Amazon and Energy Dept. team up to change how we recycle plastic

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.

Materials science probably does not come to mind when most people think of Amazon, but materials play a foundational role in almost everything we do. Materials often dictate what is possible in the physical world, from the thermal properties of materials used in our Echo devices to the fracture strength of lightweight structural materials used in our future low-Earth-orbit satellites.

Materials also play an outsized role in the area of sustainability. For example, global materials production contributes over 20% of all greenhouse gas (GHG) emissions, and over 75% of these emissions are generated from just four materials sectors: cement, steel, pulp and paper, and plastics.

Of all the materials used today, plastics are the fastest-growing category and offer the greatest opportunity for innovation. In joining the BOTTLE™ Consortium, led by the National Renewable Energy Laboratory (NREL), Amazon aims to help develop the foundational technologies that will enable the full life cycle of plastics to be net-zero carbon. From a scientific perspective, this requires rethinking plastics at the molecular level and developing new technologies that will keep these molecules in use.

Polyethylene.png
The repeating units of polyethylene polymer chains are characterized by strong carbon-carbon bonds.

Today, the most commonly used plastics are polyolefins, which include polyethylene and polypropylene, and the most common application for these materials is packaging. Recently, Raoul Meys and collaborators published an article in Science describing the feasibility of achieving net-zero, or even net-negative, carbon emissions for the full life cycle of these and other existing conventional plastics.

In this situation, the terms “net-zero” and “net-negative” mean that the sum of the total emissions associated with the life cycle of the material is zero or negative, respectively. This is possible when the carbon sequestered throughout the life cycle of the material, either from biomass feedstock or carbon capture technologies, equals or exceeds the total carbon emissions associated with materials production and end-of-life.

Based on the model Meys and collaborators developed, net-zero, or even slightly net-negative, carbon emissions are possible over the life cycle of plastics if we create a “circular carbon pathway” that combines mechanical recycling, chemical recycling with carbon capture, and feedstock derived from biomass and/or captured carbon. In essence, the carbon in the molecular backbone of these plastics should come from CO2 that is pulled out of the atmosphere (either through technological or biological means), and we should expand known recycling technologies that will keep the carbon in use as long as possible.

More on materials

Although the research by Meys and team shows a challenging yet feasible path toward net-zero carbon emissions for plastics, there are drawbacks to relying solely on existing commodity materials and known recycling technologies. The strong carbon-carbon bonds in polyolefins are difficult to break down, so in cases where mechanical recycling is not cost-effective — or even possible, due to contamination — energy-intensive chemical recycling processes (pyrolysis or gasification) would be required to recover and reuse the carbon. Likewise, conventional polyolefins with a carbon-carbon molecular backbone don’t break down easily in natural environments, an important consideration in cases where these materials may not make it into a recycling stream.

Amazon’s recent partnership with the BOTTLE (Bio-Optimized Technologies to keep Thermoplastics out of Landfills and the Environment) Consortium aims to help overcome some of these drawbacks and accelerate the path toward more-sustainable plastics.

Deconstructable waste

The goal of our work is to develop new technologies that will not only enable but also encourage keeping the carbon in plastics in use by ensuring it is both technically and economically viable to recover and recycle these materials at the end of their life. One objective of our work with the BOTTLE Consortium is to develop an energy-efficient chemical processing technology that can break down or deconstruct a mixed waste stream of plastics with labile bonds (i.e., bonds that are easy to deconstruct) into valuable feedstock that can be used to make the same types of plastics (closed-loop recycling) or new plastics altogether (open-loop recycling). And in the cases where these materials don’t make it into a future recycling stream, the molecular structure of these materials can be designed to biodegrade in natural environments.

AmazonScience_BOTTLE_RecyclingAnimation_1920x1080_V2.gif
New recycling methods can be used to deconstruct a mixed waste stream of polymers that are recyclable by design. The recycled molecules can then be used to make new materials without degraded properties.

By developing a new deconstruction technology that can handle a mixed waste stream of plastics, we will be eliminating the need for excessive sortation of the materials before deconstruction. This will also help accelerate scaling of the technology because of greater available-material volumes, and the technology itself will not be dependent on the commercial success of a single type of material.

An additional objective of the initial work we are doing with the BOTTLE Consortium is to develop new plastics that could be made from the chemicals coming out of this new deconstruction process. In some cases, closed-loop recycling may make the most sense. In other cases, developing new polymers from the deconstructed materials may be a better option.

Related content
A combination of deep learning, natural language processing, and computer vision enables Amazon to hone in on the right amount of packaging for each product.

Our plan is to synthesize new materials from the deconstructed plastics and process them into films to understand their structure-property relationships and then develop a path towards recyclable-by-design replacements for packaging applications, while also ensuring these materials could be composted in an industrial facility or safely degrade in natural environments.

We envision this new flexible deconstruction process as a flywheel, where the materials that require the least amount of time and energy to break down and recover will lead to lower-cost feedstock for new-materials production, leading to lower-cost materials. The lower costs of these materials will then further incentivize their use over traditional plastics. In addition, we anticipate that the materials that more easily break down in this new process will also have the added benefit of being more likely to be compostable or to easily degrade in natural environments.

Compostable recycling

This may lead to the question why. Why develop a new technology that can recycle plastics that can naturally degrade? Why not just help develop end-of-life pathways to compost those materials? There are two main reasons why we believe this is an important path to pursue.

Related content
New statistical model reduces shipment damage by 24% while cutting shipping costs by 5%.

The first is that we want to invent technologies that will ultimately incentivize the broad use of materials that can naturally degrade in the environment but are recycled because of their economic value as feedstock for new materials. This will reduce the need for additional feedstock for making new materials, which will reduce carbon emissions, while also ensuring plastics do not persist in the environment in the cases where they do not make it into a managed waste stream. This is not possible with conventional plastics but could be possible with new emerging plastics as the production and use of these materials grow, and new recycling technologies are developed.

The second reason is that these new emerging plastics have the potential to enable a more efficient recycling system. Plastics that are biodegradable, either in a compost pile or in the natural environment, are fundamentally easier to deconstruct into intermediate chemicals than conventional plastics are. This opens the possibility for efficient processes that can infinitely recycle the carbon molecules in these materials without degradation of properties (e.g., mechanical recycling) or the substantial amounts of energy needed to deconstruct strong carbon-carbon bonds (e.g., pyrolysis).

Ultimately, the success of this work at scale will require a fundamental shift in both the plastics that are used in our everyday lives, especially plastics used in applications such as food packaging, and the recycling systems and infrastructure to keep these materials in use. Effecting that shift is a daunting task. But knowing that Amazon started out as an online bookstore serving customers out of a garage provides hope that even daunting tasks are achievable.

Research areas

Related content

US, WA, Seattle
Do you want to join an innovative team of scientists who use machine learning to help Amazon provide the best experience to our Selling Partners by automatically understanding and addressing their challenges, needs and opportunities? Do you want to build advanced algorithmic systems that are powered by state-of-art ML, such as Natural Language Processing, Large Language Models, Deep Learning, Computer Vision and Causal Modeling, to seamlessly engage with Sellers? Are you excited by the prospect of analyzing and modeling terabytes of data and creating cutting edge algorithms to solve real world problems? Do you like to build end-to-end business solutions and directly impact the profitability of the company and experience of our customers? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Selling Partner Experience Science team. Key job responsibilities - Use statistical and machine learning techniques to create the next generation of the tools that empower Amazon's Selling Partners to succeed. - Design, develop and deploy highly innovative models to interact with Sellers and delight them with solutions. - Work closely with teams of scientists and software engineers to drive real-time model implementations and deliver novel and highly impactful features. - Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation. - Research and implement novel machine learning and statistical approaches. - Participate in strategic initiatives to employ the most recent advances in ML in a fast-paced, experimental environment. About the team Selling Partner Experience Science is a growing team of scientists, engineers and product leaders engaged in the research and development of the next generation of ML-driven technology to empower Amazon's Selling Partners to succeed. We draw from many science domains, from Natural Language Processing to Computer Vision to Optimization to Economics, to create solutions that seamlessly and automatically engage with Sellers, solve their problems, and help them grow. Focused on collaboration, innovation and strategic impact, we work closely with other science and technology teams, product and operations organizations, and with senior leadership, to transform the Selling Partner experience. We are open to hiring candidates to work out of one of the following locations: Denver, CO, USA | Seattle, WA, USA
US, WA, Seattle
Amazon is investing heavily in building a world class advertising business and developing a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses for 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. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities. Key job responsibilities Search Supply and Experiences, within Sponsored Products, is seeking a Senior Data Scientist to join a fast growing team with the mandate of creating new ads experience that elevates the shopping experience for our hundreds of millions customers worldwide. We are looking for a top analytical mind capable of understanding our complex ecosystem of advertisers participating in a pay-per-click model– and leveraging this knowledge to help turn the flywheel of the business. As a Senior Data Scientist on this team you will: - Lead Data Science solutions from beginning to end. - Deliver with independence on challenging large-scale problems with ambiguity. - Manage and drive the technical and analytical aspects of Advertiser segmentation; continually advance approach and methods. - Write code (Python, R, Scala, etc.) to analyze data and build statistical models to solve specific business problems - Retrieve, synthesize, and present critical data in a format that is immediately useful to answering specific questions or improving system performance. - Analyze historical data to identify trends and support decision making. - Improve upon existing methodologies by developing new data sources, testing model enhancements, and fine-tuning model parameters. - Provide requirements to develop analytic capabilities, platforms, and pipelines. - Apply statistical and machine learning knowledge to specific business problems and data. - Formalize assumptions about how our systems should work, create statistical definitions of outliers, and develop methods to systematically identify outliers. Work out why such examples are outliers and define if any actions needed. - Given anecdotes about anomalies or generate automatic scripts to define anomalies, deep dive to explain why they happen, and identify fixes. - Build decision-making models and propose solution for the business problem you defined - Conduct written and verbal presentation to share insights and recommendations to audiences of varying levels of technical sophistication. - Write code (python or another object-oriented language) for data analyzing and modeling algorithms. A day in the life The Senior Data Scientist will have the opportunity to use one of the world's largest eCommerce and advertising data sets to influence the evolution of our products. This role requires an individual with excellent business, communication, and technical skills, enabling collaboration with various functions, including product managers, software engineers, economists and data scientists, as well as senior leadership. This role will create and enhance performance monitoring reports to find insights that product and business team should focus on. The successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail, and with an ability to work in a fast-paced, high-energy and ever-changing environment. The drive and capability to shape the direction is a must. This role will influence the direction of the business by leveraging our data to deliver insights that drive decisions and actions. The role will involve translating broad business problems into specific analytics projects, conducting deep quantitative analyses, and communicating results effectively. The role will help the organization identify, evaluate, and evangelize new techniques and tools to continue to improve our ability to deliver value to Amazon’s customers. About the team We are a customer-obsessed team of engineers, technologists, product leaders, and scientists. We are focused on continuous exploration of contexts and creatives where advertising delivers value to customers and advertisers. We specifically work on new ads experiences globally with the goal of helping shoppers make the most informed purchase decision. We obsess about our customers and we are continuously innovating on their behalf to enrich their shopping experience on Amazon We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA
US, CA, Pasadena
The Amazon Web Services (AWS) Center for Quantum Computing (CQC) is a multi-disciplinary team of scientists, engineers, and technicians, on a mission to develop a fault-tolerant quantum computer. We are looking to hire an Applied Scientist to work on the embedded software for our control system. The position is on-site at our lab, located on the Caltech campus in Pasadena, CA. The ideal candidate will be able to translate high-level requirements (e.g. latency, bandwidth, architecture) into software/firmware implementations (e.g. low-level device drivers, kernel modules, Python APIs) compatible with our FPGA-based control systems. This requires someone who (1) has a strong desire to work within a team of scientists and engineers, and (2) demonstrates ownership in initiating and driving projects to completion. Key job responsibilities - Develop embedded software in C, C++ or Rust for high-performance real-time tasks. - Develop Linux and/or real-time operating system (RTOS) features required to operate control system. - Develop FPGA gateware that drives domain-specific functions of our control hardware. - Develop user-space API that exposes low-level features, preferably in Python. - Develop, test, and optimize control system features on bench-top and in real-world conditions. - Own the stability of control system software and firmware. We are looking for candidates with strong engineering principles, resourcefulness and a bias for action, superior problem-solving and excellent communication skills. Working effectively within a team environment is essential. You will have the opportunity to work on new ideas and stay abreast of the field of experimental quantum computation. A day in the life The lifetime of your projects will likely begin with a lot of discussion and negotiation with our scientists and engineers to translate their software and hardware feature requests into design proposals that demonstrate sensible trade-offs between complexity and delivery. Once a design proposal has been accepted, you will implement it in a logical and maintainable manner. You will also be encouraged to take ownership over the stability and quality of the software and hardware stack by identifying, proposing, and implementing features that will accelerate our realization of quantum computing technologies. You will be joining the Control & Calibration Software team within the AWS Center of Quantum Computing. Our team is comprised of scientists and engineers who are building scalable software that enables quantum computing technologies. About the team 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. Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the 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. 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. 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. Mentorship & 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. 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. Hybrid Work We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices. We are open to hiring candidates to work out of one of the following locations: Pasadena, CA, USA
US, WA, Seattle
Alexa is the Amazon cloud service that powers Echo, the groundbreaking Amazon device designed around your voice. We believe voice is the most natural user interface for interacting with technology across many domains; we are inventing the future. Alexa Audio is responsible for fulfilling customers requests for all types of audio content (Music, Radio, Podcasts, Books, custom sounds) across all Alexa enabled devices. This covers a broad set of experiences including search, browse, recommendations, playback, and devices grouping and controls. We are seeking a talented, self-directed Applied Scientists who would come up with state of the art semantic search and recommendation techniques that work with both voice and visual interfaces. This is a unique opportunity where you will be working on latest technologies including LLMs, and also see it impact customer's lives in meaningful ways. Responsibilities - Apply advance state-of-the-art artificial intelligence techniques and develop algorithms in areas of personalization, voice based dialogue systems and natural language information retrieval. - Design scientifically sound online experiments and offline simulations to study and improve products. - Work closely with talented engineers to create scalable models and put them to production. - Perform statistical analyses on large data sets, identify problems, and propose solutions. - Work with partner science teams to identify collaboration opportunities. Work hard. Have fun. Make history. We are open to hiring candidates to work out of one of the following locations: Bellevue, WA, USA | Seattle, WA, USA | Sunnyvale, CA, USA
ES, M, Madrid
Amazon's International Technology org in EU (EU INTech) is creating new ways for Amazon customers discovering Amazon catalog through new and innovative Customer experiences. Our vision is to provide the most relevant content and CX for their shopping mission. We are responsible for building the software and machine learning models to surface high quality and relevant content to the Amazon customers worldwide across the site. The team, mainly located in Madrid Technical Hub, London and Luxembourg, comprises Software Developer and ML Engineers, Applied Scientists, Product Managers, Technical Product Managers and UX Designers who are experts on several areas of ranking, computer vision, recommendations systems, Search as well as CX. Are you interested on how the experiences that fuel Catalog and Search are built to scale to customers WW? Are interesting on how we use state of the art AI to generate and provide the most relevant content? Key job responsibilities We are looking for Applied Scientists who are passionate to solve highly ambiguous and challenging problems at global scale. You will be responsible for major science challenges for our team, including working with text to image and image to text state of the art models to scale to enable new Customer Experiences WW. You will design, develop, deliver and support a variety of models in collaboration with a variety of roles and partner teams around the world. You will influence scientific direction and best practices and maintain quality on team deliverables. We are open to hiring candidates to work out of one of the following locations: Madrid, M, ESP
GB, London
Amazon Advertising is looking for an Applied Scientist to join its initiative that powers Amazon’s contextual advertising products. Advertising at Amazon is a fast-growing multi-billion dollar business that spans across desktop, mobile and connected devices; encompasses ads on Amazon and a vast network of hundreds of thousands of third party publishers; and extends across US, EU and an increasing number of international geographies.The Supply Quality organization has the charter to solve optimization problems for ad-programs in Amazon and ensure high-quality ad-impressions. We develop advanced algorithms and infrastructure systems to optimize performance for our advertisers and publishers. We are focused on solving a wide variety of problems in computational advertising like Contextual data processing and classification, traffic quality prediction (robot and fraud detection), Security forensics and research, Viewability prediction, Brand Safety and experimentation. Our team includes experts in the areas of distributed computing, machine learning, statistics, optimization, text mining, information theory and big data systems. We are looking for a dynamic, innovative and accomplished Applied Scientist to work on machine learning and data science initiatives for contextual data processing and classification that power our contextual advertising solutions. Are you excited by the prospect of analyzing terabytes of data and leveraging state-of-the-art data science and machine learning techniques to solve real world problems? Do you like to own business problems/metrics of high ambiguity where yo get to define the path forward for success of a new initiative? As an applied scientist, you will invent ML based solutions to power our contextual classification technology. As this is a new initiative, you will get an opportunity to act as a thought leader, work backwards from the customer needs, dive deep into data to understand the issues, conceptualize and build algorithms and collaborate with multiple cross-functional teams. Key job responsibilities * Design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both analysis and business judgment. * Collaborate with software engineering teams to integrate successful experiments into large-scale, highly complex Amazon production systems. * Promote the culture of experimentation and applied science at Amazon. * Demonstrated ability to meet deadlines while managing multiple projects. * Excellent communication and presentation skills working with multiple peer groups and different levels of management * Influence and continuously improve a sustainable team culture that exemplifies Amazon’s leadership principles. We are open to hiring candidates to work out of one of the following locations: London, GBR
US, WA, Bellevue
The Planning and Execution team (PLEX) is seeking a Research Scientist to build & improve mathematical optimization techniques and algorithms to support planning and execution activities throughout North America. PLEX is comprised of high-powered dynamic teams, which are shaping network execution through the development and application of innovative labor & flow planning mechanisms. Our goal is to improve and enhance the Amazon Fulfillment network to ultimately drive the best customer experience in a reliable and cost-efficient manner that is truly world-class. As part of the PLEX organization, you’ll partner closely with other scientists, engineers, and product teams in a collegial environment to build optimization strategies that will influence the performance of all North America Amazon Fulfillment networks. You will develop scientific models and perform complex mathematical research to accurately solve labor and flow planning problems, enhance automation, and provide value-added research to the business. You will continually iterate and identify new modeling and research opportunities to implement science into customer fulfillment planning processes. We are looking for a passionate scientist with a commitment to innovation & teamwork. Successful candidates will have a deep knowledge of optimization techniques and ML methods to tackle complex science problems. You will have the communication skills necessary to impact and influence leadership & partner teams through technical writings, presentations and discussions. You will learn a lot, grow, and have fun in the process! Innovation Opportunities & Career Growth Our business grows fast and we want our employees growing with it too. We provide constant opportunities for growth in our team through regular training, talent development, mentoring, and mechanisms conducive to incubating ideas from the bottom up to showcase your innovations. Inclusive Team Culture Here at Amazon, we promote an inclusive and engaging environment. We understand the strength that unique experiences bring to the team and value it. In our team, we uphold that all individuals should feel included, respected, and developed. Flexibility It's not the hours that you put into work matters, rather it's the quality of work that you put in. We provide flexibility and support to help you find a balance between your work and personal lives. This position will be based in Austin, TX We are open to hiring candidates to work out of one of the following locations: - Austin, TX - Bellevue, WA - Nashville, TN Key job responsibilities - Create & improve mathematical optimization techniques & ML models for labor & flow planning - Lead & partner with research, applied, and data science teams to improve accuracy of existing technology solutions and provide data driven recommendations for strategic model implementations - Identify and thoroughly research external and previously non-considered factors to implement with advanced mathematics - Simplify the scientific decisions by navigating through the technology complexities, explaining them in plain customer and business context to our partners & customers. We are open to hiring candidates to work out of one of the following locations: Austin, TX, USA | Bellevue, WA, USA | Nashville, TN, USA
US, WA, Seattle
We are building GenAI based shopping assistant for Amazon. We reimage Amazon Search with an interactive conversational experience that helps you find answers to product questions, perform product comparisons, receive personalized product suggestions, and so much more, to easily find the perfect product for your needs. We’re looking for the best and brightest across Amazon to help us realize and deliver this vision to our customers right away. This will be a once in a generation transformation for Search, just like the Mosaic browser made the Internet easier to engage with three decades ago. If you missed the 90s—WWW, Mosaic, and the founding of Amazon and Google—you don’t want to miss this opportunity. We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA
US, NY, New York
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. Within AWS UC, Amazon Dedicated Cloud (ADC) roles engage with AWS customers who require specialized security solutions for their cloud services. Amazon AI is looking for world class scientists and engineers to join its AWS AI Labs to develop groundbreaking generative AI technologies in Amazon Q. Q is an interactive, AI-powered assistant that touches all aspects of builder and developer experience. You will be part of the Q Code Analysis team that works at the intersection of code analysis, logical reasoning and machine learning to build and enhance capabilities, safety and security of AI-powered developer tools in Amazon Q. You will invent, implement, and deploy state-of-the-art algorithms and systems, and be at the heart of a growing and exciting focus area for AWS. Your work will directly impact millions of our customers in the form of products and services that are based on large language models, retrieval-augmented generation, code analysis, responsible AI, and a lot more. You will make breakthroughs that challenge the limits of code analysis, machine learning and AI while collaborating with academics and interacting directly with customers to bring new research rapidly to production. A day in the life Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the 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. 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. 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. Mentorship & 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. 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. EEO/Accommodations AWS is committed to a diverse and inclusive workplace to deliver the best results for our customers. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status; we celebrate the diverse ways we work. For individuals with disabilities who would like to request an accommodation, please let us know and we will connect you to our accommodation team. You may also reach them directly by visiting please https://www.amazon.jobs/en/disability/us. Hybrid Work We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our [insert req country location here] Amazon offices. About the team The Amazon Web Services (AWS) Next Gen DevX (NGDE) team uses generative AI and foundation models to reimagine the experience of all builders on AWS. From the IDE to web-based tools and services, AI will help engineers work on large and small applications. We explore new technologies and find creative solutions. Curiosity and an explorative mindset can find a place here to impact the life of engineers around the world. If you are excited about this space and want to enlighten your peers with new capabilities, this is the team for you. We are open to hiring candidates to work out of one of the following locations: New York, NY, USA
DE, Berlin
The Amazon Artificial General Intelligence (AGI) team is looking for a passionate, highly skilled and inventive Senior Applied Scientist with strong machine learning background to lead the development and implementation of state-of-the-art ML systems for building large-scale, high-quality conversational assistant systems. Key job responsibilities - Use deep learning, ML and NLP techniques to create scalable solutions for creation and development of language model centric solutions for building personalized assistant systems based on a rich set of structured and unstructured contextual signals - Innovate new methods for contextual knowledge extraction and information representation, using language models in combination with other learning techniques, that allows effective grounding in context providers when considering memory, cpu, latency and quality - Collaborate with cross-functional teams of engineers, product managers, and scientists to identify and solve complex problems in personal knowledge aggregation, processing and verification - Design and execute experiments to evaluate the performance of different algorithms and models, and iterate quickly to improve results - Think Big about the arc of development of conversational assistant system personalization over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems - Communicate results and insights to both technical and non-technical audiences, including through presentations and written reports - Mentor and guide junior scientists and engineers, and contribute to the overall growth and development of the team A day in the life As a Senior Applied Scientist, you will play a critical role in driving the development of personalization techniques enabling conversational systems, in particular those based on large language models, to be tailored to customer needs. You will handle Amazon-scale use cases with significant impact on our customers' experiences. We are open to hiring candidates to work out of one of the following locations: Berlin, DEU