Careers

Amazon continues to invest heavily in building our world class advertising business. 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, breaking fresh ground to create world-class products. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and strong bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities. The Sponsored Products Monetization team is broadly responsible for pricing of ads on Amazon search pages, balancing short-term and long-term ad revenue growth to drive sustainable marketplace health. As a Senior Applied Scientist on our team, you will be responsible for defining the science and technical strategy for one of our most impactful marketplace controls, creating lasting value for Amazon and our advertising customers. You will help to identify unique opportunities to create customized and delightful shopping experience for our growing marketplaces worldwide. Your job will be identify big opportunities for the team that can help to grow Sponsored Products business working with retail partner teams, Product managers, Software engineers and PMs. You will have opportunity to design, run and analyze A/B experiments to improve the experience of millions of Amazon shoppers while driving quantifiable revenue impact. More importantly, you will have the opportunity to broaden your technical skills in an environment that thrives on creativity, experimentation, and product innovation. Key job responsibilities - Lead science, tech and business strategy and roadmap for Sponsored Products Monetization - Drive alignment across multiple organizations for science, engineering and product strategy to achieve business goals - Lead and mentor scientists and engineers across teams to develop, test, launch and improve of science models designed to optimize the shopper experience and deliver long term value for Amazon and advertisers - Develop state of the art experimental approaches and ML models - Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity - 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 - Recruit Scientists to the team and provide mentorship

** This position is open to all candidates in 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.

Amazon Web Services (AWS) offers a broad set of global compute, storage, database, analytics, application, and deployment services that help organizations move faster, lower IT costs, and scale applications. These services are trusted by the largest enterprises and the hottest start-ups to power a wide variety of workloads including web and mobile applications, data processing and warehousing, storage, archive, and many others. We are looking for an applied scientist to help us define and build a new enterprise application. AWS Applications is building services in Supply Chain Management and is looking for a scientist to tackle complex science problems in Supply Chain including demand planning, supply planning and sustainability which will be used by our customers across a wide range of industries. We operate a fast growing business and our journey has only started. Our mission is to build the most efficient and optimal supply chain software on the planet, using our science and technology as our biggest advantage. We aim to leverage cutting edge technologies in optimization, operations research, and machine learning to grow our businesses. As an Applied Scientist, you’ll design, model, develop and implement state-of-the-art models and solutions used by users worldwide. As part of your role you will regularly interact with software engineering teams and business leadership. The focus of this role is to research, develop, and deploy models to improve state-of-the-art for time series. You will have the opportunity to work on our assistant solution allowing our users to ask data questions in natural language and get intelligent insights and exceptions. Key job responsibilities Lead and partner with the engineering to drive modeling and technical design for complex business problems. Develop accurate and scalable machine learning models to solve our hardest supply chain problems. Lead complex modeling analyses to aid management in making key business decisions and set product direction. A day in the life 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.

Project Kuiper is an initiative to increase global broadband access through a constellation of 3,236 satellites in low Earth orbit (LEO). Its mission is to bring fast, affordable broadband to unserved and underserved communities around the world. Project Kuiper will help close the digital divide by delivering fast, affordable broadband to a wide range of customers, including consumers, businesses, government agencies, and other organizations operating in places without reliable connectivity. Key job responsibilities This position is part of the Satellite Attitude Determination and Control team. You will design and analyze the control system and algorithms, support development of our flight hardware and software, help integrate the satellite in our labs, participate in flight operations, and see a constellation of satellites flow through the production line in the building next door. You will design and analyze algorithms for estimation, flight control, and precise pointing using linear methods and simulation. Along with that will be plenty of work developing and applying models and simulations, with various levels of fidelity, of the satellite and our constellation. The labs in our building provide for component level environmental testing, functional and performance checkout, subsystem integration, and satellite integration up to Day in the Life testing and mission rehearsal. We are excited to get into space, so you can look forward to seeing your designs launch and fly soon! A day in the life This is an opportunity to play a significant role in the design of an entirely new satellite system with challenging performance requirements. The large, integrated constellation brings opportunities for advanced capabilities that need investigation and development. The constellation size also puts emphasis on engineering excellence so our tools and methods, from conceptualization through manufacturing and all phases of test, will be state of the art as will the satellite and supporting infrastructure on the ground. You will find that Kuiper's mission is compelling, so our program is staffed with some of the top engineers in the industry. Our daily collaboration with other teams on the program brings constant opportunity for discovery, learning, and growth. About the team Our team has lots of experience with various satellite systems and many other flight vehicles. We have bench strength in both our mission and core GNC disciplines. We design, prototype, test, iterate and learn together. Because GNC is central to safe flight, we tend to drive Concepts of Operation and many system level analyses.

The Campaign Measurement & Optimization (CMO) organization is looking for a Senior Applied Scientist interested in solving one of the most challenging business problems in marketing measurement and optimization, a thought leader with deep expertise in ML modeling, and scaling measurement science. Working with our team of data / research / applied scientists, economists, engineers, and product managers, this leader will help redefine marketing investment decision making at Amazon and its subsidiaries. The Campaign Measurement & Optimization (CMO) organization’s mission is to be the most trusted source of measurement science solutions to drive marketing investment decisions across Amazon. The CMO team provides incrementality and efficiency measurement services to the marketing stakeholders across Amazon’s lines of business, including Stores, Prime Video, Amazon Devices, Alexa, Amazon Business, Amazon Music, Amazon Fresh, as well as subsidiaries including Audible, Ring, Whole Foods, and more. CMO applies industry leading deep learning based causal inference models to measure omni-channel effectiveness of marketing campaigns from these businesses worldwide. The impact and influence of the organization is tremendous, helping optimize spend decisions on a scale that exceeds many countries’ GDP. Our outputs shape Amazon product and marketing teams’ decisions and therefore how Amazon customers see, use, and value their experience with Amazon. This is a high-impact role with opportunities to develop systems and analyze marketing effectiveness that contributes billions of dollars to the business. As a Senior Scientist in the team, you will be responsible for designing and developing cutting edge measurement and optimization models, while collaborating with businesses, marketers, and software teams to solve key challenges facing the teams. Such challenges include measuring the incremental impact of multi-billion $$ multi-channel marketing portfolios, developing Deep Learning models for estimating the impact on sparse customer actions, and scaling measurement solutions for WW marketplaces. Unlike many companies who buy existing off-the-shelf marketing measurement systems, we are responsible for studying, designing, and building systems to serve Amazon’s suite of businesses. Our team members have an opportunity to be on the forefront of marketing measurement thought leadership by working on some of the most difficult problems in the industry with some of the best product managers, research scientists, economists and software developers in the business. In this role, you will be a technical leader in Marketing science research with significant scope, impact, and high visibility. You will champion cutting edge ML models using the latest methods in causal estimation and portfolio optimization. You will lead strategic measurement science initiatives in CMO and across various marketing teams, scaling experimentation and measurement science models, real-time inference, and cross-channel orchestration. As a successful scientist, you are an analytical problem solver who enjoys diving into data, leads development of new models, is excited about investigations and algorithms, and can credibly interface between technical teams and business stakeholders. You are an expert in employing deep learning models to solve business problems, preferably in causal inference. 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 junior scientists to grow the team’s talent and scale the impact of your work.

Revolutionize the Future of FinTech with Worldwide Installments Science & Engineering! Are you ready to shape the future of global finance? Join the elite Worldwide Installments team within Amazon Payments (AP) and be at the forefront of innovation where cutting-edge machine learning, advanced econometrics, and state-of-the-art technology converge to redefine the financial landscape. 🌟 Our Mission: To create payment experiences and financial services that are unparalleled in trust, value, and ease of use – accessible from anywhere, anytime. 🚀 What We Offer: - Unprecedented growth in a rapidly expanding market - Continuous innovation with market-leading features - Groundbreaking ML solutions that directly impact customers 🧠 Your Playground: - Access to Amazon's vast data ecosystem - Cutting-edge probabilistic modeling - Real-time decision-making systems affecting millions - Global-scale experimentation and optimization 🌍 Your Impact: - Influence the purchasing experience of hundreds of millions of consumers worldwide - Work on the most sophisticated FinTech challenges in the BNPL/Installment space - Collaborate with top-tier professionals across Amazon's global network 🔍 We're Seeking: An exceptional talent to spearhead our ML roadmap. This role is your gateway to working with one of the world's most complex and extensive data environments. You'll be at the nexus of data, strategy, and innovation, directly influencing Amazon's global financial strategies. 💼 Your Arsenal: - Mastery in managing and deriving insights from massive datasets - Deep expertise in scalable data mining and financial modeling - Strong business acumen and superior communication skills - Ability to translate complex data into actionable business strategies 🏆 Why This Role is Unmatched: This position offers unparalleled exposure to the pinnacle of FinTech innovation. You'll be working on challenges that no other company in the world can offer, with resources and scale that are truly unique to Amazon. Join us in revolutionizing global finance. Your expertise could shape how millions of people interact with money in the digital age. This isn't just a job – it's a chance to leave your mark on the future of financial technology. Are you ready to redefine what's possible in FinTech? Apply now and let's build the future together!

Your primary responsibility as a Survey Research Scientist on the Reputation Marketing & Insights team will be to provide research support for our internal employee communications tracking survey. You will be responsible for conducting basic and advanced modeling on attitudinal and perception-based survey data, as well as developing the mechanisms to ensure statistical rigor in our sampling, weighting, and measurement practices. You will dive deep into data, establish strategic territories, and identify audience opportunities in order to guide the broader Internal Corporate Communications team. The work will challenge you to be resourceful, think big while staying connected to the details, translate advanced analytics into strategic direction, and embrace a high degree of change and ambiguity at speed. The scope and scale of what we strive to achieve is immense, but it is also meaningful and energizing. This is an individual contributor role. Key job responsibilities - Conduct basic and advanced modeling on survey data (e.g., regression, structural equation modeling, latent growth curve modeling, Shapley analysis, etc.) - Design new studies and mechanisms to measure the perception impact of internal communications - Develop experiments to improve survey design, data quality, and drive causal learnings - Write code to generate data tables and charts - Manage the data ingestion pipeline, maintain, and improve existing data dashboard - Engage in strategic discussions with partner teams to ensure our research generates actionable and on-point findings - Identify messaging opportunities and inform internal communication strategies that will drive primary KPIs About the team This team sits within the Communications and Corporate Responsibility (CCR) organization. Our focus is on conducting research that tracks reputational trends on a global scale and informs communication strategies for Amazon as a brand.

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 Senior Machine Learning Applied Scientist who loves to innovate at the intersection of customer experience, deep learning, and high-scale machine-learning systems. This role will focus on driving the technical direction of ML solutions to connect customs with right products. 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 Senior 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 an Senior Machine Learning Applied Scientist, you will: * Conduct hands-on data analysis, build large-scale machine-learning models and pipelines * Work closely with software engineers on detailed requirements, technical designs and implementation of end-to-end solutions in production * Run regular A/B experiments, gather data, perform statistical analysis, and communicate the impact to senior management * Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving * Provide technical leadership, research new machine learning approaches to drive continued scientific innovation * Be a member of the Amazon-wide Machine Learning Community, participating in internal and external MeetUps, Hackathons and Conferences Help attract and recruit technical talent

Do you want to be part of the team developing the future technology that impacts the customer experience of ground-breaking products? Then come join us and make history. We are looking for a passionate, talented, and inventive Applied Scientist with a background in AI, Gen AI, Machine Learning, NLP, to help build LLM solutions for Amazon core shopping. Our team works on a variety of projects, including state of the art generative AI, LLM finetuning, alignment, prompt engineering, benchmarking solutions. Key job responsibilities As an Applied Scientist will be expected to work on state of the art technologies which will result in papers publications, however you will not be only theorizing about the algorithms, but you will also have the opportunity to implement them and see how they behave in the field. This is an incredible opportunity to validate your research on one of the most exciting Amazon AI products, where assumptions can be tested against real business scenarios and supported by an abundance of data.

The Artificial General Intelligence (AGI) team is looking for a Senior Applied Scientist to work on pre-training methodologies for Generative Artificial Intelligence (GenAI) models. You will interact closely with our customers and with the academic and research communities. You will be at the heart of a growing and exciting focus area for Amazon, working with other acclaimed engineers and world-famous scientists. Key job responsibilities Join us to work as an integral part of a team that has diverse experience with GenAI models in this space. We work on these areas: - Scaling laws - Hardware-informed efficient model architecture, low-precision training - Optimization methods, learning objectives, curriculum design - Deep learning theories on efficient hyperparameter search and self-supervised learning - Reasoning, self-reflection, interactive learning, data synthesis - Distributed training methods and solutions About the team The AGI team has a mission to push the envelope in LLMs and multimodal systems, in order to provide the best-possible experience for our customers.