Careers

The AURORA: Alexa Understanding, Runtime, ORchestration, and Applied sciences org is looking for an Applied Science Manager with a background in Natural Language Processing, Machine/Deep Learning, and Large Language Models (LLMs). You will be working with a team of Applied Scientists to enhance existing features and explore new possibilities with LLM empowerment. You will own high visibility programs with broad visibility and global impact. You will interact with a cross-functional team of Science, Product, and Engineering leaders. We are looking for an Applied Science Manager who will play a key role in the next generation of AI powered Conversational Assistants. Core Leadership & Team Management * Lead and manage applied scientists working on conversational AI capabilities across the full Alexa+ agent execution path * Build and develop high-performing science teams focused on understanding, reasoning, evaluation, and runtime systems * Foster cross-functional collaboration between science and engineering teams to deliver both customer-facing (CX) and developer-facing (DX) experiences Platform & Innovation * Develop modular, reusable platforms that enable 1P and 3P engineers and scientists to accelerate innovation * Transform how builders create conversational AI solutions at scale * Drive evaluation tooling and assessment frameworks to measure conversational experience quality Cross-Organizational Collaboration * Partner with teams across the organization to align goals and accelerate delivery * Navigate organizational changes and simplify interactions between components and teams * Establish clear communication channels and workflows across reporting lines Strategic Impact * Contribute to the team's mission of being the "AI runtime backbone and horizontal intelligence team" for Alexa * Balance advancing research with delivering robust, scalable production solutions * Drive both innovation velocity and operational excellence simultaneously Key job responsibilities * Lead and manage a team of Applied and Data scientists responsible for building and enhancing capabilities for Alexa+ * Collaborate with cross-functional teams to build methods to align Amazon’s LLMs with human preferences. * Identify and prioritize research opportunities that have the potential to significantly impact our AI systems. * Mentor and guide team members to achieve their career goals and objectives. * Communicate research findings and progress to senior leadership and stakeholders. * Rapidly experiment and drive productisation to deliver customer impact. * Drive academic partnership with top tier Indian university as part of the org’s AI/ML Center initiative. * Participate in and drive science publications in peer-reviewed venues of repute. About the team Aurora is the AI runtime backbone and horizontal intelligence team that powers Alexa's core infrastructure, AI capabilities, and specialized conversational models. We revolutionize conversational AI through three core pillars: architecting mission-critical AI runtime systems, advancing science solutions that connect key conversational capabilities, and transforming how builders create at scale. We empower 1P and 3P engineers and scientists worldwide with modular, reusable platforms that accelerate innovation—while delivering accurate, responsive, and reliable conversational experiences to millions of end-users through operational excellence at scale.

The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through novel 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 ecosystem. 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 As an Applied Scientist on our team, you will * Develop AI solutions for Sponsored Brands advertiser and shopper experiences. Build recommendation systems that leverage generative models to develop and improve campaigns. * You invent and design new solutions for scientifically-complex problem areas and/or opportunities in new business initiatives. * You drive or heavily influence the design of scientifically-complex software solutions or systems, for which you personally write significant parts of the critical scientific novelty. You take ownership of these components, providing a system-wide view and design guidance. These systems or solutions can be brand new or evolve from existing ones. * Define a long-term science vision and roadmap for our Sponsored Brands advertising business, driven from our customers' needs, translating that direction into specific plans for applied scientists and engineering teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. * Work closely with engineers and product managers to design, implement and launch AI solutions end-to-end; * Design and conduct A/B experiments to evaluate proposed solutions based on in-depth data analyses; * Think big about the arc of development of Gen AI over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems * Effectively communicate technical and non-technical ideas with teammates and stakeholders; * Translate complex scientific challenges into clear and impactful solutions for business stakeholders. * Mentor and guide junior scientists, fostering a collaborative and high-performing team culture. * Stay up-to-date with advancements and the latest modeling techniques in the field About the team We are on a mission to make Amazon the best in class destination for shoppers to discover, engage, and purchase relevant products, from brands that are relevant to them. In this role, you will design and implement Gen AI solutions that help millions of advertisers create more effective ad campaigns with intelligent recommendations, while improving the overall experience at Amazon's global scale.

Do you want to shape the next generation of AI-driven customer experiences for Amazon’s most ground-breaking products? Join us and help invent the future of shopping. We are seeking a passionate, innovative, and highly skilled Applied Scientist with expertise in AI, Agentic LLMs, Generative AI, Machine Learning, and NLP to help build LLM-powered solutions for Amazon’s BuyForMe product, which enables Amazon customers to discover and purchase products from any merchants. Our team develops science and agentic AI capabilities that power a seamless, end-to-end shopping experience for Amazon customers. We build and advance technologies such as agentic frameworks, LLM fine-tuning, reinforcement learning, prompt engineering, RAG, MCP, and automated benchmarking to improve pre-purchase, in-purchase, and post-purchase workflows. Key job responsibilities As an Applied Scientist on our team, you will: Invent, implement, and evaluate state-of-the-art models and agentic systems that directly impact customer experience. Conduct research that may lead to publications, patents, or cross-Amazon technical influence. Collaborate with engineers, product managers, and other scientists to translate business challenges into scalable science solutions. Run experiments with real customer data and validate hypotheses in a high-impact product environment. Drive excellence in model performance, safety, reliability, and evaluation frameworks.

Do you want to lead the Ads industry and redefine how we measure the effectiveness of Amazon Ads business? Are you passionate about causal inference, Deep Learning/DNN, raising the science bar, and connecting leading-edge science research to Amazon-scale implementation? If so, come join Amazon Ads to be an Economist leader within our Advertising Incrementality Measurement science team! Our work builds the foundations for providing customer-facing experimentation tools, furthering internal research & development on Econometrics, and building out Amazon's advertising measurement offerings. Incrementality is a lynchpin for the next generation of Amazon Advertising measurement solutions and this role will play a key role in the release and expansion of these offerings. Key job responsibilities As an Economist leader within the Advertising Incrementality Measurement (AIM) science team, you are responsible for defining and executing on key workstreams within our overall causal measurement science vision. In particular, you can lead the development of experimental methodologies to measure ad effectiveness, and also build observational models that lay the foundations for understanding the impact of individual ad touchpoints for billions of daily ad interactions. You will work on a team of Applied Scientists, Economists, and Data Scientists, alongside a dedicated Engineering team, to work backwards from customer needs and translate product ideas into concrete science deliverables. You will be a thought leader for inventing scalable causal measurement solutions that support highly accurate and actionable insights--from defining and executing hundreds of thousands of RCTs, to developing an exciting science R&D agenda. You will be working with massive data and industry-leading partner scientists, while also interfacing with leadership to define our future vision. Your work will help shape the future of Amazon Advertising. About the team AIM is a cross disciplinary team of engineers, product managers, economists, data scientists, and applied scientists with a charter to build scientifically-rigorous causal inference methodologies at scale. Our job is to help customers cut through the noise of the modern advertising landscape and understand what actions, behaviors, and strategies actually have a real, measurable impact on key outcomes. The data we produce becomes the effective ground truth for advertisers and partners making decisions affecting millions in advertising spend.

MULTIPLE POSITIONS AVAILABLE Employer: AMAZON DEVELOPMENT CENTER U.S., INC., Offered Position: Research Scientist II Job Location: San Francisco, California Job Number: AMZ9674001 Position Responsibilities: Design research studies to obtain scientific information. Develop theories or models of physical phenomena encountered in quantum computing, superconducting qubit device physics, materials or process development and characterization. Collaborate with others to determine design specifications, including of superconducting quantum processor chips, microwave chip packages, and associated electrical and mechanical components. Develop scientific or mathematical models to predict physical device behavior and performance, and verify the implementation of computational models. Apply mathematical principles or statistical approaches to solve problems, for example to validate modeling predictions under experimental uncertainty using statistical methods. Operate laboratory or field equipment and scientific instrumentation for device fabrication, device characterization, or advanced materials research. Develop new algorithms or methods for designing, simulating, or measuring quantum computers. Develop performance metrics or standards related to quantum information technology. Recommend technical design or process changes to improve quality or performance of superconducting quantum processors and efficiency of their design, manufacture, and testing. Collaborate on research activities with scientists or technical specialists. Prepare scientific or technical reports or presentations and present research results to others. 40 hours / week, 8:00am-5:00pm, Salary Range $168,126/year to $212,800/year. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, visit: https://www.aboutamazon.com/workplace/employee-benefits. Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation.#0000

The Measurement Intelligence Science Team (MIST) in the Measurement, Ad Tech, and Data Science (MADS) organization of Amazon Ads serves a centralized role developing solutions for a multitude of performance measurement products. We create solutions which measure the comprehensive impact of their ad spend, including sales impacts both online and offline and across timescales, and provide actionable insights that enable our advertisers to optimize their media portfolios. We leverage a host of scientific technologies to accomplish this mission, including Generative AI, classical ML, Causal Inference, Natural Language Processing, and Computer Vision. As an Applied Science Manager on the team, you will lead a team of scientists to define and execute a transformative vision for holistic measurement and reporting insights for ad effectiveness. Your team will own the science solutions for foundational experimentation platforms, foundational customer journey understanding technologies, state of the art attribution algorithms to measure the role of advertising in driving observed retail outcomes, and/or agentic AI solutions that help advertisers get quick access to custom insights that inform how to get the most out of their ad spend. Key job responsibilities You independently manage a team of scientists. You identify the needs of your team and effectively grow, hire, and promote scientists to maintain a high-performing team. You have a broad understanding of scientific techniques, several of which may fall out of your specific job function. You define the strategic vision for your team. You establish a roadmap and successfully deliver scientific solutions that execute that vision. You define clear goals for your team and effectively prioritize, balancing short-term needs and long-term value. You establish clear and effective metrics and scientific process to enforce consistent, high-quality artifact delivery. You proactively identify risks and bring them to the attention of your manager, customers, and stakeholders with plans for mitigation before they become roadblocks. You know when to escalate. You communicate ideas effectively, both verbally and in writing, to all types of audiences. You author strategic documentation for your team. You communicate issues and options with leaders in such a way that facilitates understanding and that leads to a decision. You work successfully with customers, leaders, and engineering teams. You foster a constructive dialogue, harmonize discordant views, and lead the resolution of contentious issues. About the team We are a team of scientists across Applied, Research, Data Science and Economist disciplines. You will work with colleagues with deep expertise in ML, NLP, CV, Gen AI, and Causal Inference with a diverse range of backgrounds. We partner closely with top-notch engineers, product managers, sales leaders, and other scientists with expertise in the ads industry and on building scalable modeling and software solutions.

The Measurement Intelligence Science Team (MIST) in the Measurement, Ad Tech, and Data Science (MADS) organization of Amazon Ads serves a centralized role developing solutions for a multitude of performance measurement products. We create solutions which measure the comprehensive impact of their ad spend, including sales impacts both online and offline and across timescales, and provide actionable insights that enable our advertisers to optimize their media portfolios. We leverage a host of scientific technologies to accomplish this mission, including Generative AI, classical ML, Causal Inference, Natural Language Processing, and Computer Vision. As an Applied Science Manager on the team, you will lead a team of scientists to define and execute a transformative vision for holistic measurement and reporting insights for ad effectiveness. Your team will own the science solutions for foundational experimentation platforms, foundational customer journey understanding technologies, state of the art attribution algorithms to measure the role of advertising in driving observed retail outcomes, and/or agentic AI solutions that help advertisers get quick access to custom insights that inform how to get the most out of their ad spend. Key job responsibilities You independently manage a team of scientists. You identify the needs of your team and effectively grow, hire, and promote scientists to maintain a high-performing team. You have a broad understanding of scientific techniques, several of which may fall out of your specific job function. You define the strategic vision for your team. You establish a roadmap and successfully deliver scientific solutions that execute that vision. You define clear goals for your team and effectively prioritize, balancing short-term needs and long-term value. You establish clear and effective metrics and scientific process to enforce consistent, high-quality artifact delivery. You proactively identify risks and bring them to the attention of your manager, customers, and stakeholders with plans for mitigation before they become roadblocks. You know when to escalate. You communicate ideas effectively, both verbally and in writing, to all types of audiences. You author strategic documentation for your team. You communicate issues and options with leaders in such a way that facilitates understanding and that leads to a decision. You work successfully with customers, leaders, and engineering teams. You foster a constructive dialogue, harmonize discordant views, and lead the resolution of contentious issues. About the team We are a team of scientists across Applied, Research, Data Science and Economist disciplines. You will work with colleagues with deep expertise in ML, NLP, CV, Gen AI, and Causal Inference with a diverse range of backgrounds. We partner closely with top-notch engineers, product managers, sales leaders, and other scientists with expertise in the ads industry and on building scalable modeling and software solutions.

This role leads the science function in WW Stores Finance as part of the IPAT organization (Insights, Planning, Analytics and Technology), driving transformative innovations in financial analytics through AI and machine learning across the global Stores finance organization. The successful candidate builds and directs a multidisciplinary team of data scientists, applied scientists, economists, and product managers to deliver scalable solutions that fundamentally change how finance teams generate insights, automate workflows, and make decisions. As part of the WW Stores Finance leadership team, this leader partners with engineering, product, and finance stakeholders to translate emerging AI capabilities into production systems that deliver measurable improvements in speed, accuracy, and efficiency. The role's outputs directly inform VP/SVP/CFO/CEO leadership decisions and drive impact across the entire Stores P&L. Success requires translating complex technical concepts for finance domain experts and business leaders while maintaining deep technical credibility with science and engineering teams. The role demands both strategic vision—identifying high-impact opportunities where AI can transform finance operations—and execution excellence in coordinating project planning, resource allocation, and delivery across multiple concurrent initiatives. This leader establishes methodologies and models that enable Amazon finance to achieve step-change improvements in both the speed and quality of business insights, directly supporting critical processes including month-end reporting, quarterly guidance, annual planning cycles, and financial controllership. Key job responsibilities Transformation of Finance Workflows — Lead development of agentic AI solutions that automate routine finance tasks and transform how teams communicate business insights. Deploy these solutions across financial analysis, narrative generation, and dynamic table creation for month-end reporting and planning cycles. Partner with engineering and product teams to integrate these capabilities into production systems that directly support Stores Finance and FGBS automation goals, delivering measurable reductions in manual effort and cycle time. Science-Based Forecasting — Develop and deploy machine learning forecasts that integrate into existing planning processes including OP1, OP2, and quarterly guidance cycles. Partner with finance teams across WW Stores to iterate on forecast accuracy, applying these models either as alternative viewpoints to complement bottoms-up forecasts or as hands-off replacements for manual forecasting processes. Establish evaluation frameworks that demonstrate forecast performance against business benchmarks and drive adoption across critical planning workflows. Financial Controllership — Scale AI capabilities across controllership workstreams to improve reporting accuracy and automate manual processes. Leverage generative AI to identify financial risk through systematic pattern recognition in transaction data, account reconciliations, and variance analysis. Develop production systems that enhance decision-making speed and quality in financial close, audit preparation, and compliance reporting, delivering quantifiable improvements in error detection rates and process efficiency. About the team IPAT (Insights, Planning, Analytics, and Technology) is a team in the Worldwide Amazon Stores Finance organization composed of leaders across engineering, finance, product, and science. Our mission is to reimagine finance using technology and science to provide fast, efficient, and accurate insights that drive business decisions and strengthen governance. We are dedicated to improving financial operations through innovative applications of technology and science. Our work focuses on developing adaptive solutions for diverse financial use cases, applying AI to solve complex financial challenges, and conducting financial data analysis. Operating globally, we strive to develop adaptable solutions for diverse markets. We aim to advance financial science, continually improving accuracy, efficiency, and insight generation in support of Amazon's mission to be Earth's most customer-centric company.

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 add-on subscriptions such as Apple TV+, Max, 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 technologist, 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! The Prime Video Title Lifecycle Presentation team sits at the intersection of science, experimentation, and customer experience. We leverage data signals and rigorous testing to present the most engaging information about our content to customers at precisely the right moment. Our mission is to ensure every customer interaction with Prime Video content is informed, relevant, and compelling in order to drive discovery and engagement across our vast catalog. We're seeking an Applied Scientist who excels at building sophisticated machine learning systems for content presentation and discovery. The ideal candidate brings deep expertise in: - Multi-modal embeddings for rich metadata representation, enabling nuanced understanding of content attributes and customer preferences - Contextualized ranking systems that adapt to customer intent, viewing context, and real-time signals - Reinforcement learning frameworks that create continuous improvement loops, allowing our systems to learn and optimize from customer interactions over time - General modeling techniques with strong fundamentals in machine learning and statistical methods - Recommender systems experience, with proven ability to build and scale personalization solutions You'll work with cutting-edge technology to solve complex problems in content discovery, leveraging large-scale data to create experiences that delight millions of Prime Video customers worldwide. Key job responsibilities As an Applied Scientist, you will have access to large datasets with billions of images and video to build large-scale machine learning systems. Additionally, you will analyze and model terabytes of text, images, and other types of data to solve real-world problems and translate business and functional requirements into quick prototypes or proofs of concept. We are looking for smart scientists capable of using a variety of domain expertise combined with machine learning and statistical techniques to invent, design, evangelize, and implement state-of-the-art solutions for never-before-solved problems.

Are you fascinated by the power of Natural Language Processing (NLP) and Large Language Models (LLM) to transform the way we interact with technology? Are you passionate about applying advanced machine learning techniques to solve complex challenges in the e-commerce space? If so, Amazon's International Seller Services team has an exciting opportunity for you as an Applied Scientist. At Amazon, we strive to be Earth's most customer-centric company, where customers can find and discover anything they want to buy online. Our International Seller Services team plays a pivotal role in expanding the reach of our marketplace to sellers worldwide, ensuring customers have access to a vast selection of products. As an Applied Scientist, you will join a talented and collaborative team that is dedicated to driving innovation and delivering exceptional experiences for our customers and sellers. You will be part of a global team that is focused on acquiring new merchants from around the world to sell on Amazon’s global marketplaces around the world. The position is based in Seattle but will interact with global leaders and teams in Europe, Japan, China, Australia, and other regions. Join us at the Central Science Team of Amazon's International Seller Services and become part of a global team that is redefining the future of e-commerce. With access to vast amounts of data, cutting-edge technology, and a diverse community of talented individuals, you will have the opportunity to make a meaningful impact on the way sellers engage with our platform and customers worldwide. Together, we will drive innovation, solve complex problems, and shape the future of e-commerce. Please visit https://www.amazon.science for more information Key job responsibilities - Apply your expertise in LLM models to design, develop, and implement scalable machine learning solutions that address complex language-related challenges in the international seller services domain. - Collaborate with cross-functional teams, including software engineers, data scientists, and product managers, to define project requirements, establish success metrics, and deliver high-quality solutions. - Conduct thorough data analysis to gain insights, identify patterns, and drive actionable recommendations that enhance seller performance and customer experiences across various international marketplaces. - Continuously explore and evaluate state-of-the-art NLP techniques and methodologies to improve the accuracy and efficiency of language-related systems. - Communicate complex technical concepts effectively to both technical and non-technical stakeholders, providing clear explanations and guidance on proposed solutions and their potential impact.