Careers

About Amazon Advertising: Amazon Advertising operates at the intersection of eCommerce and advertising, offering a rich array of digital display advertising solutions with the goal of helping our customers find and discover anything they want to buy. We help advertisers of all types to reach Amazon customers on Amazon.com, across our other owned and operated sites, on other high quality sites across the web, and on millions of mobile devices. We start with the customer and work backwards in everything we do, including advertising. If you’re interested in joining a rapidly growing team working to build a unique, world-class advertising group with a relentless focus on the customer, you’ve come to the right place. About our team: SPB Brand Identity Team is on a mission to make Amazon the best in class destination for all brand needs. Our team builds a centralized brand identity datastore responsible for creating brands, mapping advertisers, products, and ads to brands. This enables our advertisers and customers to tell engaging brand stories through mappings generated and delivered by our team. We also enables customer-brand engagement enhancement through a UI allowing advertisers to self-manage and correct any mappings. Together these mappings are used by dozens of internal teams to generate measurement reports, brand intelligence, similar brands (i.e. substitutes), shopper/brand signals, etc. About this Role: We are looking for a passionate, talented Applied Scientist in the field of Natural Language Processing (NLP), Large Language Model (LLM), Ads Recommender Systems, Data Mining and Feature Engineering, and/or Information Retrieval, to invent and build scalable solutions for a state-of-the-art context-aware Brand Understanding. A successful candidate will have strong machine learning background and a desire to push the boundary of one or more of the above areas. The ideal candidate is expected to leading the effort of building key ML features, contribute to the collaborative and innovative spirit within the team, and bring cutting-edge applied research to raise the bar within the team.

Amazon is looking for an outstanding Senior Economist to help build next generation selection/assortment systems. On the Specialized Selection team within the Supply Chain Optimization Technologies (SCOT) organization, we own the selection to determine which products Amazon offers in our fastest delivery programs. We build tools and systems that enable our partners and business owners to scale themselves by leveraging our problem domain expertise, focusing instead on introspecting our outputs and iteratively helping us improve our ML models rather than hand-managing their assortment. We partner closely with our business stakeholders as we work to develop state-of-the-art, scalable, automated selection. Our team is highly cross-functional and employs a wide array of scientific tools and techniques to solve key challenges, including supervised and unsupervised machine learning, non-convex optimization, causal inference, natural language processing, linear programming, reinforcement learning, and other forecast algorithms. Some critical research areas in our space include modeling substitutability between similar products, incorporating basket awareness and complementarity-aware logic, measuring speed sensitivity of products, modeling network capacity constraints, and supply and demand forecasting. We're looking for a candidate with a background in experiment design and causal analysis to lead studies related to selection and speed. Potential projects include understanding the short-term and long-term customer impact of assortment changes across different speed. As an Senior Economist, you'll build econometric models using our world-class data systems and apply economic theory to solve business problems in a fast-moving environment. You will work with software engineers, product managers, and business teams to understand the business problems and requirements, distill that understanding to crisply define the problem, and design and develop innovative solutions to address them. To be successful in this role, you'll need to communicate effectively with product and tech teams, and translate data-driven findings into actionable insights. You'll thrive if you enjoy tackling ambiguous challenges using the economics toolkit and identifying and solving problems at scale. We have a supportive, fast-paced team culture, and we prioritize learning, growth, and helping each other continuously raise the bar. Key job responsibilities - Lead data-driven econometric studies to create future business opportunities - Consult with stakeholders in Selection and other teams to help solve existing business challenges - Independently identify and pursue new opportunities to leverage economic insights - Advise senior leaders and collaborate with other scientists to drive innovation - Support innovative delivery program growth worldwide - Write business and technical documents communicating business context, methods, and results to business leadership and other scientists - Serve as a technical lead and mentor for junior scientists, ensuring a high science bar - Serve as a technical reviewer for our team and related teams, including document and code reviews

Are you excited about developing cutting-edge generative AI, large language models (LLMs), and foundation models? Are you looking for opportunities to build and deploy them on real-world problems at a truly vast scale with global impact? As part of AFT (Amazon Fulfillment Technologies) AI, a group of over 50 scientists and engineers, we are on a mission to build a new generation of dynamic end-to-end prediction models (and agents) for our warehouses. These models will be able to understand and make use of petabytes of human-centered as well as process information from our warehouse systems and robotic work cells, and learn to perceive and act to further improve our world-class customer experience – at Amazon scale. We are looking for a Senior Manager of Applied Science who will help us build next-level solutions in a full warehouse with the help of generative AI, graph neural networks, and LLMs. Together, we will be pushing beyond the state of the art in simulation and optimization of one of the most complex systems in the world: Amazon's Fulfillment Network. Key job responsibilities In this role, you will manage a talented team of scientists to to build large-scale GenAI models that will be able to understand and predict the state and future of our buildings, network, and orders. You will face a high level of research ambiguity and problems that require creative, ambitious, and inventive solutions. You will lead a team of scientists to solve cutting-edge problems going beyond the published state of the art that will drive transformative change on a truly global scale. You will collaborate with teams of engineers to leverage solutions in production. You will lead the vision and implementation and communicate both to higher level leadership at Amazon. If you thrive in a dynamic environment and are passionate about pushing the boundaries of generative AI, LLMs, and automated fulfillment solutions, we want to hear from you. About the team Amazon Fulfillment Technologies (AFT) powers Amazon’s global fulfillment network. We invent and deliver software, hardware, and data science solutions that orchestrate processes, robots, machines, and people. We harmonize the physical and virtual world so Amazon customers can get what they want, when they want it. The AFT AI team has deep expertise developing cutting edge AI solutions at scale and successfully applying them to business problems in the Amazon Fulfillment Network. These solutions typically utilize machine learning and computer vision techniques, applied to text, sequences of events, images or video from existing or new hardware. We influence each stage of innovation from inception to deployment, developing a research plan, creating and testing prototype solutions, and shepherding the production versions to launch.

Brand Stores (such as www.amazon.com/lego) are a core product offering in the Amazon Advertising portfolio. The brand’s store is their dedicated place on Amazon to differentiate, grow sales, and build loyalty with millions of shoppers. Our mission is to empower brands of all sizes to tell their story in their own unique voice to consumers. We help brands create engaging shopping experiences that assist shoppers in discovering and evaluating them as part of purchase decisions. We succeed when we are both useful to shoppers and when brands can attract and retain shopper’s attention using our products. A cool case study on brand stores can be found here: https://advertising.amazon.com/library/case-studies/nespresso-brand-store-increases-shopper-engagement. We are looking for an Applied Scientist to lead the generation of data driven insights that bring long term value to brands, as well as the idealization and creation of ranking models for brand content. In this role you will influence our team’s science and business strategy with your analyses. You will be expected to identify and solve ambiguous problems and science deficiencies, and to provide informed solutions based on state of the art machine learning research. Why you will love this opportunity: Amazon is investing heavily in building a world-class advertising business. This team collaborate closely with other advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate. Impact and Career Growth: You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. Team video https://youtu.be/zD_6Lzw8raE #adpt-brand-shopping-experiences-science Key job responsibilities As an Applied Scientist on this team, you will: - Be the technical leader in Machine Learning; lead efforts within this team and across other teams. - Perform hands-on analysis and modeling of enormous data sets to develop insights that increase traffic monetization and merchandise sales, without compromising the shopper experience. - Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity. - Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models. - Run A/B experiments, gather data, and perform statistical analysis. - Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving. - Research new and innovative machine learning approaches. About the team The Brand Shopping Experience Team (BSX) develops and deploys into production Machine Learning Algorithms that quantify relevance, select and organize Brands’ pieces of content in different placements in Amazon.com. BSX's goal is to create engaging and enjoyable shopping experiences that incentivize Brand discovery and that foster Brand-Customer relationships.

The Alexa Customer Journeys team is seeking a Language Data Scientist with experience in the field of Natural Language Processing, Machine Learning, or Large Language Models, as well as expertise in handling large data sets and strong analytical skills. You will play a critical role in innovative projects by driving design of Alexa features. The key responsibilities are to generate high-quality data and to run and evaluate experiments, which involves prompt engineering our Large Language Model for API delivery. You will work closely with engineers, scientists, and program managers to ensure we're providing the best Alexa experience for millions of our customers. As a Language Data Scientist, you will start by diving deep into a couple of critical projects across Alexa experiences . You will collaborate with fellow Language Data Scientists, Program Managers, and stakeholders in science, engineering, and product teams to understand the role data plays in developing data sets and exemplars that meet customer needs. You will analyze and automate processes for collecting and annotating LLM inputs and outputs to assess data quality and measurement. You will apply state-of-the-art Generative AI techniques to analyze how well our data represents human language and run experiments to gauge downstream interactions. You will work collaboratively with other Language Data Scientists to design and implement principled strategies for data optimization. Key job responsibilities - Collaborate with scientists and software engineers to help design APIs and evaluate performance of LLM's - Produce and manipulate different types of language data, analyze and provide efficient solutions - Design and lead a data collection; define scope and target, provide a guideline and training, guide teams cross sites to meet the quality bar, and run evaluation of data for hand off - Engineer prompts to guide generative AI to produce desired outputs in context - Automate operations and perform data analysis using Python or other scripting language - Advocate strict adherence to annotation guidelines - Test and deploy changes to Alexa's language understanding codebase - Identify and solve production issues that are impacting the Alexa customer experience - Collaborate with other linguists, scientists, and designers in creating optimal solutions to elevate the customer experience - Own the customer-facing machine learning and deterministic models for a specific domain of features - Use modeling tools to bootstrap and test new functionalities

The Amazon Web Services (AWS) Center for Quantum Computing in Pasadena, CA, is looking to hire a Research Scientist specializing the design of microwave components for cryogenic environments. Working alongside other scientists and engineers, you will design and validate hardware performing microwave signal conditioning at cryogenic temperatures for AWS quantum processors. Candidates must have a background in both microwave theory and implementation. Working effectively within a cross-functional team environment is critical. The ideal candidate will have a proven track record of hardware development from requirements development to validation. Key job responsibilities Our scientists and engineers collaborate across diverse teams and projects to offer state of the art, cost effective solutions for the signal conditioning of AWS quantum processor systems at cryogenic temperatures. You’ll bring a passion for innovation, collaboration, and mentoring to: Solve layered technical problems across our cryogenic signal chain. Develop requirements with key system stakeholders, including quantum device, test and measurement, cryogenic hardware, and theory teams. Design, implement, test, deploy, and maintain innovative solutions that meet both performance and cost metrics. Research enabling technologies necessary for AWS to produce commercially viable quantum computers. A day in the life As you design and implement cryogenic microwave signal conditioning solutions, from requirements definition to deployment, you will also: Participate in requirements, design, and test reviews and communicate with internal stakeholders. Work cross-functionally to help drive decisions using your unique technical background and skill set. Refine and define standards and processes for operational excellence. Work in a high-paced, startup-like environment where you are provided the resources to innovate quickly. About the team 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.

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! Our Prime Air Drone Vehicle Design and Test team within Flight Sciences is looking for an outstanding engineer to help us rapidly configure, design, analyze, prototype, and test innovative drone vehicles. You’ll be responsible for assessing the Aerodynamics, Performance, and Stability & Control characteristics of vehicle designs. You’ll help build and utilize our suite of Multi-disciplinary Optimization (MDO) tools. You’ll explore new and novel drone vehicle conceptual designs in both focused and wide open design spaces, with the ultimate goal of meeting our customer requirements. You’ll have the opportunity to prototype vehicle designs and support wind tunnel and other testing of vehicle designs. You will directly support the Office of the Chief Program Engineer, and work closely across all vehicle subsystem teams to ensure integrated designs that meet performance, reliability, operability, manufacturing, and cost requirements. About the team Our Flight Sciences Vehicle Design & Test organization includes teams that span the following disciplines: Aerodynamics, Performance, Stability & Control, Configuration & Spatial Integration, Loads, Structures, Mass Properties, Multi-disciplinary Optimization (MDO), Wind Tunnel Testing, Noise Testing, Flight Test Instrumentation, and Rapid Prototyping.

Do you want to revolutionize machine learning for edge devices? Join our team developing cutting-edge compression algorithms that enable AI models to run efficiently on resource-constrained hardware. Our work is transforming the way Amazon customers interact with our devices, creating novel experiences that push the boundaries of what's possible with AI. About the role: As an Applied Scientist on the Edge AI & ML team, you will be at the forefront of innovation, working on technology that directly impacts millions of Amazon customers. Our team is pioneering new approaches that achieve an order of magnitude higher compression rates compared to existing methods. You'll work on challenging problems at the intersection of deep learning, optimization, and systems. By optimizing ML models for edge deployment, we're bringing advanced AI closer to our customers, enhancing privacy, reducing latency, and enabling new features that were previously impossible. Your work will: - Power the next generation of Amazon devices with efficient, on-device AI - Enable novel customer experiences that respond in real-time, even without internet connectivity - Push the boundaries of what's possible with edge computing and machine learning Key job responsibilities As an Applied Scientist on the Edge AI ML team, you will: - Develop and implement novel algorithms for compressing and optimizing deep learning models for edge devices - Conduct experiments to evaluate and benchmark model performance across various hardware platforms - Collaborate with product teams to integrate our technology into Amazon devices and services - Innovate on techniques to achieve state-of-the-art efficiency in AI model deployment - Explore and adapt emerging ML architectures (e.g., transformers, neural architecture search) for edge computing - Investigate hardware-aware ML techniques to tailor models for specific edge devices About the team Our team is at the forefront of enabling AI capabilities on edge devices. We offer: - The opportunity to work on cutting-edge ML technologies with real-world impact - Collaboration with world-class researchers and engineers - A culture of innovation that encourages new ideas and approaches - The scale and resources of Amazon to tackle ambitious technical challenges

Come build the future of entertainment with us. Are you interested in shaping the future of movies and television? Do you want to define the next generation of how and what Amazon customers are watching? Prime Video is a premium streaming service that offers customers a vast collection of TV shows and movies - all with the ease of finding what they love to watch in one place. We offer customers thousands of popular movies and TV shows including Amazon Originals and exclusive licensed content to exciting live sports events. We also offer our members the opportunity to subscribe to add-on channels which they can cancel at anytime and to rent or buy new release movies and TV box sets on the Prime Video Store. Prime Video is a fast-paced, growth business - available in over 200 countries and territories worldwide. The team works in a dynamic environment where innovating on behalf of our customers is at the heart of everything we do. If this sounds exciting to you, please read on. The Insights team is looking for an Applied Scientist for our London office experienced in generative AI and large models. This is a hands-on role with Prime Video wide impact working with development teams across the UK, India, and the US. This greenfield project will deliver features that reduce the operational load for internal Prime Video builders and for this, you will need to develop personalized recommendations for their services. You will lead the design of machine learning models that scale to very large quantities of data across multiple dimensions. You will embody scientific rigor, designing and executing experiments to demonstrate the technical effectiveness and business value of your methods. You will work alongside other scientists and engineering teams to deliver your research into production systems. Successful candidates will have strong technical ability, excellent teamwork and communication skills, and a strong motivation to deliver customer value from their research. Our position offers exceptional opportunities for every candidate to grow their technical and non-technical skills and make a global impact immediately. Key job responsibilities - Develop machine learning algorithms for high-scale recommendations problems. - Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both quantitative analysis and business judgement. - Collaborate with software engineers to integrate successful experimental results into Prime Video wide processes. - Communicate results and insights to both technical and non-technical audiences, including through presentations and written reports. About the team Our team owns the Prime Video observability features for development teams. We consume PBs of logs daily which feed into multiple observability features focussed on reducing the customer impact time. In 2025, we are expanding our remit to consume data from more sources to provide more holistic observability for our development teams.

This is a unique opportunity to build technology and science that millions of people will use every day. Are you excited about working on large scale Natural Language Processing (NLP), Machine Learning (ML), and Large Language Models (LLM)? We are embarking on a multi-year journey to improve the shopping experience for customers using Alexa globally. In 2024, we started building all Shopping experiences leveraging LLMs in the US. We create customer-focused solutions and technologies that makes shopping delightful and effortless for our customers. Our goal is to understand what customers are looking for in whatever language happens to be their choice at the moment and help them find what they need in Amazon's vast catalog of billions of products. We are seeking an Applied Scientist to lead a new, greenfield initiative that shapes the arc of invention with Machine Learning and Large Language Models. Your deliverables will directly impact executive leadership team goals and shape the future of shopping experiences with Alexa. We’re working to improve shopping on Amazon using the conversational capabilities of LLMs, and are searching for pioneers who are passionate about technology, innovation, and customer experience, and are ready to make a lasting impact on the industry. You'll be working with talented scientists, engineers, across the breadth of Amazon Shopping and AGI to innovate on behalf of our customers. If you're fired up about being part of a dynamic, driven team, then this is your moment to join us on this exciting journey!