes, and steam and electricity from the energy plant passing to the paper mill; (3) black liquor from the paper mill and woodwaste from the pulping process flowing to the energy plant; and sequestered carbon from the energy plant being stored underground.
Carbon flows for the production of paper with integrated carbon capture and storage.

Decarbonized paper packaging

Carbon capture and storage (CCS) technology, along with sustainably managed forests, together have the potential to create a paper industry that becomes a climate solution by sequestering more emissions than the industry is responsible for releasing to the atmosphere. Although CCS technologies show promise for helping reduce or even eliminate GHG emissions, these technologies have not yet been proven out at a larger scale.

Related content
Amazon advocates for updating carbon accounting to measure where renewable-energy projects will have the greatest impact.

To help accelerate the development and adoption of CCS, we assembled a multi-disciplinary team to develop and propose a concept to build a CCS plant at a containerboard mill operated by one of our packaging suppliers. The proposal was one of only four selected by the Office of Clean Energy Demonstrations in the US Department of Energy (DOE). Our team includes International Paper (IP), Schlumberger (SLB) for the design and engineering, and RTI International, the research organization that originally developed the carbon capture technology. RTI took the lead on the proposal submission.

The award is for up to $88 million, and if we are able to successfully complete all stages of this first-of-its-kind project (target date 2029), this large-scale demonstration facility will capture up to 120,000 metric tons of CO2 per year, a portion of which are biogenic emissions. A CCS plant of this size can enable an annual production of approximately 100,000 metric tons of decarbonized paper that can be used for future Amazon boxes and other packaging, benefiting both our customers and the environment.

Data on a virgin mill, a virgin-and-recycled mill, and a recycled mill, showing that, in all three, bioenergy with carbon capture and storage reduces carbon emissions significantly more than conventional carbon capture and storage.
This chart shows the impact of electrification, fuel switching, the use of bioenergy, and CCS on the cradle-to-gate greenhouse gas (GHG) emissions of containerboard paper produced from a virgin mill, mixed paper mill, and recycled mill. The analysis was performed using an internal Amazon decarbonization model based on US average data from FisherSolve®.

Carbon capture technologies

Carbon capture technologies absorb and separate CO2 from exhaust gases associated with combustion processes that burn fuels to generate thermal energy. There are three main approaches to how CO2 can be separated from exhaust gases: 1) pre-combustion capture, which involves absorbing the CO2 before the combustion is completed; 2) post-combustion capture, which involves absorbing the CO2 after the combustion process; and 3) oxyfuel combustion capture, which refers to burning the fuels in pure oxygen instead of air. With the oxyfuel approach, the exhaust gas is predominantly composed of CO2 and water vapor, enabling the CO2 to be easily separated. Each of these ways to absorb the CO2 varies in terms of efficacy, energy demand, and cost. The most well-developed approach is post-combustion capture.

Related content
Confronting climate change requires the participation of governments, companies, academics, civil-society organizations, and the public.

For post-combustion capture, the CO2 can be captured by a liquid or a solid material that likes to bind to CO2. For the liquid approach, a mixture of water and 20-30% of an amine compound is typically used to bind the CO2. The process begins with putting the water-amine mixture in contact with the exhaust gases to selectively absorb the CO2 from the gas stream. After the CO2 has been absorbed, the liquid mixture is heated in a different step to release the CO2. The separated CO2 can then be compressed for storage, and the amine can be regenerated for re-use. This water-amine liquid method is known for its efficacy, but it is also relatively energy intensive. Solid materials have shown equally good adsorption of CO2, but they also require relatively high amounts of energy to adsorb and release the CO2.

Over the past 13 years, RTI International has been developing a different water-amine liquid that has much less water and more amine to address the core challenges with the traditional water-amine solutions. By significantly reducing the water content in the amine-based liquid, RTI’s non-aqueous amine solvent (NAS) carbon capture technology is able to lower the energy requirements for the absorption-regeneration cycle by up to 36% compared to the traditional water-amine liquid.

In addition to reducing energy consumption, the NAS technology also minimizes operational risks and maintenance costs due to its extremely low corrosivity and enhanced physicochemical properties. RTI’s NAS process represents a step forward for industrial decarbonization. The deployment of RTI’s NAS technology through the awarded DOE project at IP’s Vicksburg containerboard mill can help demonstrate the scalability of this promising approach to carbon capture.

Amazon co-founded the Climate Pledge with a goal to reach net-zero carbon emissions across our operations by 2040, 10 years ahead of the Paris Agreement. We recognize that achieving this ambitious goal requires partnerships across all industries to explore and develop cutting-edge carbon reduction technologies, such as CCS. This project allows Amazon to work with one of its paper packaging suppliers to scale up and demonstrate RTI’s NAS technology to decarbonize the papermaking process. This project will also serve as the foundation for de-risking and scaling this technology more broadly in the pulp and paper industry and across other sectors, such as cement and steel.

Research areas

Related content

GB, MLN, Edinburgh
We’re looking for a Machine Learning Scientist in the Personalization team for our Edinburgh office experienced in generative AI and large models. You will be responsible for developing and disseminating customer-facing personalized recommendation models. This is a hands-on role with global impact working with a team of world-class engineers and scientists across the Edinburgh offices and wider organization. You will lead the design of machine learning models that scale to very large quantities of data, and serve high-scale low-latency recommendations to all customers worldwide. You will embody scientific rigor, designing and executing experiments to demonstrate the technical efficacy and business value of your methods. You will work alongside a science team to delight customers by aiding in recommendations relevancy, and raise the profile of Amazon as a global leader in machine learning and personalization. Successful candidates will have strong technical ability, focus on customers by applying a customer-first approach, excellent teamwork and communication skills, and a motivation to achieve results in a fast-paced environment. Our position offers exceptional opportunities for every candidate to grow their technical and non-technical skills. If you are selected, you have the opportunity to make a difference to our business by designing and building state of the art machine learning systems on big data, leveraging Amazon’s vast computing resources (AWS), working on exciting and challenging projects, and delivering meaningful results to customers world-wide. Key job responsibilities Develop machine learning algorithms for high-scale recommendations problems. Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both quantitative analysis and business judgement. Collaborate with software engineers to integrate successful experimental results into large-scale, highly complex Amazon production systems capable of handling 100,000s of transactions per second at low latency. Report results in a manner which is both statistically rigorous and compellingly relevant, exemplifying good scientific practice in a business environment.
IN, TS, Hyderabad
Welcome to the Worldwide Returns & ReCommerce team (WWR&R) at Amazon.com. WWR&R is an agile, innovative organization dedicated to ‘making zero happen’ to benefit our customers, our company, and the environment. Our goal is to achieve the three zeroes: zero cost of returns, zero waste, and zero defects. We do this by developing products and driving truly innovative operational excellence to help customers keep what they buy, recover returned and damaged product value, keep thousands of tons of waste from landfills, and create the best customer returns experience in the world. We have an eye to the future – we create long-term value at Amazon by focusing not just on the bottom line, but on the planet. We are building the most sustainable re-use channel we can by driving multiple aspects of the Circular Economy for Amazon – Returns & ReCommerce. Amazon WWR&R is comprised of business, product, operational, program, software engineering and data teams that manage the life of a returned or damaged product from a customer to the warehouse and on to its next best use. Our work is broad and deep: we train machine learning models to automate routing and find signals to optimize re-use; we invent new channels to give products a second life; we develop highly respected product support to help customers love what they buy; we pilot smarter product evaluations; we work from the customer backward to find ways to make the return experience remarkably delightful and easy; and we do it all while scrutinizing our business with laser focus. You will help create everything from customer-facing and vendor-facing websites to the internal software and tools behind the reverse-logistics process. You can develop scalable, high-availability solutions to solve complex and broad business problems. We are a group that has fun at work while driving incredible customer, business, and environmental impact. We are backed by a strong leadership group dedicated to operational excellence that empowers a reasonable work-life balance. As an established, experienced team, we offer the scope and support needed for substantial career growth. Amazon is earth’s most customer-centric company and through WWR&R, the earth is our customer too. Come join us and innovate with the Amazon Worldwide Returns & ReCommerce team!
US, WA, Seattle
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 add-on subscriptions such as Apple TV+, Max, 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 technologist, 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! In Prime Video READI, our mission is to automate infrastructure scaling and operational readiness. We are growing a team specialized in time series modeling, forecasting, and release safety. This team will invent and develop algorithms for forecasting multi-dimensional related time series. The team will develop forecasts on key business dimensions with optimization recommendations related to performance and efficiency opportunities across our global software environment. As a founding member of the core team, you will apply your deep coding, modeling and statistical knowledge to concrete problems that have broad cross-organizational, global, and technology impact. Your work will focus on retrieving, cleansing and preparing large scale datasets, training and evaluating models and deploying them to production where we continuously monitor and evaluate. You will work on large engineering efforts that solve significantly complex problems facing global customers. You will be trusted to operate with complete independence and are often assigned to focus on areas where the business and/or architectural strategy has not yet been defined. You must be equally comfortable digging in to business requirements as you are drilling into design with development teams and developing production ready learning models. You consistently bring strong, data-driven business and technical judgment to decisions. You will work with internal and external stakeholders, cross-functional partners, and end-users around the world at all levels. Our team makes a big impact because nothing is more important to us than delivering for our customers, continually earning their trust, and thinking long term. You are empowered to bring new technologies to your solutions. If you crave a sense of ownership, this is the place to be.
US, WA, Seattle
Amazon Advertising operates at the intersection of eCommerce and advertising, and is investing heavily in building a world-class advertising business. We are defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long-term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products to improve both shopper and advertiser experience. With a broad mandate to experiment and innovate, we grow at an unprecedented rate with a seemingly endless range of new opportunities. The Ad Response Prediction team in Sponsored Products organization build advanced deep-learning models, large-scale machine-learning pipelines, and real-time serving infra to match shoppers’ intent to relevant ads on all devices, for all contexts and in all marketplaces. Through precise estimation of shoppers’ interaction with ads and their long-term value, we aim to drive optimal ads allocation and pricing, and help to deliver a relevant, engaging and delightful ads experience to Amazon shoppers. As the business and the complexity of various new initiatives we take continues to grow, we are looking for talented Applied Scientists to join the team. Key job responsibilities As a Applied Scientist II, you will: * Conduct hands-on data analysis, build large-scale machine-learning models and pipelines * Work closely with software engineers on detailed requirements, technical designs and implementation of end-to-end solutions in production * Run regular A/B experiments, gather data, perform statistical analysis, and communicate the impact to senior management * Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving * Provide technical leadership, research new machine learning approaches to drive continued scientific innovation * Be a member of the Amazon-wide Machine Learning Community, participating in internal and external MeetUps, Hackathons and Conferences
US, CA, Palo Alto
Amazon’s Advertising Technology team builds the technology infrastructure and ad serving systems to manage billions of advertising queries every day. The result is better quality advertising for publishers and more relevant ads for customers. In this organization you’ll experience the benefits of working in a dynamic, entrepreneurial environment, while leveraging the resources of Amazon.com (AMZN), one of the world's leading companies. Amazon Publisher Services (APS) helps publishers of all sizes and on all channels better monetize their content through effective advertising. APS unites publishers with advertisers across devices and media channels. We work with Amazon teams across the globe to solve complex problems for our customers. The end results are Amazon products that let publishers focus on what they do best - publishing. The APS Publisher Products Engineering team is responsible for building cloud-based advertising technology services that help Web, Mobile, Streaming TV broadcasters and Audio publishers grow their business. The engineering team focuses on unlocking our ad tech on the most impactful Desktop, mobile and Connected TV devices in the home, bringing real-time capabilities to this medium for the first time. As a successful Data Scientist in our team, · You are an analytical problem solver who enjoys diving into data, is excited about investigations and algorithms, and can credibly interface between technical teams and business stakeholders. You will collaborate directly with product managers, BIEs and our data infra team. · You will analyze large amounts of business data, automate and scale the analysis, and develop metrics (e.g., user recognition, ROAS, Share of Wallet) that will enable us to continually measure the impact of our initiatives and refine the product strategy. · Your analytical abilities, business understanding, and technical aptitude will be used to identify specific and actionable opportunities to solve existing business problems and look around corners for future opportunities. Your expertise in synthesizing and communicating insights and recommendations to audiences of varying levels of technical sophistication will enable you to answer specific business questions and innovate for the future. · You will have direct exposure to senior leadership as we communicate results and provide scientific guidance to the business. Major responsibilities include: · Utilizing code (Apache, Spark, Python, R, Scala, etc.) for analyzing data and building statistical models to solve specific business problems. · Collaborate with product, BIEs, software developers, and business leaders to define product requirements and provide analytical support · Build customer-facing reporting to provide insights and metrics which track system performance · Influence the product strategy directly through your analytical insights · Communicating verbally and in writing to business customers and leadership team with various levels of technical knowledge, educating them about our systems, as well as sharing insights and recommendations
US, WA, Bellevue
mmPROS Surface Research Science seeks an exceptional Applied Scientist with expertise in optimization and machine learning to optimize Amazon's middle mile transportation network, the backbone of its logistics operations. Amazon's middle mile transportation network utilizes a fleet of semi-trucks, trains, and airplanes to transport millions of packages and other freight between warehouses, vendor facilities, and customers, on time and at low cost. The Surface Research Science team delivers innovation, models, algorithms, and other scientific solutions to efficiently plan and operate the middle mile surface (truck and rail) transportation network. The team focuses on large-scale problems in vehicle route planning, capacity procurement, network design, forecasting, and equipment re-balancing. Your role will be to build innovative optimization and machine learning models to improve driver routing and procurement efficiency. Your models will impact business decisions worth billions of dollars and improve the delivery experience for millions of customers. You will operate as part of a team of innovative, experienced scientists working on optimization and machine learning. You will work in close collaboration with partners across product, engineering, business intelligence, and operations. Key job responsibilities - Design and develop optimization and machine learning models to inform our hardest planning decisions. - Implement models and algorithms in Amazon's production software. - Lead and partner with product, engineering, and operations teams to drive modeling and technical design for complex business problems. - Lead complex modeling and data analyses to aid management in making key business decisions and set new policies. - Write documentation for scientific and business audiences. About the team This role is part of mmPROS Surface Research Science. Our mission is to build the most efficient and optimal transportation network on the planet, using our science and technology as our biggest advantage. We leverage technologies in optimization, operations research, and machine learning to grow our businesses and solve Amazon's unique logistical challenges. Scientists in the team work in close collaboration with each other and with partners across product, software engineering, business intelligence, and operations. They regularly interact with software engineering teams and business leadership.
IL, Tel Aviv
Come join the AWS Agentic AI science team in building the next generation models for intelligent automation. AWS, the world-leading provider of cloud services, has fostered the creation and growth of countless new businesses, and is a positive force for good. Our customers bring problems that will give Applied Scientists like you endless opportunities to see your research have a positive and immediate impact in the world. You will have the opportunity to partner with technology and business teams to solve real-world problems, have access to virtually endless data and computational resources, and to world-class engineers and developers that can help bring your ideas into the world. As part of the team, we expect that you will develop innovative solutions to hard problems, and publish your findings at peer reviewed conferences and workshops. We are looking for world class researchers with experience in one or more of the following areas - autonomous agents, API orchestration, Planning, large multimodal models (especially vision-language models), reinforcement learning (RL) and sequential decision making. Key job responsibilities PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience 3+ years of building models for business application experience Experience in patents or publications at top-tier peer-reviewed conferences or journals Experience programming in Java, C++, Python or related language Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
IL, Haifa
Come join the AWS Agentic AI science team in building the next generation models for intelligent automation. AWS, the world-leading provider of cloud services, has fostered the creation and growth of countless new businesses, and is a positive force for good. Our customers bring problems that will give Applied Scientists like you endless opportunities to see your research have a positive and immediate impact in the world. You will have the opportunity to partner with technology and business teams to solve real-world problems, have access to virtually endless data and computational resources, and to world-class engineers and developers that can help bring your ideas into the world. As part of the team, we expect that you will develop innovative solutions to hard problems, and publish your findings at peer reviewed conferences and workshops. We are looking for world class researchers with experience in one or more of the following areas - autonomous agents, API orchestration, Planning, large multimodal models (especially vision-language models), reinforcement learning (RL) and sequential decision making.
US, NY, New York
Join us in a historic endeavor to make Generative AI accessible to the world with breakthrough research! The AWS AI team has a world-leading team of researchers and academics, and we are looking for world-class colleagues to join us and make the AI revolution happen. Our team of scientists drives the innovation that enables external and internal SageMaker customers to train their next generation models on both GPU and Trainium instances. As part of the team, we expect that you will develop innovative solutions to hard problems, and publish your findings at peer reviewed conferences and workshops. AWS is the world-leading provider of cloud services, has fostered the creation and growth of countless new businesses, and is a positive force for good. Our customers bring problems which will give Applied Scientists like you endless opportunities to see your research have a positive and immediate impact in the world. You will have the opportunity to partner with technology and business teams to solve real-world problems, have access to virtually endless data and computational resources, and to world-class engineers and developers that can help bring your ideas into the world. About the team Why AWS Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Utility Computing (UC) AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (IoT), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Mentorship and Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
US, WA, Seattle
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 add-on subscriptions such as Apple TV+, Max, 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 in the Content Understanding Team, you will lead the end-to-end research and deployment of video and multi-modal models applied to a variety of downstream applications. More specifically, you will: - Work backwards from customer problems to research and design scientific approaches for solving them - Work closely with other scientists, engineers and product managers to expand the depth of our product insights with data, create a variety of experiments to determine the high impact projects to include in planning roadmaps - Stay up-to-date with advancements and the latest modeling techniques in the field - Publish your research findings in top conferences and journals About the team Our Prime Video Content Understanding team builds holistic media representations (e.g. descriptions of scenes, semantic embeddings) and apply them to new customer experiences supply chain problems. Our technology spans the entire Prime Video catalogue globally, and we enable instant recaps, skip intro timing, ad placement, search, and content moderation.