Careers

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses. Amazon's advertising portfolio helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers. 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 ADSP Forecasting team's vision is to build the best in class forecasting products offered by any DSP to allow advertisers to forecast campaign outcomes across the full market funnel. Our goal is to empower advertisers using Amazon demand side platform to make informed decisions by providing predictions and recommendations of supply and ad-performance. Our forecasting models and analytical solutions will also help internal teams (sales, PSC, supply desk etc) to gain insights into forecasted supply, demand and ad performance to make the best business decisions. The team comprises scientists and engineers who own end-to-end projects - data collection, analysis, ideation, and prototyping, to development, metrics and monitoring. The models and services are integrated directly with Amazon's Ads eco system and the forecasts are used to drive key business decisions at the VP/SVP level. We are a team of Applied Scientists and Engineers, who are passionate about solving technical problems in the Ad Forecasting space with models using Machine Learning, Bayesian Statistics, etc. You will join a group of highly talented PhDs with diverse background to design, prototype, and implement models to deliver impact directly to customers. You will have the opportunity to present your work in science communities and to leadership As a Applied Scientist on this team, you will: - Be the technical leader in Machine Learning; lead efforts within this team and across other teams. - Perform hands-on analysis and modeling of enormous data sets to develop insights that increase traffic monetization and merchandise sales, without compromising the shopper experience. - Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity. - Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models. - Run A/B experiments, gather data, and perform statistical analysis. - Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving. - Research new and innovative machine learning approaches. Why you will love this opportunity: Amazon is investing heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate. 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 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

Amazon’s Last Mile Team is looking for a passionate individual with strong optimization and analytical skills to join its Last Mile Science team in the endeavor of designing and improving the most complex planning of delivery network in the world. Last Mile builds global solutions that enable Amazon to attract an elastic supply of drivers, companies, and assets needed to deliver Amazon's and other shippers' volumes at the lowest cost and with the best customer delivery experience. Last Mile Science team owns the core decision models in the space of jurisdiction planning, delivery channel and modes network design, capacity planning for on the road and at delivery stations, routing inputs estimation and optimization. Our research has direct impact on customer experience, driver and station associate experience, Delivery Service Partner (DSP)’s success and the sustainable growth of Amazon. Optimizing the last mile delivery requires deep understanding of transportation, supply chain management, pricing strategies and forecasting. Only through innovative and strategic thinking, we will make the right capital investments in technology, assets and infrastructures that allows for long-term success. Our team members 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, scientists, and software engineers in the industry. Key job responsibilities Candidates will be responsible for developing solutions to better manage and optimize delivery capacity in the last mile network. The successful candidate should have solid research experience in one or more technical areas of Operations Research or Machine Learning. These positions will focus on identifying and analyzing opportunities to improve existing algorithms and also on optimizing the system policies across the management of external delivery service providers and internal planning strategies. They require superior logical thinkers who are 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. To support their proposals, candidates should be able to independently mine and analyze data, and be able to use any necessary programming and statistical analysis software to do so. 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.

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. The Kuiper Global Capacity Planning team owns designing, implementing, and operating systems that support the planning, management, and optimization of Kuiper network resources worldwide. We are looking for a talented principal scientist to lead Kuiper’s long-term vision and strategy for capacity simulations and inventory optimization. This effort will be instrumental in helping Kuiper execute on its business plans globally. As one of our valued team members, you will be obsessed with matching our standards for operational excellence with a relentless focus on delivering results. Key job responsibilities In this role, you will: Work cross-functionally with product, business development, and various technical teams (engineering, science, R&D, simulations, etc.) to establish the long-term vision, strategy, and architecture for capacity simulations and inventory optimization. Design and deliver modern, flexible, scalable solutions to complex optimization problems for operating and planning satellite resources. Lead short and long terms technical roadmap definition efforts to predict future inventory availability and key operational and financial metrics across the network. Design and deliver systems that can keep up with the rapid pace of optimization improvements and simulating how they interact with each other. Analyze large amounts of satellite and business data to identify simulation and optimization opportunities. Synthesize and communicate insights and recommendations to audiences of varying levels of technical sophistication to drive change across Kuiper. Export Control Requirement: Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum.

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!

Disrupting the way Amazon fulfills our customers’ orders. Amazon operations is changing the way we improve Customer Experience through flawless fulfillment focused on 1) successful on-time delivery, 2) at speed and 3) at the lowest possible cost. Being the engine of Amazon Operational excellence, driving zero defects through ideal operation, being the heart of the Fulfillment network and its center of excellence, being proactive and aspiring for zero defects across the network with 100% organizational engagement. For example, our applied science team leverage a variety of advanced machine learning and cloud computing techniques to power Amazon's operations performance management. This includes building algorithms and cloud services using LLMs, deep neural networks, and other ML approaches to make root cause analysis of incidents and defects better. They develop machine learning models to predict inbound capacity forecasts and select the optimal order of unloading and stowing the incoming items in the Fulfilment Center. The teams also utilize Langchain, Amazon Bedrock, Amazon Textract, ElasticCache Redis, Opensearch and Kubernetes to extract insights from big data and deliver recommendations to operations managers, continuously improving through offline analysis and impact evaluation. Underpinning these efforts are unique technical challenges, such as operating at unprecedented scale (100k requests per second with SNS/SQS and <1ms latency with Redis) while respecting privacy and customer trust guarantees, and solving a wide variety of complex computational operational problems related to inbound management for unloading and stowing before stow time SLA, outbound for picking and packing before SLAM PAD time and shipping for staging and loading before Critical Pull Time. Key job responsibilities GOX team is looking for a Senior Applied Scientist to support our vision of giving our customers the best fulfillment experience in the world, and our mission of delighting our customers by providing capabilities, tools and mechanisms to fulfillment operations. As Skynet Sr. APSCI, you would be providing resources and expertise for all data related reports (dashboard, scorecards…), analysis (statistical approach), and Machine Learning products and tools development. On top of your internal customers within GOX team you would be supporting more widely with your experience and skills all across the org, partnering with a wide range of departments within Ops Integration (Packaging, Sustainability) within the company mainly with ICQA, ATS, AMZL, GTS… on several projects. You will be part of the community of Scientists within Amazon Operations including other AS, BIEs, SDEs, … split across the different departments. You will be part of projects requiring your close collaboration and interactions with Operations that require you to have a good understanding of product flow and process all along the distribution chain. The GOX team is now recognized for its expertise and excellence in creating tools that improve massively the customer experience. Several of them now rolled out in other regions with some of these tools becoming worldwide standard. Reporting to the GOX Senior Manager, you will be responsible for developing the data-driven decision process from historical data and ML based predictive analysis and maintaining accurate and reliable data infrastructure. You will work across the entire business, and be exposed to a wide range of functions from Operations, Finance, Technology, and Change management. The successful candidate will be able to work with minimal instruction and oversight, manage multiple tasks and support projects simultaneously. Maintaining your relationships with the customers in operations and within the team, while owning deliverables end-to-end is expected. Critical to the success of this role is your ability to work with big data, develop insightful analysis, communicate findings in a clear and compelling way and work effectively as part of the team, raising the bar and insisting on high standards. About the team GOX DEA team is the engine of Amazon Operational excellence at the heart of the fulfillment network operations, aspiring zero defects. It is our purpose to improve Customer Experience through flawless fulfillment focused on 1) successful on-time delivery, 2) at speed and 3) at the lowest possible cost. Our Solutions support on-time delivery of billions of packages to our customers across the globe leveraging AI & Generative AI technology.

The Alexa Smart Home team is focused on making Alexa the user interface for the home. From the simplest voice commands (turn on the lights, turn down the heat) to use cases spanning home security, home entertainment, and the home environment; we are evolving Alexa into an intelligent, indispensable companion that automates daily routines, simplifies interaction with appliances and electronics, and alerts when something unusual is detected. You can be part of a team delivering features that are highly anticipated by media and well received by our customers. As an Applied Scientist, you will work with other scientists and software developers to design and build the next generation of Smart Home voice control using the latest Large Language Models (LLMs). And, you will have the satisfaction of working on a product your friends and family can relate to, and want to use every day. Key job responsibilities - Develop new inference and training techniques to improve the performance of LLMs for Smart Home control and Automation - Develop robust techniques for synthetic data generation for training large models and maintaining model generalization - Mentoring junior scientists to improve their skills, knowledge, and their ability to get things done About the team We are a team of Scientists, Machine Learning Engineers, and Software Developers that work together to make Alexa more insightful and proactive through ambient intelligence, with features like Alexa Hunches that automatically control Smart Home devices. We are interdisciplinary and we act like it. We ask each other questions and value our different perspectives.

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

Do you want to join an innovative team of scientists who use machine learning and statistical techniques to help Amazon provide the best customer experience by protecting Amazon customers from hackers and bad actors? Do you want to build advanced algorithmic systems that help manage the trust and safety of millions of customer every day? Are you excited by the prospect of analyzing and modeling terabytes of data and create state-of-art algorithms to solve real world problems? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Amazon Account Integrity team. The Amazon Account Integrity team works to ensure that customers are protected from bad actors trying to access their accounts. Our greatest challenge is protecting customer trust without unjustly harming good customers. To strike the right balance, we invest in mechanisms which allow us to accurately identify and mitigate risk, and to quickly correct and learn from our mistakes. This strategy includes continuously evolving enforcement policies, iterating our Machine Learning risk models, and exercising high‐judgement decision‐making where we cannot apply automation. Main responsibilities - Use statistical and machine learning techniques to create scalable risk management systems - Analyzing and understanding large amounts of Amazon’s historical business data for specific instances of risk or broader risk trends - Design, development and evaluation of highly innovative models for risk management - Working closely with software engineering teams to drive real-time model implementations and new feature creations - Working closely with operations staff to optimize risk management operations - Establishing scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation - Tracking general business activity and providing clear, compelling management reporting on a regular basis - Research and implement novel machine learning and statistical approaches

At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our mission is to prevent denied entities from transacting with Amazon businesses. We build automatic mechanisms to detect and prevent prohibited transactions with denied entities using a diverse set of algorithms and machine learning techniques. We screen over a billion events every day and develop algorithms which are able to scale and detect suspicious entities . We are still Day 1 and have an exciting road map to build Machine Learning (ML) and Generative AI (LLM) powered detection and resolution systems to help scale Amazon for years to come. We are seeking an outstanding Applied Scientist to join our team and help tackle challenging problems at the forefront of machine learning and artificial intelligence. Working closely with a multidisciplinary team of engineers, data scientists, and domain experts, you will play a crucial role in defining cutting-edge ML/AI-powered customer experiences and solutions. If you have an entrepreneurial mindset, the technical depth to deliver impactful results, and a passion for innovation, we want to hear from you. Key job responsibilities In this role, you will: • Drive the research, design, and development of novel ML/AI models and systems to power critical products and services • Collaborate cross-functionally to deeply understand business requirements, customer needs, and technical constraints • Rapidly prototype, test, and iterate on ML/AI solutions, iterating quickly based on data and feedback • Communicate complex technical concepts to technical and non-technical stakeholders • Mentor and grow a team of talented ML scientists and engineers • Stay up-to-date on the latest advancements in AI/ML and identify opportunities to apply emerging techniques A day in the life 1. Starting the day by reviewing the latest model performance metrics and identifying areas for improvement 2. Brainstorming new ML architectures and approaches with your cross-functional team during a whiteboard session 3. Diving deep into a complex dataset, leveraging advanced statistical and ML techniques to uncover hidden insights 4. Prototyping a new ML model and running a series of experiments to optimize its performance 5. Preparing a presentation to pitch your latest research findings and recommendations to product and engineering leaders 6. Mentoring a junior data scientist, providing guidance on coding best practices and problem-solving strategies About the team Why Amazon Security At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon’s products and services. 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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve. Inclusive Team Culture In Amazon Security, it’s in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices. Training 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, training, and other career-advancing resources here to help you develop into a better-rounded professional.

Have you ever wanted to be part of a team that is building industry changing technology? Amazon’s Project Kuiper is an initiative to launch a constellation of Low Earth Orbit satellites that will provide low-latency, high-speed broadband network connectivity to unserved and underserved communities around the world. The Kuiper Business Solutions team owns a suite of products and services to operate and scale Kuiper. We are looking for a passionate, talented, and inventive Data Scientist with a background in AI, Gen AI, Machine Learning, NLP, to lead delivering best in class automated customer service and business analytic solutions for Kuiper Customer Service. As a Data Scientist, you will be responsible for the development, fine-tuning, and evaluation of AI models that power our chatbot and IVR solutions. Your work will ensure the chatbot and IVR is accurate, reliable, and continually improving to meet customer needs. This role involves collaborating with cross-functional teams to integrate AI solutions into our customer service platform, monitor their performance, and implement ongoing enhancements. The ideal candidate has experience in successfully building chat bots using AI technologies, measuring their performance and delivering ongoing improvements. Export Control Requirement: Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum. Key job responsibilities * Build and validate data pipelines for training and evaluating the LLMs * Extensively clean and explore the datasets * Train and evaluate LLMs in a robust manner * Design and conduct A/B tests to validate model performance * Automate model inference on AWS infrastructure