Careers

** This position is open to all candidates in Palo Alto, CA, Seattle, WA, NYC and Arlington, VA ** Amazon Ads Response Prediction team is your choice, if you want to join a highly motivated, collaborative, and fun-loving team with a strong entrepreneurial spirit and bias for action. We are seeking an experienced and motivated Machine Learning Applied Scientist who loves to innovate at the intersection of customer experience, deep learning, and high-scale machine-learning systems. Amazon Advertising operates at the intersection of eCommerce and advertising, and is investing heavily in building a world-class advertising business. We are defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long-term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products to improve both shopper and advertiser experience. With a broad mandate to experiment and innovate, we grow at an unprecedented rate with a seemingly endless range of new opportunities. We are looking for a talented Machine Learning Applied Scientist for our Amazon Ads Response Prediction team to grow the business. We are providing advanced real-time machine learning services to connect shoppers with right ads on all platforms and surfaces worldwide. Through the deep understanding of both shoppers and products, we help shoppers discover new products they love, be the most efficient way for advertisers to meet their customers, and helps Amazon continuously innovate on behalf of all customers. Key job responsibilities As a Machine Learning Applied Scientist, you will: * Conduct deep data analysis to derive insights to the business, and identify gaps and new opportunities * Develop scalable and effective machine-learning models and optimization strategies to solve business problems * Run regular A/B experiments, gather data, and perform statistical analysis * Work closely with software engineers to deliver end-to-end solutions into production * Improve the scalability, efficiency and automation of large-scale data analytics, model training, deployment and serving * Conduct research on new machine-learning modeling to optimize all aspects of Sponsored Products business About the team We are pioneers in applying advanced machine learning and generative AI algorithms in Sponsored Products business. We empower every customer with a customized discovery experiences from back-end optimization (such as customized response prediction models) to front-end CX innovation (such as widgets), to help shoppers feel understood and shop efficiently on and off Amazon.

Excited by Big Data, Machine Learning, and Predictive Software? Interested in creating new state-of-the-art solutions using Machine Learning and Data Mining techniques on Terabytes of Data? At Amazon Global Logistics (AGL), our vision is to become the carrier of choice for all of our Selling Partners' cross-border shipping needs, offering a complete set of end-to-end cross-border solutions from key manufacturing hubs to footprint countries, supporting businesses that use Amazon to grow their business globall Key job responsibilities - Utilize machine learning, data mining, and statistical techniques to create new, scalable solutions for business problems. - Analyze and extract relevant information from business data to help automate and optimize key processes. - Design, develop, and evaluate highly innovative models for predictive learning. - Establish scalable, efficient, automated processes for large-scale data analyses, model development, model validation, and model implementation. - Research and implement novel machine learning and statistical approaches. A day in the life As a Data Scientist III in the Business Insight team at Amazon Global Logistics, you will be responsible for developing state-of-the-art large-scale Machine Learning Services involving vast amounts of data and macroeconomic inputs. Your primary focus will be to produce robust forecasts to aid operational excellence and continue improving the customer experience. You will collaborate with cross-functional teams to understand seller behaviors and their impacts on demand generation, demand forecasting, pricing strategies, and asset utilization, especially in areas with variable demand. Your expertise in machine learning, data mining, and statistical techniques will be crucial in creating scalable solutions that drive business impact. About the team The Business Insight team at Amazon Global Logistics is dedicated to leveraging data and advanced analytics to drive operational excellence and enhance the customer experience. As we expand our global logistics operations, the need for solid understanding of seller behaviors, demand forecasting, pricing strategies, and asset utilization becomes increasingly vital. Our team comprises talented and experienced professionals who are passionate about applying innovative machine learning techniques to real-world problems and converting them into highly business-impacting solutions. We foster a collaborative environment that encourages creativity, continuous learning, and a strong commitment to delivering exceptional results. Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan Learn more about our benefits here: https://www.amazon.jobs/en/internal/benefits/us-benefits-and-stock

Amazon Next Generation Developer Experience (NGDE) Organization is looking for world class scientists and engineers to join its team working on AI4Code, LLM, and natural language processing. This group is entrusted with developing core algorithms/capabilities for Amazon Q Developer. At NGDE you will invent, implement, and deploy state of the art AI algorithms and systems for developers. You will build prototypes and explore conceptually new large scale AI solutions. You will interact closely with our customers and with the academic community. You will be at the heart of a growing and exciting focus area for AWS and work with other acclaimed engineers and world famous scientists. About the team AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services. Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

Amazon’s AGI Information is seeking an exceptional Senior Applied Scientist to drive science advancements in the Amazon Knowledge Graph team (AKG). AKG is re-inventing knowledge graphs for the LLM-era, optimizing for LLM grounding and other LLM-based customer experiences. At the same time, AKG is innovating to utilize LLMs in the knowledge graph construction pipelines to overcome obstacles that traditional technologies could not overcome. As a member of the AKG Science team, you will have the opportunity to work on interesting cutting edge problems with immediate customer impact. The team is addressing challenges in automating gap detection, data ingestion, fact verification, query optimization and entity resolution. Your initial focus will be on entity resolution, and you will also have the opportunity to work with scientists working on the other challenges, and with the engineering teams that deliver the science advancements to our customers. A successful candidate has a strong machine learning and LLM background, is a master of state of the art techniques, has a strong publication record, has a desire to push the envelope in one or more of the above areas, and has a track record of delivering to customers. The ideal candidate enjoys operating in dynamic environments, is self-motivated to take on new challenges, and enjoys working with customers, stakeholders and engineering teams to deliver big customer impact, shipping solutions via rapid experimentation and then iterating on user feedback and interactions. Key job responsibilities As a Senior Applied Scientist, you will leverage your technical expertise and experience to demonstrate leadership in tackling large complex problems. You will collaborate with applied scientists and engineers to develop novel algorithms and modeling techniques to build the knowledge graph that delivers fresh factual knowledge to our customers, and that automates the knowledge graph construction pipelines to scale to many billions of facts. Your first responsibility will be to solve entity resolution to enable conflating facts from multiple sources into a single graph entity for each real world entity. You will develop generic solutions that work fo all classes of data in AKG (e.g., people, places, movies, etc.), that cope with sparse, noisy data, that scale to hundreds of millions of entities, and that can handle streaming data. You will define a roadmap to make progress incrementally and you will insist on scientific rigor, leading by example.

When customers search for products on the Amazon website, they often see brand advertisements displayed right below the search bar. These ads are part of the Sponsored Brands (SB) program. Our team, the SB Search and Relevance team, works on solving challenges to retrieve the most relevant ads for a customer's search query. A customer's search query is typically a short, free-form text consisting of just a few words. Our algorithm needs to understand the customer's underlying intention from this limited information. At the same time, each advertisement consists of various elements like text descriptions, images, videos, and more. Our algorithm also needs to comprehend the content of these ads and identify the most relevant one from the large pool of ad candidates. As Amazon's advertising business is growing rapidly, we are looking for experienced applied scientists. As an Applied Scientist on this team, you will: Build deep learning models to improve our search relevance for online advertising. - Apply deep learning and natural language processing to improve information retrieval and relevance. - Design and run A/B experiments. Evaluate the impact of your optimizations and communicate your results to various business stakeholders. - Optimize deep learning inference latency by utilizing methods like knowledge distillation. - Work with software development engineers and write code to bring models into production. 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 fundamentally 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

We are building GenAI based shopping assistant for Amazon. We reimage Amazon Search with an interactive conversational experience that helps you find answers to product questions, perform product comparisons, receive personalized product suggestions, and so much more, to easily find the perfect product for your needs. We’re looking for the best and brightest across Amazon to help us realize and deliver this vision to our customers right away. This will be a once in a generation transformation for Search, just like the Mosaic browser made the Internet easier to engage with three decades ago. If you missed the 90s—WWW, Mosaic, and the founding of Amazon and Google—you don’t want to miss this opportunity.

Are you fascinated by the power of Large Language Models (LLM) and applying Generative AI to solve complex challenges within one of Amazon's most significant businesses? Amazon Selection and Catalog Systems (ASCS) builds the systems that host and run the world’s largest e-Commerce products catalog - it powers the online buying experience for customers worldwide so they can find, discover and buy anything they want. Amazon’s customers rely on the completeness, consistency and correctness of Amazon's product data to make well-informed purchase decisions. Improving the quality of product data is a continuous process. It requires data driven decisions on what product data changes simplify and improve the Customers’ experience. Amazon Selection and Catalog Systems (ASCS) is seeking an Applied Scientist II for developing Generative AI and Large Language Models (LLM) that can help generate richer and expanded product information. You will be a part of a team consisting of experienced Applied Scientists working on a new set of initiatives, building models and delivering them into the Amazon production ecosystem. Your efforts will build a robust ensemble of LLM artifacts and ML systems that can achieve high precision and recall, and scale to new marketplaces and languages. This problem is challenging due to sheer scale (billions of products in the catalog), diversity (products ranging from electronics to groceries to instant video across multiple languages) and multitude of input sources (millions of sellers contributing product data with different quality). We are looking for an experienced Scientist who can develop best in class solutions. Your primary customers are Amazon shoppers who would thank you for correct product information in our catalogs across countries and languages. The ideal Applied Scientist candidate has deep expertise in one or several of the following fields: Web search, Applied/Theoretical Machine Learning, Large Language Models, Deep Neural Networks, Classification Systems, Clustering, Label Propagation, Natural Language Processing, Computer Vision, Active learning, and Artificial Intelligence. S/he has a strong publication record at top relevant academic venues and experience in launching products/features in the industry. Do you want the excitement of experimenting with cutting edge Large Language Models (LLMs), machine learning, natural language processing, computer vision, and active learning models to solve real world problems at scale? Imagine experimenting with LLMs, with Deep Neural Networks as your daily job and imagine using your model outputs to affect the product discovery of the biggest e-commerce retailer in the world. Imagine doing research inside of an Amazon team that is always looking to deploy creative solutions to real world problems in product discovery. Your research findings are directly related to Amazon’s customer experiences and impact millions of customers, ingesting images, text and all the structured and unstructured attributes in the Amazon catalog to drive true understanding of products at scale. Amazon Science gives you insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work. Please visit https://www.amazon.science for more information. A day in the life You will work with an Amazon team that builds creative solutions to real world problems. Your team will own devising the strategy and execution plans that power initiatives ranging from: developing tuning artifacts on top of foundational LLMs, training ML models, performing fact extraction, automatic detection of missing product information, active learning mechanisms for scaling human tasks, building applications for distilling product information, building mechanisms to analyze product composition, ingest images, text, and unstructured data to drive deep understanding of products at scale. About the team The team's mission is to infer knowledge, understand, classify, derive product facts for all Amazon products entering the Catalog. The work is critical to power the Amazon product detail pages experiences, Search, Navigation and impacting millions of customers. This is an already formed team with experience leading programs spanning services and ML initiatives supporting all countries and languages. The candidate collaborates closely with Scientists, Software Developers, and has exposure to multiple peer teams at Amazon who rely on this team's developments.

The Team: Amazon Go is a new kind of store with no lines and no checkout—you just grab and go! Customers simply use the Amazon Go app to enter the store, take what they want from our selection of fresh, delicious meals and grocery essentials, and go! Our checkout-free shopping experience is made possible by our Just Walk Out Technology, which automatically detects when products are taken from or returned to the shelves and keeps track of them in a virtual cart. When you’re done shopping, you can just leave the store. Shortly after, we’ll charge your Amazon account and send you a receipt. Check it out at amazon.com/go. Designed and custom-built by Amazonians, our Just Walk Out Technology uses a variety of technologies including computer vision, sensor fusion, and advanced machine learning. Innovation is part of our DNA! Our goal is to be Earths’ most customer centric company and we are just getting started. We need people who want to join an ambitious program that continues to push the state of the art in computer vision, machine learning, distributed systems and hardware design. The Role: Everyone on the team needs to be entrepreneurial, wear many hats and work in a highly collaborative environment that’s more startup than big company. We’ll need to tackle problems that span a variety of domains: computer vision, image recognition, machine learning, real-time and distributed systems. As a Machine Learning or Computer Vision Research Scientist, you will help solve a variety of technical challenges and mentor other engineers. You will tackle challenging, novel situations every day and given the size of this initiative, you’ll have the opportunity to work with multiple technical teams at Amazon in different locations. You should be comfortable with a degree of ambiguity that’s higher than most projects and relish the idea of solving problems that, frankly, haven’t been solved at scale before - anywhere. Along the way, we guarantee that you’ll learn a ton, have fun and make a positive impact on millions of people. About the team Why AWS Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Mentorship and Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

The Team: Amazon Go is a new kind of store with no lines and no checkout—you just grab and go! Customers simply use the Amazon Go app to enter the store, take what they want from our selection of fresh, delicious meals and grocery essentials, and go! Our checkout-free shopping experience is made possible by our Just Walk Out Technology, which automatically detects when products are taken from or returned to the shelves and keeps track of them in a virtual cart. When you’re done shopping, you can just leave the store. Shortly after, we’ll charge your Amazon account and send you a receipt. Check it out at amazon.com/go. Designed and custom-built by Amazonians, our Just Walk Out Technology uses a variety of technologies including computer vision, sensor fusion, and advanced machine learning. Innovation is part of our DNA! Our goal is to be Earths’ most customer centric company and we are just getting started. We need people who want to join an ambitious program that continues to push the state of the art in computer vision, machine learning, distributed systems and hardware design. The Role: Everyone on the team needs to be entrepreneurial, wear many hats and work in a highly collaborative environment that’s more startup than big company. We’ll need to tackle problems that span a variety of domains: computer vision, image recognition, machine learning, real-time and distributed systems. As a Machine Learning or Computer Vision Research Scientist, you will help solve a variety of technical challenges and mentor other engineers. You will tackle challenging, novel situations every day and given the size of this initiative, you’ll have the opportunity to work with multiple technical teams at Amazon in different locations. You should be comfortable with a degree of ambiguity that’s higher than most projects and relish the idea of solving problems that, frankly, haven’t been solved at scale before - anywhere. Along the way, we guarantee that you’ll learn a ton, have fun and make a positive impact on millions of people. About the team Why AWS Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Mentorship and Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

Have you ever wondered how Amazon predicts when your order will arrive and how we ensure that it actually arrives on at the promised date/time? Have you wondered where all those Amazon semi-trucks on the road are headed? Are you passionate about increasing efficiency and reducing carbon footprint? Does the idea of having worldwide impact on Amazon's logistics network including our planes, trucks, and vans sound exciting to you? If so, then we want to talk with you! At Amazon's Supply Chain Optimization Technologies (SCOT), we are tasked with optimizing the fulfilment on customer orders so that we fulfil all orders worldwide in the most intelligent manner while ensuring Amazon customers get their orders on time. Amazon Fulfillment Planning & Execution (FPX) Science team within SCOT- Fulfilment Optimization group is seeking Manager Research Science with expertise in Machine Learning and/or Optimization and a proven record of leading scientists and solving business problems through scalable ML solutions. FPX Science tackles some of the most mathematically complex challenges in transportation planning and execution space to improve Amazon's operational efficiency worldwide. We own Amazon’s global fulfilment center and transportation planning and execution. The team also owns the short-term network planning and execution that determines the optimal flow of customer orders through Amazon fulfilment network. This includes developing sophisticated math models and controllers that assign orders to fulfilment centers to be picked and packed and then planning the optimal ship method in terms of cost, speed and carbon impact to deliver to the customer. These plans drive downstream decisions that are in the billions of dollars at Amazon Scale worldwide. The systems we build are entirely in-house, and are on the cutting edge of both academic and applied research in large scale supply chain planning, optimization, machine learning and statistics. These systems operate at various scales, from real-time decision system that completes thousands of transactions per seconds, to large scale distributed system that optimize Amazon’s fulfilment network. As Amazon continues to build and expand the first party delivery network, this role will be critical to realize this vision. Your team and tech solution will have large impacts to the physical supply chain of Amazon, and play a key role in improving Amazon consumer business’s long-term profitability. If you are interested in diving into a multi-discipline, high impact space this is the team for you. We’re looking for a passionate, results-oriented, and inventive Scientist who can lead from the front towards developing and deploying ML models for our outbound transportation planning systems. In addition, you will be working on design, development and evaluation of highly innovative ML models for solving complex business problems in the area of outbound transportation planning systems. The position is located at Bellevue, WA, just next to Seattle with beautiful outdoors and great city life. Watch http://bit.ly/amazon-scot to get the big picture. Key job responsibilities As a Manager of Research Science within FPX Science team, you will lead a team of research and applied scientists towards designing and deploy solutions that will likely draw from a range of scientific areas such as supervised, semi-supervised and unsupervised learning, reinforcement learning, advanced statistical modeling, and graph models. You will have an opportunity to be on the forefront of supply chain thought leadership by working on some of the most difficult problems in the industry, with some of the best product managers, research scientists, statisticians, and software engineers to integrate scientific work into production systems. You will bring deep technical expertise in the area of Machine Learning, and will play an integral part in building Amazon's Fulfillment Optimization systems. Other responsibilities include: * Lead a team of research and applied scientists towards design, development and evaluation of highly innovative ML models for solving complex business problems. * Technically lead and mentor the scientists on the team. * Research and apply the latest ML techniques and best practices from both academia and industry. * Use and analytical techniques to create scalable solutions for business problems. * Work closely with software engineering teams to build model implementations and integrate successful models and algorithms in production systems at very large scale. * Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation. A day in the life In this critical role, you will be a technical leader in operations research or machine learning with significant scope, impact, and visibility. Your solutions have the potential to drive billions of dollars in impact for Amazon's supply chain globally. As a science manager on the team, you will engage in all facets of the process from ideation, business analysis and scientific research to development and deployment of advanced models. We are seeking someone who wants to lead projects that require innovative thinking and deep technical problem-solving skills to create production-ready machine learning solutions. A successful candidate is able to quickly approach large ambiguous problems, turn high-level business requirements into mathematical models, identify the right solution approach, and contribute to the software development for production systems. Successful candidates must thrive in fast-paced environments, which encourage collaborative and creative problem solving, be able to measure and estimate risks, constructively critique peer research, and align research focuses with the Amazon's strategic needs. We look for individuals who know how to deliver results and show a desire to develop themselves, their team, and their career. About the team Fulfillment Planning & Execution Science team contains a group of scientists with different technical backgrounds including Machine Learning and Operations Research, who will collaborate closely with you on your projects. Our team directly supports critical functional areas across Fulfillment Optimization and the research needs of the corresponding product and engineering teams. We tackle some of the most mathematically complex challenges in facility and transportation planning and execution to improve Amazon's operational efficiency worldwide and at a scale that is unique to Amazon. We often seek the opportunity of applying hybrid techniques in the space of Operations Research and Machine Learning to tackle some of our biggest technical challenges. We disambiguate complex supply chain problems and create ML and optimization solutions to solve those problems at scale.