Careers

Amazon Advertising is one of Amazon's fastest growing businesses. Amazon's advertising portfolio helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day! The Creative X team within Amazon Advertising time aims to democratize access to high-quality creatives (audio, images, videos, text) by building AI-driven solutions for advertisers. To accomplish this, we are investing in understanding how best users can leverage Generative AI methods such as latent-diffusion models, large language models (LLM), generative audio (music and speech synthesis), computer vision (CV), reinforced learning (RL) and related. As an Applied Scientist you will be part of a close-knit team of other applied scientists and product managers, UX and engineers who are highly collaborative and at the top of their respective fields. We are looking for talented Applied Scientists who are adept at a variety of skills, especially at the Agentic AI, development and use of multi-modal Generative AI and can use state-of-the-art generative music and audio, computer vision, latent diffusion or related foundational models that will accelerate our plans to generate high-quality creatives on behalf of advertisers. Every member of the team is expected to build customer (advertiser) facing features, contribute to the collaborative spirit within the team, publish, patent, and bring SOTA research to raise the bar within the team. As an Applied Scientist on this team, you will: Drive the invention and development of novel AI Agent architectures and video/image/audio generation models in advertising. Strong expertise in AI agent evaluation methodologies and complex task decomposition; hands-on experience with AI-powered video generation pipelines; Deep knowledge in LLM/VLM fine tuning and reinforcement learning. Work closely and integrate end-to-end proof-of-concept Machine Learning projects that have a high degree of ambiguity, scale and complexity. Build interface-oriented systems that use 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. Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving. Mentor and help recruit Applied Scientists to the team. Present results and explain methods to senior leadership. Willingness to publish research at internal and external top scientific venues. Write and pursue IP submissions. Key job responsibilities This role is focused on developing new multi-modal Generative AI methods to augment generative imagery and videos. You will develop AI agent, new multi-modal paradigms, models, datasets that will be at the core of advertising-facing tools that we are launching. You may also work on development of ML and GenAI models suitable for advertising. You will conduct literature reviews to stay on the SOTA of the field. You will regularly engage with product managers, UX designers and engineers who will partner with you to productize your work. For reference see our products: Enhanced Video Generator, Creative Agent and Creative Studio. A day in the life On a day-to-day basis, you will be doing your independent research and work to develop models, you will participate in sprint planning, collaborative sessions with your peers, and demo new models and share results with peers, other partner teams and leadership. About the team The team is a dynamic team of applied scientists, UX researchers, engineers and product leaders. We reside in the Creative X organization, which focuses on creating products for advertisers that will improve the quality of the creatives within Amazon Ads. We are open to hiring candidates to work out of one of the following locations: USA (Seattle).

We are seeking a Principal Applied Scientist to lead research and development in automated reasoning, formal verification, and program analysis. You will drive innovation in making formal methods practical and accessible for real-world systems at cloud scale. Key job responsibilities - Lead research initiatives in automated reasoning, formal verification, SMT solving, model checking, or program analysis - Design and implement novel algorithms and techniques that advance the state of the art - Mentor and guide applied scientists, research scientists, and engineers - Collaborate with product teams to transition research into production systems - Define technical vision and strategy for automated reasoning initiatives - Represent AWS in the academic and research community - Drive cross-organizational impact through technical leadership About the team The Automated Reasoning Group at AWS develops and applies cutting-edge formal methods and automated reasoning techniques to ensure the security, reliability, and correctness of AWS services and customer applications. Our work innovates tools and services to perform verification at scale and apply them to build safe and secure systems at AWS. We are also pioneering the use of formal verification and automated reasoning to develop agentic systems, ensuring AI agents operate within defined safety boundaries.

We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to apply their causal inference skillsets to solve real world problems. The intern will work in the area of stores selection and develop models to improve our selection decisions. Our PhD Economist Internship Program offers hands-on experience in applied economics, supported by mentorship, structured feedback, and professional development. Interns work on real business and research problems, building skills that prepare them for full-time economist roles at Amazon and beyond. You will learn how to build data sets and perform applied econometric analysis collaborating with economists, scientists, and product managers. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with placement. These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis.

The Stores Economics and Science (SEAS) team uses Economics, Statistics, and Machine Learning to understand and design the complex economy of Amazon’s network of buyers and sellers. We are an interdisciplinary team, committed to use of cutting edge technology and leveraging the strengths of engineers and scientists to build solutions for some of the toughest business problems at Amazon. We are looking for an outstanding science manager who is able to provide structure around complex business problems, work with machine learning scientists to estimate and validate their models on large scale data, and who can help business and tech partners turn the results of their analysis into policies, programs, and actions that have a major impact on Amazon’s business. We are looking for creative thinkers who can combine a strong economic toolbox with a desire to learn from others, and who know how to execute and deliver on big ideas. Experience in applied economic analysis is essential, and you should be familiar with modern tools for data science and business analysis.

The Alexa AI Domains is seeking a passionate, talented, and resourceful Senior Applied Scientist to invent and build scalable solutions for sate-of-the-art conversational AI. You will be working on advancing technologies in the fields of LLM, Artificial Intelligence (AI), Natural Language Processing (NLP) and/or Information Retrieval. As part of this role, you will collaborate with talented peers, have significant influence on our overall strategy as you guide and mentor Applied Scientists to create innovative and scalable solutions that touch millions of Alexa customers. Creating reliable, scalable, and high performance products requires exceptional technical expertise, a sound understanding of the fundamentals of AI, and practical experience building large-scale machine learning systems. The ideal candidate will be a self-starter who can dive into a project with limited guidance and is able to design and implement inventive, simple solutions to complex problems. They will be passionate about new technologies and have a track record of delivering valuable software features and products in a fast-paced, highly iterative environment. A commitment to team work, hustle, and strong communication skills (to both business and technical partners) are absolute requirements. Join us in our mission to shape the space of Generative AI and provide unparalleled experiences for our customers. Key job responsibilities • Define the science roadmap and advance core science primitives for conversation modelling, content generation, and automated quality assurance via state-of-the-art computer vision, machine learning, and generative AI • Architect agentic systems, making high-judgment trade-offs across audio/text/visual quality, relevance, latency, cost, and long-term extensibility • Establish evaluation frameworks, metrics, and success criteria for the team's scientific initiatives, institutionalizing rigorous validation across customer touch points • Own end-to-end delivery of complex, ambiguous research initiatives from problem formulation through experimentation to production deployment, with minimal guidance • Identify whitespace opportunities by staying at the forefront of AI/ML advances and translating them into actionable research directions with clear customer and business impact • Drive development and deployment of scalable agentic systems for conversation understanding and generation, ensuring architectural decisions support long-term platform evolution • Set and continuously raise the scientific and engineering bar across the team • Tackle the team's most complex technical problems while maintaining practical focus on customer value and solution generalizability • Advance the team's scientific reputation through high-impact publications and presentations at top-tier internal and external venues, and generate intellectual property through patents About the team The AIDo (AI Domains) org is part of Alexa AI VP and Devices and Services SVP organizations. Our vision is to build an ecosystem of AI systems and services that elevate the core LLM model performance across endpoints, modalities, and locales. We are the horizontal Science and Engineering team that empowers Domains and Horizontal CX owners with transformative solutions that enable rapid, efficient scaling. AIDo represents a sophisticated global organization that spans multiple international locations including the US (Boston, Seattle), Germany, Italy, and India. The team's core mission is to develop and maintain AI systems and services that enhance the performance of core LLM models across various endpoints, modalities, and locales.

Amazon Leo is an initiative to increase global broadband access through a constellation of 3,236 satellites in low Earth orbit (LEO). Its mission is to bring fast, affordable broadband to unserved and underserved communities around the world. Amazon Leo will help close the digital divide by delivering fast, affordable broadband to a wide range of customers, including consumers, businesses, government agencies, and other organizations operating in places without reliable connectivity. Do you get excited by aerospace, space exploration, and/or satellites? Do you want to help build solutions at Amazon Leo to transform the space industry? If so, then we would love to talk! Key job responsibilities Work cross-functionally with product, business development, and various technical teams (engineering, science, simulations, etc.) to execute on the long-term vision, strategy, and architecture for the science-based global demand forecast. Design and deliver modern, flexible, scalable solutions to integrate data from a variety of sources and systems (both internal and external) and develop Bandwidth Usage models at granular temporal and geographic grains, deployable to Leo traffic management systems. Work closely with the capacity planning science team to ensure that demand forecasts feed seamlessly into their systems to deliver continuous optimization of resources. Lead short and long terms technical roadmap definition efforts to deliver solutions that meet business needs in pre-launch, early-launch, and mature business phases. Synthesize and communicate insights and recommendations to audiences of varying levels of technical sophistication to drive change across Amazon Leo. Export Control Requirement: Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum. About the team The Amazon Leo Global Demand Planning team's mission is to map customer demand across space and time. We enable Amazon Leo's long-term success by delivering actionable insights and scientific forecasts across geographies and customer segments to empower long range planning, capacity simulations, business strategy, and hardware manufacturing recommendations through scalable tools and durable mechanisms.

Do you want a role with deep meaning and the ability to make a major impact? As part of Intelligent Talent Acquisition (ITA), you'll have the opportunity to reinvent the hiring process and deliver unprecedented scale, sophistication, and accuracy for Amazon Talent Acquisition operations. ITA is an industry-leading people science and technology organization made up of scientists, engineers, analysts, product professionals and more, all with the shared goal of connecting the right people to the right jobs in a way that is fair and precise. Last year we delivered over 6 million online candidate assessments, and helped Amazon deliver billions of packages around the world by making it possible to hire hundreds of thousands of workers in the right quantity, at the right location and at exactly the right time. You’ll work on state-of-the-art research, advanced software tools, new AI systems, and machine learning algorithms, leveraging Amazon's in-house tech stack to bring innovative solutions to life. Join ITA in using technologies to transform the hiring landscape and make a meaningful difference in people's lives. Together, we can solve the world's toughest hiring problems. Intelligent Talent Acquisition (ITA)is looking for an economist with expertise in applying causal inference, experimental design, and/or causal machine learning techniques to topics in labor or related applied economics. They will collaborate with business partners to define and deliver economic thinking that guide strategic decisions. They will work closely with data scientists, research scientists and engineers to estimate and validate their models on large scale data, and will help business partners turn the results of their analysis to business actions that have a major impact. Ideal candidates will own key inputs to all stages of research projects, including data requirements, model development, experimental design, and data analysis. They will be customer-centric, working closely with business partners to define key research questions, communicate scientific approaches and findings, listen to and incorporate partner feedback, and deliver successful solutions. Key job responsibilities The Economist will work with teammates (Data Scientists, Research Scientists (Industrial-Organizational Psychologists), Business Intelligence Engineers to apply economic methods to business problems. This might include identifying the appropriate research questions, writing code to implement a Difference-in-Differences (DiD) analysis, estimate a structural model, building a statistical / regression model or writing and presenting a document with findings to business leaders. Our economists also collaborate with partner teams throughout the process, from understanding their challenges, to developing a research agenda that will address those challenges, to help them implement solutions. A day in the life The Economist will work with teammates to apply economic methods to business problems. This might include identifying the appropriate research questions, writing code to implement the model, or writing and presenting a document with findings to business leaders. The economist will also conduct code and paper reviews, engage in science panel reviews and attend meetings to scope the work and/or present results. The economists will also manage and update their work through regular ASANA project updates.

RBS (Retail Business Services) Tech team works towards enhancing the customer experience (CX) and their trust in product data by providing technologies to find and fix Amazon CX defects at scale. Our platforms help in improving the CX in all phases of customer journey, including selection, discoverability & fulfilment, buying experience and post-buying experience (product quality and customer returns). The team also develops GenAI platforms for automation of Amazon Stores Operations. As a Sciences team in RBS Tech, we focus on foundational ML research and develop scalable state-of-the-art ML solutions to solve the problems covering customer experience (CX) and Selling partner experience (SPX). We work to solve problems related to multi-modal understanding (text and images), task automation through multi-modal LLM Agents, supervised and unsupervised techniques, multi-task learning, multi-label classification, aspect and topic extraction for Customer Anecdote Mining, image and text similarity and retrieval using NLP and Computer Vision for product groupings and identifying duplicate listings in product search results. Key job responsibilities As an Applied Scientist, you will be responsible to design and deploy scalable GenAI, NLP and Computer Vision solutions that will impact the content visible to millions of customer and solve key customer experience issues. You will develop novel LLM, deep learning and statistical techniques for task automation, text processing, image processing, pattern recognition, and anomaly detection problems. You will define the research and experiments strategy with an iterative execution approach to develop AI/ML models and progressively improve the results over time. You will partner with business and engineering teams to identify and solve large and significantly complex problems that require scientific innovation. You will help the team leverage your expertise, by coaching and mentoring. You will contribute to the professional development of colleagues, improving their technical knowledge and the engineering practices. You will independently as well as guide team to file for patents and/or publish research work where opportunities arise. The RBS org deals with problems that are directly related to the selling partners and end customers and the ML team drives resolution to organization level problems. Therefore, the Applied Scientist role will impact the large product strategy, identifies new business opportunities and provides strategic direction which is very exciting.

RBS (Retail Business Services) Tech team works towards enhancing the customer experience (CX) and their trust in product data by providing technologies to find and fix Amazon CX defects at scale. Our platforms help in improving the CX in all phases of customer journey, including selection, discoverability & fulfilment, buying experience and post-buying experience (product quality and customer returns). The team also develops GenAI platforms for automation of Amazon Stores Operations. As a Sciences team in RBS Tech, we focus on foundational ML research and develop scalable state-of-the-art ML solutions to solve the problems covering customer experience (CX) and Selling partner experience (SPX). We work to solve problems related to multi-modal understanding (text and images), task automation through multi-modal LLM Agents, supervised and unsupervised techniques, multi-task learning, multi-label classification, aspect and topic extraction for Customer Anecdote Mining, image and text similarity and retrieval using NLP and Computer Vision for product groupings and identifying duplicate listings in product search results. Key job responsibilities As an Applied Scientist, you will be responsible to design and deploy scalable GenAI, NLP and Computer Vision solutions that will impact the content visible to millions of customer and solve key customer experience issues. You will develop novel LLM, deep learning and statistical techniques for task automation, text processing, image processing, pattern recognition, and anomaly detection problems. You will define the research and experiments strategy with an iterative execution approach to develop AI/ML models and progressively improve the results over time. You will partner with business and engineering teams to identify and solve large and significantly complex problems that require scientific innovation. You will independently file for patents and/or publish research work where opportunities arise. The RBS org deals with problems that are directly related to the selling partners and end customers and the ML team drives resolution to organization level problems. Therefore, the Applied Scientist role will impact the large product strategy, identifies new business opportunities and provides strategic direction which is very exciting.

Alexa Connections is looking for a passionate, talented, and inventive Applied Scientist to help build industry-leading technology with Large Language Models (LLMs) and multimodal systems, requiring strong deep learning and generative models knowledge. You will contribute to developing novel solutions and deliver high-quality results that impact Connections products and services. Key job responsibilities As an Applied Scientist with the Alexa Connections team, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art with LLMs. Your work will directly impact our customers in the form of products and services that make use of digital assistant technology. You will leverage Amazon's heterogeneous data sources, unique and diverse international customer nuances and large-scale computing resources to accelerate advances in text, voice, and vision domains in a multimodal setup. The ideal candidate possesses a solid understanding of machine learning, natural language understanding, modern LLM architectures, LLM evaluation & tooling, and a passion for pushing boundaries in this vast and quickly evolving field. They thrive in fast-paced environments to tackle complex challenges, excel at swiftly delivering impactful solutions while iterating based on user feedback, and collaborate effectively with cross-functional teams. A day in the life * Analyze, understand, and model customer behavior and the customer experience based on large-scale data. * Build novel online & offline evaluation metrics and methodologies for multimodal personal digital assistants. * Fine-tune/post-train LLMs using techniques like SFT, DPO, RLHF, and RLAIF. * Set up experimentation frameworks for agile model analysis and A/B testing. * Collaborate with partner teams on LLM evaluation frameworks and post-training methodologies. * Contribute to end-to-end delivery of solutions from research to production, including reusable science components. * Communicate solutions clearly to partners and stakeholders. * Contribute to the scientific community through publications and community engagement.