Careers

The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through cutting-edge 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 - Define and lead science initiatives from problem framing through production deployment in a high-ambiguity environment - Develop and deploy models spanning computer vision, language, and search and retrieval that operate on multimodal inputs at scale - Design and analyze large-scale online experiments to measure impact on shopper and advertiser outcomes - Collaborate with engineering, product, and design to ship science into production A day in the life As an Applied Scientist on the Sponsored Videos team, you will tackle problems at the intersection of computer vision, generative AI, search and retrieval, and personalization. You'll own the full science lifecycle from research and experimentation through online testing and production deployment, working closely with engineering, product, and design partners to bring ideas to market. You should be comfortable working with multimodal signals, building models that operate at scale, and measuring impact through rigorous experimentation. Your work will directly influence the experience of hundreds of millions of shoppers and the outcomes of tens of thousands of advertisers. About the team The Sponsored Videos team within Sponsored Products and Brands develops the science and systems behind video advertising experiences that connect advertisers and shoppers across Amazon. We are on a mission to make Amazon the best-in-class destination for shoppers to discover, engage with, and build affinity with brands through videos.

Are you excited about building at the intersection of enterprise AI and customer experience? Are you passionate about applying science to real customer problems? Do you want your work shaped by real-world conditions and validated through customer deployments? The Alexa Enterprise team is looking for a passionate, talented, and inventive Senior Applied Scientist with a strong background in speech and audio machine learning who thrives in a startup-style environment. In this role, you'll set scientific direction and lead the development of techniques to improve speech-to-text accuracy for domain-specific use cases and optimize the performance and latency of end-to-end audio pipelines. You'll lead work across model evaluation and selection, fine-tuning, data and evaluation strategies, and real-time inference optimization. You'll partner closely with software engineers to turn scientific advances into production capabilities, while working with enterprise customers to understand how speech and audio systems perform in their environments. You'll turn improvements inspired by one customer's needs into capabilities that serve many, while influencing teams around a shared scientific vision. We're a small, fast-moving team building AI-powered solutions at the intersection of Alexa AI capabilities and AWS cloud services. Our customers span healthcare, energy, retail, and insurance, and they're deploying in environments where the technical challenges are real and the feedback loops are immediate. Key job responsibilities - Set the scientific direction for improving speech-to-text accuracy across domain-specific use cases and real-world operating conditions - Lead the evaluation, selection, adaptation, and fine-tuning of speech and audio models based on accuracy, latency, cost, reliability, and deployment constraints - Drive improvements to the performance and latency of end-to-end audio pipelines, from signal processing and streaming through inference and transcription - Define datasets, benchmarks, experiments, and evaluation methodologies that reflect customer use cases - Lead the optimization of models and inference pipelines for reliable, real-time operation - Work directly with enterprise customers to understand quality challenges, validate scientific improvements, and identify opportunities for broader platform capabilities - Turn patterns from customer engagements into reusable models, evaluation methods, and scientific capabilities that scale across customers and industries - Influence and collaborate with software engineering and partner teams to productionize models, measure their performance, and continuously improve deployed systems - Write scientific and technical documents, lead reviews, and communicate experimental results and trade-offs to engineering, product, and business leaders - Mentor Applied Scientists and engineers, participate in hiring, and raise the team's science and engineering standards About the team The Alexa Enterprise team builds AI-powered solutions for businesses. We work with enterprise customers across healthcare, energy, retail, and insurance to deploy solutions that transform operations. Our team operates at the intersection of Alexa AI capabilities and AWS cloud services, partnering closely with AWS sales, product, and specialist teams to deliver customer outcomes. Our work brings together applied AI, speech and audio science, real-time systems, and cloud services. Senior Applied Scientists on the team have real ownership, from identifying and framing customer problems through setting scientific direction, experimentation, production integration, and measurement of customer impact. This is an opportunity to lead meaningful scientific work while helping shape a platform in its early stages.

Are you excited about building at the intersection of enterprise AI and customer experience? Are you passionate about applying science to real customer problems? Do you want your work shaped by real-world conditions and validated through customer deployments? The Alexa Enterprise team is looking for a passionate, talented, and inventive Senior Applied Scientist with a strong background in speech and audio machine learning who thrives in a startup-style environment. In this role, you'll set scientific direction and lead the development of techniques to improve speech-to-text accuracy for domain-specific use cases and optimize the performance and latency of end-to-end audio pipelines. You'll lead work across model evaluation and selection, fine-tuning, data and evaluation strategies, and real-time inference optimization. You'll partner closely with software engineers to turn scientific advances into production capabilities, while working with enterprise customers to understand how speech and audio systems perform in their environments. You'll turn improvements inspired by one customer's needs into capabilities that serve many, while influencing teams around a shared scientific vision. We're a small, fast-moving team building AI-powered solutions at the intersection of Alexa AI capabilities and AWS cloud services. Our customers span healthcare, energy, retail, and insurance, and they're deploying in environments where the technical challenges are real and the feedback loops are immediate. Key job responsibilities - Set the scientific direction for improving speech-to-text accuracy across domain-specific use cases and real-world operating conditions - Lead the evaluation, selection, adaptation, and fine-tuning of speech and audio models based on accuracy, latency, cost, reliability, and deployment constraints - Drive improvements to the performance and latency of end-to-end audio pipelines, from signal processing and streaming through inference and transcription - Define datasets, benchmarks, experiments, and evaluation methodologies that reflect customer use cases - Lead the optimization of models and inference pipelines for reliable, real-time operation - Work directly with enterprise customers to understand quality challenges, validate scientific improvements, and identify opportunities for broader platform capabilities - Turn patterns from customer engagements into reusable models, evaluation methods, and scientific capabilities that scale across customers and industries - Influence and collaborate with software engineering and partner teams to productionize models, measure their performance, and continuously improve deployed systems - Write scientific and technical documents, lead reviews, and communicate experimental results and trade-offs to engineering, product, and business leaders - Mentor Applied Scientists and engineers, participate in hiring, and raise the team's science and engineering standards About the team The Alexa Enterprise team builds AI-powered solutions for businesses. We work with enterprise customers across healthcare, energy, retail, and insurance to deploy solutions that transform operations. Our team operates at the intersection of Alexa AI capabilities and AWS cloud services, partnering closely with AWS sales, product, and specialist teams to deliver customer outcomes. Our work brings together applied AI, speech and audio science, real-time systems, and cloud services. Senior Applied Scientists on the team have real ownership, from identifying and framing customer problems through setting scientific direction, experimentation, production integration, and measurement of customer impact. This is an opportunity to lead meaningful scientific work while helping shape a platform in its early stages.

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. We are looking for a Senior Applied Scientist to build the science that helps Amazon's advertisers grow — with a focus on Cross Border Sellers who face distinct barriers as they scale across multiple marketplaces, and this role is about understanding those pain points deeply and removing them: building intelligent, autonomous solutions that simplify advertising, act efficiently on the advertiser's behalf, and let advertisers accelerate their growth and success. We expect a Senior Scientist to think innovatively about how to reduce the effort and complexity of advertising for these advertisers. Working backwards from their needs — spanning hands-off sellers and global brands with cross-marketplace operations — you will take the lead on medium-to-large, ambiguous problems where neither the problem nor the solution is well defined, invent new methods, validate them through rigorous experimentation, and deliver customer-facing products with measurable business impact. This role combines science depth, product focus, and hands-on engineering: you will raise the science bar, build consensus on approach across product and engineering partners, and mentor scientists and engineers while remaining deeply hands-on with the hardest technical problems. Key job responsibilities As a Senior Applied Scientist on this team you will: - Understand the pain points of Cross border advertisers as they scale across marketplaces, and build science-driven solutions that remove barriers and accelerate their growth and success. - Build agentic and ML systems that autonomously create, structure, and manage ad campaigns on advertisers' behalf, encoding auction and marketplace dynamics (bidding, budget pacing, targeting decisions) while balancing advertiser ROI, shopper experience, and marketplace health. - Innovate on new, simpler ways to advertise powered by GenAI, and push the frontier of existing autonomous programs (e.g., auto-targeting, global lift-and-shift) while proposing and prototyping the next generation of campaign automation. - Develop models across the campaign lifecycle — opportunity discovery, ranking, ad-readiness and demand prediction, and bid/budget optimization — and apply the right approach for each problem, from classical ML to LLM/reasoning methods. - Define and curate the datasets and signals needed to train and evaluate these systems — advertiser and campaign data, cross-marketplace performance, auction and bid/budget signals, impressions, clicks, conversions, and search-term/keyword performance. - Own core parts of the agentic architecture — planning, tool use and integration (e.g., MCP), reasoning frameworks (e.g., ReAct, CoT/ToT), and model customization — and define evaluation and safety methodology so that automated decisions are reliable and trustworthy. - Stay deeply hands-on: write production-quality, critical-path code and build core components that take systems from prototype to launch on large-scale pipelines (Spark/EMR, Airflow) and online serving. - Raise the science bar: mentor scientists and engineers, review designs and experiment plans, and communicate results and tradeoffs clearly to technical and business leaders. About the team Autonomous SP drives growth and simplifies advertising for Amazon's hands-off advertisers by creating and enhancing autonomous campaign solutions. We lead existing successful programs, including auto-targeting and global lift-and-shift, and continually innovate by building new, simpler campaign constructs powered by GenAI to act efficiently on advertisers' behalf. Cross-border Seller Experience (CBSX) focuses on developing targeted solutions for domestic and global advertisers with multi-marketplace operations. By understanding and addressing their unique Seller Central needs, we optimize for cross-marketplace efficiency, improved performance, and streamlined advertising experiences. Our team operates horizontally, delivering impactful solutions that benefit both hands-on and hands-off advertisers globally. Together, we sit within Sponsored Products and Brands, which is re-imagining advertising through the latest generative AI — building responsible, intelligent systems that balance the needs of advertisers, the shopping experience, and marketplace health.

Amazon Ads is a multi-billion dollar global business that delivers advertising experiences across Amazon's owned-and-operated properties (including Prime Video, Twitch, Fire TV, and Amazon.com), third-party publisher networks, and emerging channels like generative AI-powered shopping experiences. As one of the fastest-growing segments of Amazon, we operate at unprecedented scale across desktop, mobile, connected TV, and emerging surfaces. Within Amazon Ads, Traffic Quality is a critical pillar of advertiser trust and marketplace integrity. Our mission is to build advanced capabilities that work at petabyte scale to detect sophisticated invalid traffic (IVT) which includes sophisticated non-human traffic, bot networks, and fraudulent engagement patterns across programmatic advertising. We are on a journey to establish Amazon Ads as an industry leader in traffic quality standards and transparency. Our research agenda focuses on staying ahead of adversarial actors through continuous innovation in detection methodologies, leveraging state-of-the-art techniques in deep learning and generative modeling, user behavior and multi-modal representation learning, anomaly detection, time-series analysis, and sparse labeling methods. We process billions of ad events daily, developing novel algorithms that balance precision and recall while operating under strict latency constraints. Our work directly protects hundreds of millions of dollars in advertiser spend annually while maintaining a seamless user experience. Key job responsibilities As an Applied Scientist II in Traffic Quality, you will solve inherently hard problems in advertising fraud detection using deep learning, self-supervised techniques, representation learning, and advanced clustering. You'll work on systems that process billions of ad impressions and clicks per day, using Amazon's cloud services including EC2, S3, EMR, Sagemaker, and RedShift. - Define and frame new research problems in fraud detection where neither problem nor solution is well-defined. - Invent and adapt new machine learning approaches, models, and algorithms to detect sophisticated invalid traffic. - Design and deploy production-quality ML components that directly impact advertiser trust and the business top-line. - Apply domain knowledge to perform broad data analysis as a precursor to modeling and build business insights. - Work with unstructured and massive datasets to deliver results. - Produce research reports meeting top-tier external publication standards. - Contribute to the scientific community through publications at peer-reviewed venues and reviewing research submissions. - Mentor and develop junior scientists on the team. About the team Here are a few papers published by the team: 1/ [Scaling Generative Pre-training for User Ad Activity Sequences. AdKDD 2023.](https://assets.amazon.science/b7/42/03be071743d5a57cb1656e6caa34/scaling-generative-pre-training-for-user-ad-activity-sequences.pdf) 2/ [SLIDR: Real-time Robot Detection On Online Ads, IAAI 2023, Deployed Highly Innovative Applications of AI Track (AAAI 2023)](https://assets.amazon.science/75/2f/3b7106b143f38f7f4d2806388ace/real-time-detection-of-robotic-traffic-in-online-advertising.pdf) 3/ [Self-supervised Representation Learning Across Sequential and Tabular Features Using Transformers, NeurIPS 2022, First Table Representation Learning Workshop](https://openreview.net/forum?id=wIIJlmr1Dsk)

SCOT's RoW Regional team is seeking an experienced and motivated Data Scientist to help optimize, enhance, and scale Supply Chain decision algorithms in countries beyond US/EU. The focus will be on enhancing and also building new solutions solving for forecasting, buying, placement and inventory health management issues in 10 stores. You will work closely with Product Managers Tech, BIEs, SDEs, Supply Chain Managers, and other Scientists across US and EU to build scalable, high insight- high impact products and own improvements to business outcomes within your area, enabling execution of WW and local solutions for next generation Supply Chain systems. You will leverage your expertise in modeling, maths, algorithms and more importantly AI to analyze diverse and large datasets to uncover insights and build working models that help minimize dependence on manual supply chain decisions within the vast landscape and selection in which Amazon operates. Areas of work would include: 1) Building OR, RL, Agentic AI based models for automated supply chain optimization decisions; integrating with the central tech solutions owned by SCOT WW, 2) Creating decision frameworks to choose between multiple models to solve for a given supply chain problem, 3) Build visibility, audit and decision frameworks that help operate complex and nuanced supply chains across 10 countries. Key job responsibilities You will be responsible for researching, experimenting and analyzing predictive and optimization models. You will work on ambiguous and complex business and research science problems with large opportunities. You are an analytical individual who is comfortable working with cross-functional teams and systems. Significantly AI Savvy. You must be a self-starter and be able to learn on the go. Excellent written and verbal communication skills are required as you will work very closely with diverse teams. Key job responsibilities - Interact with product managers to understand their business requirements and operational processes. - Frame business problems into scalable solutions. - Adapt existing and invent new techniques for solutions. - Be the proponent of using latest techniques in data science and leveraging AI to fasten experimentation and model launch. - Gather data required for analysis and model building. - Collaborate with product and engineering teams to design rigorous experiments to evaluate the impact of new features or algorithms. - Create and track accuracy and performance metrics. - Prototype models by using high-level modeling languages such as R or in software languages such as Python. - Familiarity with transforming prototypes to production is preferred. - Create, enhance, and maintain technical documentation. - Represent the team and contribute to science forums within Amazon About the team Have you ever ordered a product on Amazon and when that box with the smile arrived, wondered how it got to you so fast? Wondered where it came from and how much it cost Amazon? If so, Amazon’s Supply Chain Optimization Technology (SCOT) organization is for you. At SCOT, we solve deep technical problems and build innovative solutions in a fast-paced environment working with smart & passionate team members. (Learn more about SCOT: http://bit.ly/amazon-scot)

Amazon is seeking exceptional talent to help develop the next generation of advanced robotics systems that will transform automation at Amazon's scale. We're building revolutionary robotic systems that combine cutting-edge AI, sophisticated control systems, and advanced mechanical design to create adaptable automation solutions capable of working safely alongside humans in dynamic environments. This is a unique opportunity to shape the future of robotics and automation at an unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic dexterous manipulation, locomotion, and human-robot interaction. This role presents an opportunity to shape the future of robotics through innovative applications of deep learning and large language models. At Amazon we leverage advanced robotics, machine learning, and artificial intelligence to solve complex operational challenges at an unprecedented scale. Our fleet of robots operates across hundreds of facilities worldwide, working in sophisticated coordination to fulfill our mission of customer excellence. The ideal candidate will contribute to research that bridges the gap between theoretical advancement and practical implementation in robotics. You will be part of a team that's revolutionizing how robots learn, adapt, and interact with their environment. Join us in building the next generation of intelligent robotics systems that will transform the future of automation and human-robot collaboration. Key job responsibilities - Collaborate with simulation and robotics experts to translate physical modeling needs into robust, scalable, and maintainable simulation solutions. - Design and implement high-performance simulation modeling and tools for rigid and deformable body simulation. - Identify and optimize performance bottlenecks in simulation pipelines to support real-time and batch simulation workflows. - Help build validation and unit testing pipelines to ensure correctness and physical fidelity of simulation results. - Identify potential sources of sim-to-real gaps and propose modeling and numerical approximations to reduce them. - Stay current with the latest advances in numerical methods, parallel computing, and GPU architectures, and incorporate them into our tools.

robotics systems that will transform automation at Amazon's scale. We're building revolutionary robotic systems that combine cutting-edge AI, sophisticated control systems, and advanced mechanical design to create adaptable automation solutions capable of working safely alongside humans in dynamic environments. This is a unique opportunity to shape the future of robotics and automation at unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic manipulation, locomotion, and human-robot interaction. This role presents an opportunity to shape the future of robotics through innovative applications of deep learning and large language models. At Amazon Industrial Robotics we leverage advanced robotics, machine learning, and artificial intelligence to solve complex operational challenges at unprecedented scale. Our fleet of robots operates across hundreds of facilities worldwide, working in sophisticated coordination to fulfill our mission of customer excellence. We are pioneering the development of robotics foundation models that: Enable unprecedented generalization across diverse tasks Enable unprecedented robustness and reliability, industry-ready Integrate multi-modal learning capabilities (visual, tactile, linguistic) Accelerate skill acquisition through demonstration learning Enhance robotic perception and environmental understanding Streamline development processes through reusable capabilities The ideal candidate will contribute to research that bridges the gap between theoretical advancement and practical implementation in robotics. You will be part of a team that's revolutionizing how robots learn, adapt, and interact with their environment. Join us in building the next generation of intelligent robotics systems that will transform the future of automation and human-robot collaboration. As an Applied Science Manager in the Foundation Model team, you will build and lead a team that develops and improves machine learning systems that help robots perceive, reason, and act in real-world environments. You will set the technical direction for leveraging state-of-the-art models (open source and internal research), evaluating them on representative tasks, and adapting/optimizing them to meet robustness, safety, and performance needs. You will drive the capability roadmap and the evaluation strategy that defines “what the robot brain can do,” and you will sponsor targeted innovation when gaps remain. You’ll collaborate closely with research, controls, hardware, and product teams, and ensure the team’s outputs can be further customized and deployed by downstream teams on specific robot embodiments.

AWS Applied AI Solutions (AAIS) is building toward a future where every business innovates with Amazon AI teammates. To get there, we build AI solutions that improve human capabilities and transform entire business functions. We create end-to-end products that surprise and delight out-of-the-box, making complex things easy and hard things possible, with no cloud experience required. We start with customers who embrace the future and build bridges to meet the rest where they are. We pursue ambitious opportunities with conviction, and we are looking for builders who share that mindset. At AWS we use Artificial Intelligence to be able to identify every need of a customer across all AWS services before they have to tell us about it and help customers adopt best practices while architecting on the cloud. We are looking for a Senior Applied scientist who will function as a science leader and drive innovation with Gen AI to bring paradigm shift to how the business operates and build "best in the world" experience that customers will love! Some of the science challenges we work on include building Agentic AI systems for complex use cases such as optimizing customers' cloud architectures innovating optimization techniques for cost-efficiency in agentic workflows fine-tuning language models for domain specific use cases building scalable agentic evaluation systems designing continual learning systems that incorporate real-time customer and operational feedback to improve model performance over time and developing collaborative filtering approaches that surface personalized recommendations at scale. You will have an opportunity to lead invent and design technology that will directly impact every customer across all AWS services. We are building industry-leading technology that cuts across a wide range of ML techniques from Natural Language Processing to Deep Learning and Generative Artificial Intelligence. You will be a key driver in taking something from an idea to an experiment to a prototype and finally to a live production system. As a senior scientist on this team you will define the science vision and long-term research roadmap for your problem space. You will set technical and research direction and ensure our approaches remain at the frontier of what's possible. You will mentor junior scientists and engineers helping them grow their technical depth develop scientific rigor and navigate ambiguous problem spaces. You will raise the bar for the team through code reviews science experimentation reviews and by fostering a culture of experimentation and intellectual curiosity. Key job responsibilities • Deliver real world production systems at AWS scale. • Work closely with the business to understand the problem space identify the opportunities and formulate the problems. • Use machine learning data mining statistical techniques Generative AI and others to create actionable meaningful and scalable solutions for the business problems. • Analyze and extract relevant information from large amounts of data and derive useful insights. • Work with software engineering teams to deliver production systems with your ML models • Establish scalable efficient automated processes for large scale data analyses model development model validation and model implementation 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. About the team 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. 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. We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud. 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 and AmazeCon conferences, inspire us to never stop embracing our uniqueness. 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.

FBA Science seeks an Applied Scientist to invent and build optimization models and algorithms that improve how Amazon plans and places seller inventory across its worldwide fulfillment network. FBA moves the inventory of hundreds of thousands of sellers through a multi-echelon network of origin storage, national and regional distribution, and fulfillment centers — putting the right inventory in the right place, on time and at low cost. Operating this network is a constant stream of decisions: how much a seller should send, and where and when it should flow, all under scarce receiving and storage capacity. And these decisions are not ours to make alone — sellers choose what to send and how to respond to the options and incentives we offer, so we have to plan the network and shape seller behavior together. Solve it well and we drive out cost and speed up delivery, while making FBA the easiest way for a seller to grow their business. Our strategy is to make these decisions with science-driven technology, and because existing techniques rarely fit Amazon's scale and unique business needs, we invent new approaches and algorithms. As an Applied Scientist, you'll develop optimization models and algorithms across FBA's inventory planning and placement systems. Your role will initially focus on joint replenishment and placement decisions. Your models will impact business decisions worth billions of dollars and improve the experience of every FBA seller. Key job responsibilities - Own the development of the replenishment, placement, and transportation-planning algorithms that decide how a seller's inventory flows across Amazon's fulfillment network. - Design and implement large-scale optimization models and algorithms for complex inventory-planning problems, and the prediction and estimation layer they depend on. - Partner closely with Product Managers and engineers to define high-impact problems, translate ambiguous business challenges into well-scoped science initiatives, and deliver actionable, science-driven solutions. - Build and deploy science solutions into production pipelines, ensuring that models operate reliably at scale across a network serving hundreds of thousands of sellers. A day in the life You will own a science area with significant scope, impact, and high visibility, and your work will touch millions of products, hundreds of thousands of selling partners, and tens of millions of customers. You will be in the seller's critical path and you will be involved in every step, from idea generation and business analysis through research to the development and deployment of production-grade models. You will move between the optimization and the behavior. You are expected to make decisions about methodology, model architecture, and technology choices, and to strive for simplicity and demonstrate judgment backed by mathematical rigor. You will work closely with product managers, engineers, and fellow scientists, and collaborate with the broader science community across Amazon to broaden the horizon of your work. You will be entrepreneurial, wear many hats, and work in a fast-paced, high-energy, highly collaborative environment where we value people who deliver results, know their subject deeply, and are eager to learn new areas. About the team Sellers play a vital role in Amazon’s ecosystem, integral to our mission of offering the Earth’s largest selection, lowest prices, and fastest delivery speed. FBA is an optional service that enables third-party sellers to outsource order fulfillment to Amazon, and leverage Amazon’s world-class facilities to provide customers fast delivery promise. With commitment to taking on even more of the supply chain and operational complexities on behalf of our selling partners, Amazon now provides an end-to-end suite of supply chain services. This comprehensive solution empowers sellers to reliably transport products from manufacturing sites to customers worldwide. The FBA team is the core group in charge of warehousing, inventory management, fulfillment and pricing, and a diverse range of recommendation services for sellers, as well as building the internal resource management systems. We work to learn seller behavior, understand seller experience, recommend right actions to sellers, design seller policies and incentives, and develop science products and services that empower sellers to grow their businesses. To do so, we build and innovate science solutions that leverage the right tools across different fields including operations research, economics, machine learning, statistics, and data analytics. Our culture is centered on rapid prototyping, rigorous experimentation, and data-driven decision-making.