Careers

Amazon is looking for a talented Postdoctoral Scientist to join our Seller Fees Science & Tech team for a one-year, full-time research position. Postdoctoral Scientists will drive data-driven innovations in the seller fee domain for our EU marketplace. In this role, you will have the opportunity to: Leverage economic methods like modeling and impact estimation to address key issues using large, real-world datasets; Partner with PMs and BAs to identify data and define metrics evaluating business initiatives and making recommendations; Execute from idea to implementation as an integral part of cross-functional teams; Thrive in a highly complex and fast pacing environment. Participate in research activities, including publishing papers, attending conferences, and collaborating with academic institutions to advance the state-of-the-art in relevant fields. Key job responsibilities In this role you will: Build causal inference modeling to evaluate the effects of policy changes, such as fee adjustments and new fee structures, on seller behaviors and business metrics; Analyze how sellers and key outcomes are impacted by variations in growth strategies; Design experiments to measure pilot programs and support scaling-up effort; Synthesize learnings from past policy changes into critical insight to help the business develop new strategies and make science-based decisions. Work closely with a senior science advisor, collaborate with other scientists and engineers, and be part of Amazon’s vibrant and diverse global science community. Publish your innovation in top-tier academic venues and hone your presentation skills. Be inspired by challenges and opportunities to invent cutting-edge techniques in your area(s) of expertise. About the team The Fee Science Team works on science, economic, machine learning, and data engineering projects for Selling Partner Services and third-party fees. Our projects include causal modeling and impact of structural changes, models that support fee integrity, business analytics, and a comprehensive set of data sources and pipelines.

About Amazon Health Amazon Health’s mission is to make it dramatically easier for customers to access the healthcare products and services they need to get and stay healthy. Towards this mission, we (Health Storefront and Shared Tech) are building the technology, products and services, that help customers find, buy, and engage with the healthcare solutions they need. Job summary We are seeking an exceptional Senior Applied Scientist to join a team of experts in the field of machine learning, and work together to break new ground in the world of healthcare to make personalized and empathetic care accessible, convenient, and cost-effective. We leverage and train state-of-the-art large-language-models (LLMs) and develop entirely new experiences to help customers find the right products and services to address their health needs. We work on machine learning problems for intent detection, dialogue systems, and information retrieval. You will work in a highly collaborative environment where you can pursue both near-term productization opportunities to make immediate, meaningful customer impacts while pursuing ambitious, long-term research. You will work on hard science problems that have not been solved before, conduct rapid prototyping to validate your hypothesis, and deploy your algorithmic ideas at scale. You will get the opportunity to pursue work that makes people's lives better and pushes the envelop of science. #everydaybetter Key job responsibilities - Translate product and CX requirements into science metrics and rigorous testing methodologies. - Invent and develop scalable methodologies to evaluate LLM outputs against metrics and guardrails. - Design and implement the best-in-class semantic retrieval system by creating high-quality knowledge base and optimizing embedding models and similarity measures. - Conduct tuning, training, and optimization of LLMs to achieve a compelling CX while reducing operational cost to be scalable. A day in the life In a fast-paced innovation environment, you work closely with product, UX, and business teams to understand customer's challenges. You translate product and business requirements into science problems. You dive deep into challenging science problems, enabling entirely new ML and LLM-driven customer experiences. You identify hypothesis and conduct rapid prototyping to learn quickly. You develop and deploy models at scale to pursue productizations. You mentor junior science team members and help influence our org in scientific best practices. About the team We are the Health AI team at HST (Health Store and Technology). The team consists of exceptional ML Scientists with diverse background in healthcare, robotics, customer analytics, and communication. We are committed to building and deploying the most advanced scientific capabilities and solutions for the products and services at Amazon Health.

Are you interested in building state-of-the-art machine learning systems for the most complex, and fastest growing, transportation network in the world? If so, Amazon has the most exciting, and never-before-seen, challenges at this scale (including those in sustainability, e.g. how to reach net zero carbon by 2040). Amazon’s transportation systems get millions of packages to customers worldwide faster and cheaper while providing world class customer experience – from online checkout, to shipment planning, fulfillment, and delivery. Our software systems include services that use tens of thousands of signals every second to make business decisions impacting billions of dollars a year, that integrate with a network of small and large carriers worldwide, that manage business rules for millions of unique products, and that improve experience of over hundreds of millions of online shoppers. As part of this team you will focus on the development and research of machine learning solutions and algorithms for core planning systems, as well as for other applications within Amazon Transportation Services, and impact the future of the Amazon delivery network. Current research and areas of work within our team include machine learning forecast, uncertainty quantification, planning systems, model interpretability, graph neural nets, among others. We are looking for a Machine Learning Scientist with a strong academic background in the areas of machine learning, time series forecasting, and/or optimization. At Amazon, we strive to continue being the most customer-centric company on earth. To stay there and continue improving, we need exceptionally talented, bright, and driven people. If you'd like to help us build the place to find and buy anything online, and deliver in the most efficient and greenest way possible, this is your chance to make history. About the team The EU ATS Science and Technology (SnT) team owns scalable algorithms, models and systems that improve customer experience in middle-mile. We work backwards from Amazon's customers aiming to make transportation faster, cheaper, safer, more reliable and ecologically sustainable.

Want to work in a start-up environment with the resources of Amazon behind you? Do you want to have direct and immediate impact on millions of customers every day? If you are a self-starter, passionate about machine learning, deep learning, big data systems, enjoy designing and implementing new features and machine learned models, and intrigued by ambiguous problems, look no further. 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 Kindles, tablets, and 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: Our team is responsible for building a new advertising product for non-endemic advertisers. We are tasked with taking this start-up offering to market, with the goal of empowering over one million non-endemic advertisers to independently plan and execute campaigns. “Non-endemic” brands offer products and services that are not sold/available in Amazon’s retail marketplace, including restaurants, hotels, airlines, insurance, telecom, and automobiles. We are embarking on a multi-year vision to democratize display advertising for non-endemic advertisers at self-service scale. This will open up Amazon Ads to self-service non-endemic demand— whether they sell on the Amazon store or not— to activate Amazon Ads first-party audiences built from shopping and streaming signals and access unique ad inventory to help grow their business. Key job responsibilities - Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity. - 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. - 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. - Train and fine-tune neural models including transformers and language models. - Recruit Applied Scientists to the team and provide mentorship.

Do you want to join an innovative team of scientists who use machine learning and statistical techniques to create state-of-the-art solutions for providing better value to Amazon’s customers? Do you want to build and deploy advanced algorithmic systems that help optimize millions of transactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data to solve real world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Machine Learning and Data Sciences team for India Consumer Businesses. If you have an entrepreneurial spirit, know how to deliver, love to work with data, are deeply technical, highly innovative and long for the opportunity to build solutions to challenging problems that directly impact the company's bottom-line, we want to talk to you. Major responsibilities 3+ years of building machine learning models for business application experience PhD, or Master's degree and 2+ years of applied research experience Knowledge of programming languages such as C/C++, Python, Java or Perl Experience programming in Java, C++, Python or related language You have expertise in one of the applied science disciplines, such as machine learning, natural language processing, computer vision, Deep learning You are able to use reasonable assumptions, data, and customer requirements to solve problems. You initiate the design, development, execution, and implementation of smaller components with input and guidance from team members. You work with SDEs to deliver solutions into production to benefit customers or an area of the business. You assume responsibility for the code in your components. You write secure, stable, testable, maintainable code with minimal defects. You understand basic data structures, algorithms, model evaluation techniques, performance, and optimality tradeoffs. You follow engineering and scientific method best practices. You get your designs, models, and code reviewed. You test your code and models thoroughly You participate in team design, scoping and prioritization discussions. You are able to map a business goal to a scientific problem and map business metrics to technical metrics. You invent, refine and develop y

The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and innovative applied scientist with a strong background in responsible AI, deep learning and large language models (LLMs) techniques to develop and deploy world-class foundation models. Key job responsibilities As an Applied Scientist with the AGI team, you will work with world-class scientists and engineers to develop novel data, modeling and engineering solutions to support the responsible AI initiatives at AGI. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources and collaborate with colleagues cross-AGI to achieve this objective. Your work will have a direct impact to AGI's business and customers through the foundation models we develop and depoly. About the team Our team's mission is to develop and deploy industry-leading foundation models that set the benchmark for the industry, comply with the relevant responsible RAI policies and delight our customers in the process.

We’re working to improve shopping on Amazon using the conversational capabilities of large language models, 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, and technical program managers (TPM) 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!

Amazon.com strives to be Earth's most customer-centric company where customers can shop in our stores to find and discover anything they want to buy. We hire the world's brightest minds, offering them a fast paced, technologically sophisticated and friendly work environment. Economists at Amazon partner closely with senior management, business stakeholders, scientist and engineers, and economist leadership to solve key business problems. Amazon Economists build econometric models using our world class data systems and apply approaches from a variety of skillsets. You will work in a fast moving environment to solve business problems as a member of a cross-functional team. You will be expected to develop techniques that apply econometrics to large data sets, address quantitative problems, and contribute to the design of automated systems around the company. Key job responsibilities A Senior Economist in this team leads initiatives that make a significant measurable impact on the strategic goals of the business through empowering the PV organization to make smart, long-term decisions through the use of both online (within experiment) and offline metrics (post-predicted) that drive economically sustainable growth for Amazon. They own best in class casual models and metrics that unblock trade-off decisions when business and customer outcomes do not align. Sr. Economist in this team partners with finance to align PV’s economic models with the business financial P&L models, and works closely with Product Managers and Business to bridge the gap between science and business. They partner with data engineers and central teams to standardize economic data definitions and integrate the LTV measures directly in Amazon experimentation tooling. They set the Standard Operating Procedure for the PV LTV measurement systems, provide visibility and explainability into the model outputs to empower users to understand and use them effectively. To be successful in the role, a Senior Economist in PSE must have deep expertise in econometrics and possess a good understanding of strength and weakness of various science approaches.They drive best practices and set standards for metric development process, model calibration, evaluation and governance, and balancing science (i.e. metric fidelity) and engineering constraints. They advise on minimum data requirements for various models, and are able to persuade teams to collect additional observational or experimental data when necessary. They extensively monitor model performance and identify opportunities for improvement in model precision, sensitivity, scalability and operational excellence. About the team Prime Video Content discovery science is a central team which defines customer and business success metrics, models, heuristics and econometric frameworks. The team develops, owns and operates a suite of data science and economic models that govern online and offline decision making systems. The team is responsible for Prime Video’s experimentation practice and continuously innovates and upskills teams across the organization on science best practices. The team values diversity, collaboration and learning, and is excited to welcome a new member whose passion and creativity will help the team continue innovating and enhancing customer experience.

The Amazon Search team creates powerful, customer-focused search and advertising solutions and technologies. Whenever a customer visits an Amazon site worldwide and types in a query or browses through product categories, our services go to work. We design, develop, and deploy high performance, fault-tolerant distributed search systems used by millions of Amazon customers every day. This position will develop economic frameworks for selecting products into customer consideration sets, develop a theoretic framework of the search process and customer frictions that lends to policy evaluation, and create frameworks for coordinating product discovery with other marketplace decision systems like ordering, pricing, and delivery optimization. The ideal candidate will have outstanding Economics knowledge, demonstrated strength in practical and policy relevant structural econometrics, strong collaboration skills, proven ability to lead highly ambiguous and large projects, and a drive to deliver results. They will work closely with Economists, Data / Applied Scientists, Engineers, and Product leads to integrate economic insights into policy and production systems Familiarity with informational retrieval and recommender systems is a plus but not required. Key job responsibilities This role is responsible for creating mechanisms (metrics, models, mechanism) that optimize search while accounting for effects on the entirety of the Amazon Stores. Some example projects include: * Develop an economic frameworks for selecting products into customer consideration sets. Utilizing demand estimation, internalizing spillovers (e.g. menu effects), and incorporating long term effects on customer beliefs. We want to embed economics into state of the art list-wise ranking models. * Develop a means of valuing newly launched products and how the impact all aspects of the experience (prices, brand awareness, or even referential utility). * Develop a theoretic framework of the search process with a valuation of customer frictions that lends to evaluation of changes in the experience (aka a “search/browse model”) * Create frameworks for coordinating product discovery with other marketplace decision systems like ordering, pricing, and delivery optimization.

Amazon is hiring a Principal Applied Scientist (PAS) to join the Search and Conversational Shopping AI team. In this role, you will be responsible for the architectural design and technological advancements of the customer experience of Amazon Rufus, our next-generation, AI-driven search and shopping assistant. This innovative role focuses on developing innovative search and shopping experiences, utilizing large language models, generative AI, and advanced machine learning technologies. Key job responsibilities As a Principal Applied Scientist in Search, you will possess deep expertise in machine learning and data science, with specializations in information retrieval, recommendations, ranking, large language models, and generative AI across various modalities. The role involves solution alignment across multiple partners, such as front-end, relevance, ranking, and personalization teams. You will collaborate with teams of scientists and engineers to translate business and functional requirements into concrete deliverables, leading strategic efforts to enhance upper funnel search customer experiences. You will design integrated solutions efficiently delivered across all contributing stakeholder teams, driving alignment among these tech teams in the short term and influencing their future roadmaps in the long term to support our experimentation roadmap. Responsible for overall solution quality, this role will focus on improving experimentation velocity and, in the future, facilitating partner development on upper funnel customer experiences. This role ensures we are building scalable solutions with smart checks on data quality centrally, navigating the ambiguity inherent in this new area. You will make critical judgements to select the best technical solutions for both short and long-term experimentation objectives, bringing clarity from ambiguity, structuring tradeoff decisions, and effectively communicating on technically contentious topics. Finally, you will engage with academic partners to augment our in-house talent with access to the latest research and expert mentoring. About the team The vision of the Search and Conversational Shopping AI Team is to revolutionize the search and shopping experience through technological innovations in advanced AI and machine learning. We focus on enhancing query understanding, navigational and upper funnel search, developing LLM-based AI assistants, and more. Our goal is to create intuitive, personalized search interfaces that seamlessly connect customers with products, enhancing satisfaction, engagement, and transforming e-commerce interactions.