Careers

The Amazon Search Mission Understanding (SMU) team is at the forefront of revolutionizing the online shopping experience through the Amazon search page. Our ambition extends beyond facilitating a seamless shopping journey; we are committed to creating the next generation of intelligent shopping assistants. Leveraging cutting-edge Large Language Models (LLMs), we aim to redefine navigation and decision-making in e-commerce by deeply understanding our users' shopping missions, preferences, and goals. By developing responsive and scalable solutions, we not only accomplish the shopping mission but also foster unparalleled trust among our customers. Through our advanced technology, we generate valuable insights, providing a guided navigation system into various search missions, ensuring a comprehensive and holistic shopping experience. Our dedication to continuous improvement through constant measurement and enhancement of the shopper experience is crucial, as we strategically navigate the balance between immediate results and long-term business growth. We are seeking an Applied Scientist who is not just adept in the theoretical aspects of Machine Learning (ML), Artificial Intelligence (AI), and Large Language Models (LLMs) but also possesses a pragmatic, hands-on approach to navigating the complexities of innovation. The ideal candidate will have a profound expertise in developing, deploying, and contributing to the next-generation shopping search engine, including but not limited to Retrieval-Augmented Generation (RAG) models, specifically tailored towards enhancing the Rufus application—an integral part of our mission to revolutionize shopping assistance. You will take the lead in conceptualizing, building, and launching groundbreaking models that significantly improve our understanding of and capabilities in enhancing the search experience. A successful applicant will display a comprehensive skill set across machine learning model development, implementation, and optimization. This includes a strong foundation in data management, software engineering best practices, and a keen awareness of the latest developments in distributed systems technology. We are looking for individuals who are determined, analytically rigorous, passionate about applied sciences, creative, and possess strong logical reasoning abilities. Join the Search Mission Understanding team, a group of pioneering ML scientists and engineers dedicated to building core ML models and developing the infrastructure for model innovation. As part of Amazon Search, you will experience the dynamic, innovative culture of a startup, backed by the extensive resources of Amazon.com (AMZN), a global leader in internet services. Our collaborative, customer-centric work environment spans across our offices in Palo Alto, CA, and Seattle, WA, offering a unique blend of opportunities for professional growth and innovation. Key job responsibilities In this role you will leverage your engineering background and expertise to help build the next generation of our mission understanding models and data collection framework. On a day-to-day basis, you will: * Interface with Applied Scientists, Product Managers, and Program Managers to determine requirements for production systems * Analyze log data to determine future system design and configure parameters Build scalable and production-ready data pipelines to extract features from petabytes of raw data Integrate models and algorithms in complex, real-time production systems on immense scale * Design and execute experiments to determine the impact of models and algorithms you intend to deploy in production * Run analysis reports of web-experiments to identify benefits and risk of launching the models and algorithms * Serve as a liaison to our customer/seller-facing partner teams in case of escalations Project manage cross-functional Machine Learning initiatives

Amazon Japan Store Tech (JST) Science team serves as the core science division of JP Store Tech, with the vision to enable and accelerate the best-in-class CX through state-of-the-art machine learning technologies. This team owns the science vision definition, science roadmap planning, and science solution delivery in key business areas in Japan including Search, Customer Growth and Engagement, Personalization and Delivery. As the Applied Science Manager, you will manager the teams of scientists (applied scientists, data scientists) and machine learning engineers where the business opportunity or overall strategy may not yet be defined. You need to create the science long-term vision and roadmap across multiple business domains. Your team will design, implement and deliver science models on Amazon site, helping millions of customers every day to find quickly what they are looking for. Key job responsibilities * Leads team(s) performing strategically important scientific analyses to identify technology gaps and business opportunities. * Leads team(s) driving the design and delivery of solutions or systems that address significantly complex science problems and tooling efforts, decisions, and escalations. * Communicates and drives strategic initiatives (3-5 year). Critical inputs into OP1/OP2. May be actively involved with the external scientific community *Build a science publication strategy (what to publish, where and when). Determines when to establish a program or make a case for resources. A day in the life Your benefits include: * Working on a high-impact, high-visibility product, with your work improving the experience of millions of customers * The opportunity to use (and innovate) state-of-the-art ML methods to solve real-world problems with tangible customer impact * Being part of a growing team where you can influence the team's mission, direction, and how we achieve our goals

Here at Amazon, we embrace our differences. We are committed to furthering our culture of diversity and inclusion of our teams within the organization. How do you get items to customers quickly, cost-effectively, and—most importantly—safely, in less than an hour? And how do you do it in a way that can scale? Our teams of hundreds of scientists, engineers, aerospace professionals, and futurists have been working hard to do just that! We are delivering to customers, and are excited for what’s to come. Check out more information about Prime Air on the About Amazon blog (https://www.aboutamazon.com/news/transportation/amazon-prime-air-delivery-drone-reveal-photos). If you are seeking an iterative environment where you can drive innovation, apply state-of-the-art technologies to solve real world delivery challenges, and provide benefits to customers, Prime Air is the place for you. Come work on the Amazon Prime Air Team! We are seeking a highly skilled Navigation Scientist to help develop advanced algorithms and software for our Prime Air delivery drone program. In this role, you will conduct comprehensive navigation analysis to support cross-functional decision-making, define system architecture and requirements, contribute to the development of flight algorithms, and actively identify innovative technological opportunities that will drive significant enhancements to meet our customers' evolving demands. Export Control License: This position may require a deemed export control license for compliance with applicable laws and regulations. Placement is contingent on Amazon’s ability to apply for and obtain an export control license on your behalf.

Amazon is looking for creative Applied Scientists to tackle some of the most interesting problems on the leading edge of information retrieval (IR) and machine learning (ML) with our Alexa Artificial Intelligence (AI) team. Alexa AI aims to reinvent search and information retrieval for a voice-forward, multi-modal future. We enable customers to interact with unstructured and semi-structured content via a broad range of customer experiences including question answering, summarization, and search. If you are looking for an opportunity to develop innovative solutions to deep technical problems having a massive customer impact, this might be the role for you! As an Applied Scientist, you will work with smart, passionate colleagues in a fast-paced environment. You will develop and help deploy novel, scalable algorithms to advance the state-of-the-art in technology areas at the intersection of IR and ML. You will keep up with relevant research in the field of IR and publish your work in top-tier conferences. You will contribute to a multi-year research roadmap, enabling the team to focus on the right technical challenges to delight our customers. Key job responsibilities Develop state-of-the-art web search technology, including training novel retrieval and ranking models, scaling models and optimizing performance, partnering with engineering to deploy and debug model performance in production, and building and scaling quality training data sets.

Our customers have immense faith in our ability to deliver packages timely and as expected. A well planned network seamlessly scales to handle millions of package movements a day. It has monitoring mechanisms that detect failures before they even happen (such as predicting network congestion, operations breakdown), and perform proactive corrective actions. When failures do happen, it has inbuilt redundancies to mitigate impact (such as determine other routes or service providers that can handle the extra load), and avoids relying on single points of failure (service provider, node, or arc). Finally, it is cost optimal, so that customers can be passed the benefit from an efficiently set up network. Amazon Shipping is hiring Applied Scientists to help improve our ability to plan and execute package movements. As an Applied Scientist in Amazon Shipping, you will work on multiple challenging machine learning problems spread across a wide spectrum of business problems. You will build ML models to help our transportation cost auditing platforms effectively audit off-manifest (discrepancies between planned and actual shipping cost). You will build models to improve the quality of financial and planning data by accurately predicting ship cost at a package level. Your models will help forecast the packages required to be pick from shipper warehouses to reduce First Mile shipping cost. Using signals from within the transportation network (such as network load, and velocity of movements derived from package scan events) and outside (such as weather signals), you will build models that predict delivery delay for every package. These models will help improve buyer experience by triggering early corrective actions, and generating proactive customer notifications. Your role will require you to demonstrate Think Big and Invent and Simplify, by refining and translating Transportation domain-related business problems into one or more Machine Learning problems. You will use techniques from a wide array of machine learning paradigms, such as supervised, unsupervised, semi-supervised and reinforcement learning. Your model choices will include, but not be limited to, linear/logistic models, tree based models, deep learning models, ensemble models, and Q-learning models. You will use techniques such as LIME and SHAP to make your models interpretable for your customers. You will employ a family of reusable modelling solutions to ensure that your ML solution scales across multiple regions (such as North America, Europe, Asia) and package movement types (such as small parcel movements and truck movements). You will partner with Applied Scientists and Research Scientists from other teams in US and India working on related business domains. Your models are expected to be of production quality, and will be directly used in production services. You will work as part of a diverse data science and engineering team comprising of other Applied Scientists, Software Development Engineers and Business Intelligence Engineers. You will participate in the Amazon ML community by authoring scientific papers and submitting them to Machine Learning conferences. You will mentor Applied Scientists and Software Development Engineers having a strong interest in ML. You will also be called upon to provide ML consultation outside your team for other problem statements. If you are excited by this charter, come join us!

How can Amazon improve the advertising experience for customers around the world? How can we help advertisers and customers find each other in a meaningful way? Amazon Advertising creates and transforms the connection between retailers/service providers and customers. Our teams strive to reinvent the way advertisers and agencies build brands and drive performance in their advertising. By using Amazon's foundation in e-commerce, we help brands connect with the right customers through creative solutions and formats across screens and devices, and in the physical world. Amazon Advertising seeks a Data Scientist with strong Data Analysis skills to join the ADSP engineering team split across Edinburgh and London. We make Guidance products that help optimise our customer's advertising campaign workflows and performance. As a scientist on the team, you will be involved in many aspects of the process - from idea generation, business analysis and scientific research, through to development - giving you a real sense of ownership. The systems that you help to build will operate at massive scale to advertising customers around the world. Our ideal candidate is an experienced Data scientist who has a track-record of performing analysis, applying statistical techniques and building basic ML models to solve real business problems, who has great leadership and communication skills, and who is motivated to achieve results in a fast-paced environment. Key job responsibilities Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both quantitative analysis and business judgment. Collaborate with software engineering teams to integrate successful experimental results into large-scale, highly complex Amazon production systems. Report results in a manner which is both statistically rigorous and compellingly relevant, exemplifying good scientific practice in a business environment. Promote the culture of experimentation at Amazon.

Amazon is looking for a passionate, talented, and inventive Applied Scientist with a strong machine learning background to help build industry-leading language technology. 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. Our mission is to provide a delightful experience to Amazon’s customers by pushing the envelope in Natural Language Processing (NLP), Generative AI, Large Language Model (LLM), Natural Language Understanding (NLU), Machine Learning (ML), Retrieval-Augmented Generation, Responsible AI, Agent, Evaluation, and Model Adaptation. As part of our AI team in Amazon AWS, you will work alongside internationally recognized experts to develop novel algorithms and modeling techniques to advance the state-of-the-art in human language technology. Your work will directly impact millions of our customers in the form of products and services, as well as contributing to the wider research community. You will gain hands on experience with Amazon’s heterogeneous text and structured data sources, and large-scale computing resources to accelerate advances in language understanding. The Science team at AWS Bedrock builds science foundations of Bedrock, which is a fully managed service that makes high-performing foundation models available for use through a unified API. We are adamant about continuously learning state-of-the-art NLP/ML/LLM technology and exploring creative ways to delight our customers. In our daily job we are exposed to large scale NLP needs and we apply rigorous research methods to respond to them with efficient and scalable innovative solutions. At AWS Bedrock, you’ll experience the benefits of working in a dynamic, entrepreneurial environment, while leveraging AWS resources, one of the world’s leading cloud companies and you’ll be able to publish your work in top tier conferences and journals. We are building a brand new team to help develop a new NLP service for AWS. You will have the opportunity to conduct novel research and influence the science roadmap and direction of the team. Come join this greenfield opportunity! About the team 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.

We are seeking a talented applied researcher to join the Whole Page Planning and Optimization (WPPO) Science team in Search. The latest data from Business Insider shows that almost 50% of online shoppers visit Amazon first. The Search WPPO Science team is responsible for developing reinforcement learning systems for the next generation Amazon shopping experience and delivering it to millions of customers. We believe that shopping on Amazon should be simple, delightful, and full of WOW moments for EVERYONE, whether you are technically savvy or new to online shopping. As an Applied Scientist, you will be working closely with a team of applied scientists and engineers to build systems that shape the future of Amazon's shopping experience by automatically generating relevant content and building a whole page experience that is coherent, dynamic, and interesting. You will improve ranking and optimization in our algorithm. You will participate in driving features from idea to deployment, and your work will directly impact millions of customers. You are going to love this job because you will: * Apply state-of-the-art Machine Learning (ML) algorithms, including Deep Learning and Reinforcement Learning, to improve hundreds of millions of customers’ shopping experience. * Have measurable business impact using A/B testing. * Work in a dynamic team that provides continuous opportunities for learning and growth. * Work with leaders in the field of machine learning.

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! Key job responsibilities We seek strong Applied Scientists with domain expertise in machine learning and deep learning, transformers, generative models, large language models, computer vision and multimodal models. You will devise innovative solutions at scale, pushing the technological and science boundaries. You will guide the design, modeling, and architectural choices of state-of-the-art large language models and multimodal models. You will devise and implement new algorithms and new learning strategies and paradigms. You will be technically hands-on and drive the execution from ideation to productionization. You will work in collaborative environment with other technical and business leaders, to innovate on behalf of the customer.

Do you have a passion for diving deep to uncover key insights that drive critical business decisions? If yes, the Marketing Incrementality and Decision Support (MIDS) team is looking for talented individuals with your enthusiasm and skills to work as part of the team. We are looking for a Senior Research Scientist with marketing measurement, experimentation and causal inference background, who is curious, driven, and passionate about marketing insights and analytics. The Customer Behavior Analytics (CBA) organization owns Amazon’s insights pipeline, from data collection to deep analytics. We aspire to be the place where Amazon teams come for answers, a trusted source for data and insights that empower our systems and business leaders to make better decisions. Our outputs shape Amazon product and marketing teams’ decisions and thus how Amazon customers see, use, and value their experience. MIDS’s mission is to make Amazon’s marketing the most measurably effective in the world. Our long-term objective is to measure the incremental impact of all Amazon’s marketing investments on consumer perceptions, actions, and sales. This requires measuring Amazon’s marketing comparably and consistently across channels, business teams and countries using a comprehensive approach that integrates all Paid, Owned and Earned marketing activity. As the experts on marketing performance, we will lead the Amazon worldwide marketing community by providing critical cross-country insights that can power marketing best practices and tenets globally. In this role, you will be a technical leader to design and run Randomized Control Trials and large-scale online experiments to measure the performance of Amazon's marketing cross all marketing channels, geographies and businesses. You will lead scientists and engineers to develop both experimental and observational models to understand customer behavior and how customers respond to Amazon’s advertisement. You will drive innovation to combine experiment results with observational model outputs to build more accurate marketing measurement solutions. You will lead strategic measurement science initiatives in MIDS and across various marketing teams, scaling experimentation and development and deployment of the measurement science models, real-time inference, and cross-channel orchestration. As a successful Research Scientist, you are an analytical problem solver who enjoys diving into data, leads problem solving, guides development of new frameworks, writes code, is excited about investigations and algorithms, and can credibly interface between technical teams and business stakeholders. You are an expert in causal inference and experiment design, preferably has experience leveraging experimental model to calibrate observational model. You are a hands-on innovator who can contribute to advancing Marketing measurement technology in a B2C and B2B environment, and push the limits on what’s scientifically possible with a razor sharp focus on measurable customer and business impact. You will coach and guide scientists in the team to grow the team’s talent and scale the impact of your work. You will also communicate verbally and in writing to business customers and leadership team with various levels of technical knowledge, educating them about our systems, as well as sharing insights and recommendations