The path to better plastics: Our progress and partnerships

How Amazon is helping transform plastics through innovation in materials, recycling technology, sortation, and more.

In 2022, we shared our vision for transforming plastics through an innovative collaboration with the U.S. Department of Energy's BOTTLE Consortium. Today, that vision is advancing from laboratory concept to commercial trials. Through work with our partners — from material scientists to recycling facilities to Amazon Fresh stores — we're demonstrating the steps to prove out a new value chain for plastics that are derived from renewable resources and easily recyclable, while also being naturally biodegradable.

When we first started this work, we knew we needed to develop a new recycling technology that could efficiently process biodegradable plastics, as that is not something that exists at scale today. Our specific focus was on polyester-based biodegradable plastics. The molecular backbones of these plastics contain carbon-oxygen ester linkages, which are much easier to break down than the carbon-carbon bonds found in more common plastics, such as polyethylene or polypropylene.

AWWS_PackagingInnovationsLab_Skrobecki_ -134 (1).jpg
Amazon scientists test biopolyester materials in the Sustainable Materials Innovation Lab.

The ester linkages that make these types of plastics more susceptible to biodegradation also make them easier to break down in controlled environments where the remaining molecules can be recycled back into new materials. Solvolysis techniques, such as methanolysis and glycolysis, are being developed for polyethylene terephthalate (PET), but they could be extended to other polyesters, such as polylactic acid (PLA) or polyhydroxyalkanoates (PHAs), that are more readily biodegradable.

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.

While focusing on recycling polyester-based biodegradable plastics — or biopolyesters, for short — we also aimed to make this new recycling technology work for a mixed-waste stream of materials. There is no single biodegradable plastic that can meet the diverse needs of different packaging applications, and applications will often require blends or different materials layered together.

Having a separate recycling stream for each new type of biopolyester plastic would be impractical and likely uneconomical. It also would not solve the problem of recycling blends and multilayered materials. Working backward from this insight, we partnered with scientists at the National Renewable-Energy Laboratory (NREL) to conduct a comprehensive analysis comparing different chemical recycling approaches for recycling a mixed-waste stream of polyester-based plastics.

Our initial analysis, which was recently published in One Earth, provided the scientific foundation for what would become EsterCycle™, a new startup founded by one of our collaborators at NREL, Julia Curley. EsterCycle™’s technology uses low-energy methanolysis processes with an amine catalyst to selectively break the ester bonds that hold these polymers together.

EsterCycle 1.jpg
Julia Curley, founder of EsterCycle.

Importantly, the recycling technology was developed to handle a mixed-waste stream of polyesters without requiring extensive sorting of different materials beforehand. This is a crucial advantage because it means we can start recycling biopolyesters even while they represent a small portion of the waste stream, processing them alongside more common materials like PET.

The development of the EsterCycle™ technology represents a key step toward our vision of a more sustainable circular value chain for plastics, but for EsterCycle™ to succeed at scale, there needs to be a reliable supply of materials to recycle. This is where our partnership with Glacier Technologies comes in.

Glacier, which Amazon’s Climate Pledge Fund recently invested in, uses AI-powered robots to automate the sorting of recyclables and collect real-time data on recycling streams. In real time, Glacier’s proprietary AI model can identify a range of different material and package types, from rigid PET containers, such as thermoformed clam shells, to multi-material flexible packaging, such as snack bags.

Glacier 1.jpg
Glacier’s AI vision and robotic systems are used at a materials recovery facility to sort new materials in mixed-waste streams.

We launched a sortation trial with Glacier and a recycling facility in San Francisco to test how effectively Glacier’s AI vision and robotic systems could identify and sort biopolyester packaging. A key insight from these trials was that packaging design significantly influences AI detection. Packaging with consistent, visible features was identified correctly by Glacier's AI models 99% of the time. However, lookalike materials and inconsistent designs led to higher rates of misidentification. These results will help us and our partners design packaging that's easier to recycle as we design and test emerging biopolyesters for new applications.

Our next step in helping build out this new value chain for plastics was to test and trial emerging biopolyesters in real-world applications. Our first priority is to minimize packaging — and even eliminate it, where possible. But there are some applications where packaging is necessary, and paper is not a viable option — particularly, applications with specific and stringent requirements, such as moisture barrier properties. To understand how biopolyesters perform in these critical applications, we launched several commercial trials across our operations.

In Seattle, we tested biopolyester produce bags made with Novamont's Mater-Bi material in Amazon Fresh stores. Customer feedback was overwhelmingly positive, with 83% of Amazon Fresh customers reporting they "really liked" the new compostable bags. Our shelf-life testing showed that the bags performed similarly to conventional plastic bags in keeping produce fresh for the first week after purchase, though different types of produce showed varying results in longer-term storage, which is an area where we are working with materials developers to improve.

AWWS_PackagingInnovationsLab_Skrobecki_ 41.jpg
Examples of biopolyester-material product applications.

In Europe, we successfully trialed biopolyester prep bags at three Amazon fulfillment centers near Milan, Italy. The majority of associates reported that the biopolyester bags were just as easy to use as conventional plastic bags, with no impact on operational efficiency. Similarly, in Valencia, Spain, we tested biopolyester bags for grocery delivery through Amazon Fresh. This trial actually showed improvements in quality metrics, including reduced rates of damaged and missing items compared to conventional packaging.

These trials demonstrate that biopolyester materials can effectively replace conventional plastics in many applications while delighting customers and enabling continued operational excellence. The data and findings from these trials are helping build confidence across the industry around these new materials, which is crucial for driving broader adoption to replace conventional plastics.

Related content
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.

Today, we cannot yet recycle these materials at scale, so composting is the interim end-of-life option. However, as EsterCycle scales, and as Glacier enables more materials recovery facilities to sort a range of different polyesters, from PET to PLA to new PHAs, we envision a future where these materials are widely accepted in household recycling programs, making it easy for our customers to recycle these materials.

Building a new, circular value chain for plastics is a complex challenge that requires innovation at multiple levels — from developing new materials and recycling technologies to creating the infrastructure that will enable these materials to be collected and processed at scale. Through our work with partners like NREL, Glacier, and Novamont, we're demonstrating that this transformation is possible.

While there is still much work to be done, we are encouraged by the progress we've made with our partners. We are excited that by continuing to invest in research, support innovative startups, and collaborate across the value chain, we are at the forefront of a more sustainable future for plastics.

Research areas

Related content

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