Careers

The Digital Discovery team is part of the Digital Acceleration organization and is seeking a highly motivated, talented, and innovative Applied Scientist to drive the prototyping, optimization, and deployment of machine learning (ML) algorithms. These algorithms will be instrumental in enhancing the discovery of digital products and subscriptions across the Amazon platform. The Digital Discovery team is responsible for developing advanced algorithms and modeling techniques to acquire new customers and improve engagement for digital business including eBooks, Music, Audible, and Prime. In this pivotal role, you will leverage your expertise in machine learning and deep learning to build predictive models aimed at acquiring new customers and driving deeper engagement with existing customers across these digital offerings. This will involve developing propensity models for various digital products, optimizing targeting strategies for different placements, and identifying real-time customer digital interests. Collaborating closely with the engineering team, you will be responsible for the end-to-end lifecycle of these ML models - from architecture and training to production deployment. Your primary focus will be on uncovering customer pain points and devising novel, data-driven solutions to address them. This will require proposing hypotheses, validating them through offline experimentation, and ultimately running rigorous A/B tests to validate the online performance of your innovations. Throughout this process, you will develop production-ready code that can seamlessly integrate with the systems powering Amazon’s digital businesses. Your work will directly contribute to enhancing the discoverability and engagement of digital products and subscriptions. If you are a passionate, self-driven individual who thrives in a fast-paced, collaborative environment and is eager to push the boundaries of what’s possible in AI and ML, we encourage you to apply for this exciting opportunity on the Digital Discovery team. Key job responsibilities - Convert business problem in digital discovery into a Science problem to improve recommendation. - Work with Data Engineering and BI teams to identify features and build data pipelines. - Use and enhance ML Ops tools to train, validate, deploy, and compare the models with automatic retraining. - Explain model performance to tech and business leaders. - Work with peer community in Science to present, review and publish the model reports and papers. About the team Amazon Digital Acceleration powers ordering, subscriptions, and device management for Prime, Amazon Video, Music, Audible, Alexa, and Kindle, amongst other digital businesses. We process billions of digital purchases every year and enable our digital businesses to grow their businesses worldwide. We are on a mission to be earth's best provider of one-time and recurring digital commerce, delivering a seamless and enjoyable post-purchase customer experience.

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 forecasting, planning systems and robust decision making on large networks, as well as uncertainty quantification, generative models on graphs and ml explainability, among others. We are looking for an Applied 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.

Amazon is looking for world class Data Scientists (at all levels) to join its AWS AI Labs with expertise in AI-assistants focusing on conversational- retrieval augmented generation (RAG), agent orchestration, multi-modal and multi-lingual chat agents, etc. You will be joining a team of scientists developing robust and scalable machine learning solutions for enterprise conversational assistants. You will interact in a cross-functional capacity with product and engineering leaders, as well as 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 acclaimed engineers and world-class scientists. We are hiring scientists at all levels and at following locations: SEA, NYC and Santa Clara. About the team Amazon Q Business is a generative AI–powered assistant that can answer questions, provide summaries, generate content, and take actions, securely completing the tasks based on data and information in your enterprise systems. It empowers employees to be more creative, data-driven, efficient, prepared, and productive. As member of Q team, you’ll work on optimizing large language models in an efficient manner and implementing solutions to enhance and build new functionalities into Q assistant. 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 Robotics develops state-of-the-art robotics solutions to power Amazon's world-class Fulfillment Operations, which handle more single items than any other company. Our collaborative team is at the forefront of building automated manipulation products to handle and process packages and singular items. As a Data Scientist in the team, you will play a crucial role in driving data-powered decision making. Your main focus will be: * Developing predictive models and simulations to analyze complex, large-scale datasets and uncover insights to improve customer experience, cost efficiency, capital investment effectiveness, and automation utilization. * Creating compelling data visualizations that communicate end-to-end system performance and identify optimization opportunities. * Establishing robust data analysis frameworks and KPIs to quantify the impact of your solutions and evaluate tradeoffs between potentially contending goals. * Collaborating cross-functionally with engineering, operations, and business stakeholders to understand their needs, translate them into data-driven projects, and deliver impactful results. We're looking for an experienced, self-directed Data Scientist with a strong background in machine learning, data mining, and statistical analysis. You should have excellent problem-solving skills, the ability to work autonomously, and an enthusiasm for leveraging data to drive meaningful business outcomes. A day in the life 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 If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!

Amazon is looking for a passionate, talented, and inventive Applied Scientist with a strong machine learning background to join our science team in the area of Speech and Natural Language Processing. Our organization develops the science that drives the cloud-based AI services of AWS. Our mission is two-fold: to empower developers with powerful AI tools and to create delightful user experiences that solve real-world business problems. You'll have the opportunity to push the boundaries in Automatic Speech Recognition (ASR), Natural Language Processing (NLP), Natural Language Understanding (NLU), Generative AI, Large Language Model (LLM), and Machine Learning (ML). Prior domain knowledge in speech and natural language processing is preferred; Key job responsibilities As an Applied Scientist, you will partner with talented scientists and engineers to design, train, test, and deploy machine learning models. You will contribute to innovative features, improve our services based on customer requirements, and help maintain a highly scalable data and model management infrastructure that supports cutting-edge research. You will be responsible for translating business and engineering requirements into deliverables and software products. About the team About 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. Why AWS? Utility Computing (UC) 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.

The Artificial General Intelligence (AGI) team is seeking a dedicated, skilled, and innovative Applied Scientist with a robust background in deep learning, to build industry-leading technology with Large Language Models (LLMs) and multimodal systems. Key job responsibilities As part of the AGI team, an Applied Scientist will collaborate closely with talented colleagues to lead the development of advanced approaches and modeling techniques, driving forward the frontier of LLM technology. This includes innovating model-in-the-loop and human-in-the-loop approaches to ensure the collection of high-quality data, safeguarding data privacy and security for LLM training, and more. An Applied Scientist will also have a direct impact on enhancing customer experiences through state-of-the-art products and services that harness the power of speech and language technology. A day in the life An Applied Scientist with the AGI team will support the science solution design, run experiments, research new algorithms, and find new ways of optimizing the customer experience; while setting examples for the team on good science practice and standards. Besides theoretical analysis and innovation, an Applied Scientist will also work closely with talented engineers and scientists to put algorithms and models into practice. The ideal candidate should be passionate about delivering experiences that delight customers and creating robust solutions. They will also create reliable, scalable and high-performance products that require exceptional technical expertise, and a sound understanding of Machine Learning.

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day! The Customer - Advertiser Success & Insights (CASI) team is seeking an Applied Scientist to help increase the effectiveness of online advertising. You will leverage computer vision, generative AI, natural language processing, casual inference, and machine learning to enhance the customer experience with online advertising. In this role, you will collaborate closely with business leaders, stakeholders, and cross-functional teams to drive success for our customers through data-driven solutions. This is an excellent opportunity for a technically-minded individual to make a tangible impact on the online advertising landscape. The role offers the chance to work with state-of-the-art technologies and contribute to the evolution of a rapidly changing industry. Key job responsibilities As an Applied Scientist in CASI, you will: -> Shape the science roadmap for CASI, fostering a culture of data-driven decision-making. -> Deliver significant business impact through advanced ML models, generative AI, and cutting-edge causal inference methodologies. -> Produce and deliver models that help drive best-in-class customer experiences and build systems that allow us to deploy these models to production with low latency and high throughput. -> 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. -> Research new and innovative machine learning approaches.

How should Amazon adjust the customer experience (CX) based on the competitiveness of its prices? How can we balance between helping customers discover new products through lower prices, helping sellers promote, and being confident that our pricing consistently earns trust? Where should we show pricing depth versus selection breadth? This role will be the technical leader developing the mental model and data to answer these and related questions. The long term goal will be to propose and implement mechanisms to improve the customer journey from a price perspective, helping to use prices to prioritize between products, determining which information is displayed on the product (and how), and using prices to personalize of the CX to save customers money and time. The role will drive prioritization and implementation by generating value estimates of the impact of alternative decisions. A key component of the role is to develop the framework to guide prioritization and the expected impact from the proposed improvements, and use it to align efforts across different teams within and outside of the organization. An important component of the role is therefore to understand and quantify where price has more impact than other aspects of the CX. Most of the questions this role will advance are on the intersection of many other teams that contribute to the CX, and to Amazon’s price setting mechanisms. An important component of the role is to collaborate with the these science and product teams on improvements that will enable further optimization of the price-related CX. This role will be expected to drive several cross-org science and product initiatives, and be a significant contributor to others. Therefore, the role is expected to work closely with leaders and ICs across multiple orgs on scoping, planning, execution, and delivery. Key job responsibilities Today, we are missing a unified way to frame our traffic shaping actions in terms of their impact on the long-term customer CX. While we have conviction that we are doing the right thing, and our tenets are customer-obsessed, we lack the system which allows us to discern our interventions between good and great. This role will: - develop a framework to connect our measurements of price perception (UPEF, surveys, specific defect measurements like FOD) to our actions to protect the customer experience (badging, promoting, delisting) - produce quantifiable, explainable, measurements of good/bad CX which are used to calibrate this framework - develop a scientific roadmap which prioritizes the development based on the opportunity of using these measurements - partner with key scientific partners (Search, Stores Monetization) to stay connected to co-developments in related domains - Deliver the capability to begin to optimize our traffic shaping program by connecting our measurement inputs (price quality, promotional signals) to our customer and seller outputs (pricing LTV, OPS/CP) About the team The Pricing and Promotions Optimization Science (P2OS) team is a small unit of specialized science resources with deep expertise in optimization, machine learning, and microeconomics. We are equipped to solve some of the organization’s most ambiguous challenges to benefit Amazon customers and Sellers by optimizing business decision-making. This includes determining whether prices are set optimally according to measured customer demand and business objectives (Optimization), guaranteeing that promotions are incremental, using forecasting to recommend and rank the highest quality promotions are influence their schedule, amount, and type (Incrementality), and ensure our best prices and promotions are discoverable (Traffic Shaping).

The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Senior Applied Scientist with a strong deep learning background, to build industry-leading Generative Artificial Intelligence (GenAI) technology with Large Language Models (LLMs) and multimodal systems. Key job responsibilities As an Senior Applied Scientist with the AGI team, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art with LLMs. Your work will directly impact our customers. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in conversational AI. About the team Our team’s mission is to deliver general-purpose multimodal foundation models across a wide range of applications. We are responsible for building state-of-the-art general-purpose adaptable multimodal foundation models and advancing model architecture and optimization technologies at various stages of model building, including pre-training, context length extension, fine-tuning and post-training optimization/adaptation. We partner with other teams to achieve state-of-the-art performance. We support product teams to deliver innovative conversational AI solutions to a broad set of customers and use cases.

Amazon strives to be Earth's most customer-centric company where people can find and discover virtually anything they want to buy online. Amazon's evolution is driven by the spirit of innovation that is part of the company's DNA. Amazon Seller Services is looking for a Data Scientist to work hands on from concept to delivery on generative AI, statistical analysis, prescriptive and predictive analysis, and machine learning implementation projects. We are looking for a problem solver with strong analytical skills and a solid understanding of statistics & Machine learning algorithm as well as a practical understanding of collecting, assembling, cleaning and setting up disparate data from enterprise systems. Key job responsibilities Responsibilities: Ability to understand a business problem and the available data and identify what statistical or ML techniques can be applied to answer a business question Given a business problem, estimate solution feasibility and potential approaches based on available data Understand what data is available, where, and how to pull it together. Work with partner teams where needed to facilitate permissions and acquisition of required data Quickly prototype solutions and build models to test feasibility of solution approach Build statistical models/ ML models, train and test them to and drive towards the optimal level of model performance Improve existing processes with development and implementation of state of the art generative AI models Work with technology teams to integrate models by wrapping them as services that plug into Amazon's marketplace and fulfillment systems Work across the spectrum of reporting and data visualization, statistical modeling and supervised learning tools and techniques and apply the right level of solution to the right problem The problem set covers aspects of detecting fraud and abuse, improving performance, driving lift and adoption, recommend the right upsell to the right audience, cost saving, selection economics and several others.