Careers

Are you seeking an environment where you can drive innovation? Do you want to be at the forefront of solving the toughest real-world supply chain problems? Do you want to play a key role in the future of Amazon's Stores business? Come and join us! Supply Chain Optimization Technologies (SCOT) owns Amazon's global inventory planning systems. We decide what, when, where, and how much we should buy to meet Amazon's business goals and to make our customers happy. We decide how to place and move inventory within Amazon's fulfillment network. We do this for hundreds of millions of items and hundreds of product lines worth billions of dollars worldwide. Check our website if you are curious to learn more about the breadth of problems we tackle: https://www.amazon.science/tag/supply-chain-optimization-technologies We are seeking a Sr. Manager of Applied Science with expertise in Statistical Machine Learning and/or Reinforcement Learning to drive research, development, and deployment of AI technology that empowers SCOT to build, run, and continuously improve the world's most efficient supply chain. To achieve this goal, we accelerate ML / RL software adoption through our partnerships and infrastructure. In this role, you will manage a team of scientists tasked researching the next generation of solutions to power buying, placement, and fulfillment decisions, while translating customer needs into reusable software infrastructure that accelerates adoption and deployment. Key job responsibilities - Lead technical innovation in reinforcement learning applications for complex supply chain environments, solving unique challenges and ensuring practical implementation in real-world deployments. - Build and develop a high-performing team by fostering collaboration, mentoring top talent, and creating a balanced culture of technical excellence. - Bridge technical possibilities with business requirements by providing strategic judgment, evaluating technology feasibility, and managing implementation risk. - Drive cross-functional collaboration by interfacing with product teams, leadership, and partner organizations to translate business needs into technical solutions.

The Ads Measurement Science team in the Measurement, Ad Tech, and Data Science (MADS) team of Amazon Ads serves a centralized role developing solutions for a multitude of performance measurement products. We create solutions which measure the comprehensive impact of advertiser's ad spend, including sales impacts both online and offline and across timescales, and provide actionable insights that enable our advertisers to optimize their media portfolios. We also own the science solutions for AI tools that unlock new insights and automate high-effort customer workflows, such as custom query and report generation based on natural language user requests. We leverage a host of scientific technologies to accomplish this mission, including Generative AI, classical ML, Causal Inference, Natural Language Processing, and Computer Vision. As an Applied Scientist on the team, you will lead measurement solutions end-to-end from inception to production. You will propose, design, analyze, and productionize models to provide novel measurement insights to our customers. Key job responsibilities - Leverage deep expertise in one or more scientific disciplines to invent solutions to ambiguous ads measurement problems - Disambiguate problems to propose clear evaluation frameworks and success criteria - Work autonomously and write high quality technical documents - Implement a significant portion of critical-path code, and partner with engineers to directly carry solutions into production - Partner closely with other scientists to deliver large, multi-faceted technical projects - Share and publish works with the broader scientific community through meetings and conferences - Communicate clearly to both technical and non-technical audiences - Contribute new ideas that shape the direction of the team's work - Mentor more junior scientists and participate in the hiring process About the team We are a team of scientists across Applied, Research, Data Science and Economist disciplines. You will work with colleagues with deep expertise in ML, NLP, CV, Gen AI, and Causal Inference with a diverse range of backgrounds. We partner closely with top-notch engineers, product managers, sales leaders, and other scientists with expertise in the ads industry and on building scalable modeling and software solutions.

Are you interested in defining the science strategy that enables Amazon to market to millions of customers based on their lifecycle needs rather than one-size-fits-all campaigns? We are seeking a Senior Applied Scientist to lead the science strategy for our Lifecycle Marketing Experimentation roadmap within the PRIMAS (Prime & Marketing analytics and science) team. The position is open to candidates in Amsterdam and Barcelona. In this role, you will own the end-to-end science approach that enables EU marketing to shift from broad, generic campaigns to targeted, cohort-based marketing that changes customer behavior. This is a high-ambiguity, high-impact role where you will define what problems are worth solving, build the science foundation from scratch, and influence senior business leaders on marketing strategy. You will work directly with Business Directors and channel leaders to solve critical business problems: how do we win back customers lost to competitors, convert Young Adults to Prime, and optimize marketing spend by de-averaging across customer cohorts. Key job responsibilities Science Strategy & Leadership: 1. Own the end-to-end science strategy for lifecycle marketing, defining the roadmap across audience targeting, behavioral modeling, and measurement 2. Navigate high ambiguity in defining customer journey frameworks and behavioral models – our most challenging science problem with no established playbook 3. Lead strategic discussions with business leaders translating business needs into science solutions and building trust across business and tech partners 4. Mentor and guide a team of 2-3 scientists and BIEs on technical execution while contributing hands-on to the hardest problems Advanced Customer Behavior Modeling: 1. Build sophisticated propensity models identifying customer cohorts based on lifecycle stage and complex behavioral patterns (e.g., Bargain hunters, Young adults Prime prospects) 2. Define customer journey frameworks using advanced techniques (Hidden Markov Models, sequential decision-making) to model how customers transition across lifecycle stages 3. Identify which customer behaviors and triggers drive lifecycle progression and what messaging/levers are most effective for each cohort 4. Integrate 1P behavioral data with 2P survey insights to create rich, actionable audience definitions Measurement & Cross-Workstream Integration: 1. Partner with measurement scientist to design experiments (RCTs) that isolate audience targeting effects from creative effects 2. Ensure audience definitions, journey models, and measurement frameworks work coherently across Meta, LiveRamp, and owned channels 3. Establish feedback loops connecting measurement insights back to model improvements About the team The PRIMAS (Prime & Marketing Analytics and Science) is the team that support the science & analytics needs of the EU Prime and Marketing organization, an org that supports the Prime and Marketing programs in European marketplaces and comprises 250-300 employees. The PRIMAS team, is part of a larger tech tech team of 100+ people called WIMSI (WW Integrated Marketing Systems and Intelligence). WIMSI core mission is to accelerate marketing technology capabilities that enable de-averaged customer experiences across the marketing funnel: awareness, consideration, and conversion.

The Artificial General Intelligence (AGI) Foundations team is looking for a passionate, talented, and inventive Principal ML Engineer with strong machine learning background, to lead the development of industry-leading technology. As a Principal Software Engineer, ML within the Artificial General Intelligence (AGI) organization, you are a trusted part of the technical leadership. You bring business and industry context to technology decisions. You will be responsible for leading the development of novel algorithms and techniques to advance the state of Large Language Model (LLM) training. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate development of multimodal Large Language Models and Generative Artificial Intelligence solutions. You will collaborate closely with the Applied Scientists on LLM reinforcement learning techniques to build production training workflows. You set the standard for engineering excellence and make decisions that affect the way we build and integrate algorithms. Your solutions are exemplary in terms of system design, clarity, efficiency, and extensibility. You tackle intrinsically hard problems; you're interested in learning; and you acquire skills and expertise as needed. Your expertise is deep and broad; you’re hands on, producing both detailed technical work and high-level architectural designs. You help managers guide the career growth of other engineers by mentoring and play a significant role in hiring and developing engineers and leads. You will play a critical role in driving the development of Generative AI (GenAI) technologies that can handle Amazon-scale use cases and have a significant impact on our customers' experiences. Key job responsibilities Serve as a technical lead on our most demanding, cross-functional projects. Ensure the quality of architecture and design of systems. Functionally decompose complex problems into simple, straight-forward solutions. Fully and completely understand system interdependencies and limitations. Possess expert knowledge in performance, scalability, enterprise system architecture, and engineering best practices. Leverage knowledge of internal and industry prior art in design decisions. Effectively research and benchmark Amazon technology against other competing systems in the industry. Contribute intellectual property through patents. Assist in the career development of others, actively mentoring individuals and the community on advanced technical issues and helping managers guide the career growth of their team members. Exert technical influence over multiple teams, increasing their productivity and effectiveness by sharing your deep knowledge and experience.

Do you have a passion for data? Are you matriculating in a Master’s or PhD program? Amazon is looking for driven data science students with strong modeling skills who are comfortable owning and executing data. To be successful in this internship, you will need the ability to develop, automate, and run analytical models for our systems. During this internship, you will build tools and support structures needed to analyze and dive deep into data to resolve systems errors and changes. You will have the ability to present your findings to our business partners and help drive improvements. Previous applicants demonstrated the aptitude to manage medium-scale modeling projects, identified requirements, and built methodology/tools that were statistically grounded. For more information on the Amazon Science community please visit https://www.amazon.science

About Sponsored Products and Brands The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry leading generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. About our team The Gnome team within the Sponsored Products and Brands (SPB) improves ad selection helping shoppers reach their shopping mission. To do this, we apply a broad range of machine learning, causal inference, reinforcement learning based optimization techniques and LLMs to continuously explore, learn, and optimize ads shown. We are an interdisciplinary team with a focus on customer obsession and inventing and simplifying. Our primary focus is on improving the ads experience by gaining a deep understanding of shopper pain points and developing new innovative solutions to address them. A day in the life As a Senior Applied Scientist on this team, you will be responsible to improve quality of ads shown using in-session and offline signals via online experimentation, ML modeling, simulation, and online feedback. As an Applied Scientist on this team, you will identify big opportunities for the team to make a direct impact on customers and the search experience. You will work closely with with search and retail partner teams, software engineers and product managers to build scalable real-time ML solutions. You will have the opportunity to design, run, and analyze A/B experiments that improve the experience of millions of Amazon shoppers while driving quantifiable revenue impact while broadening your technical skillset. #GenAI

Ever wonder how you can keep the world’s largest selection also the world’s safest and legally compliant selection? Then come join a team with the charter to monitor and classify the billions of items in the Amazon catalog to ensure compliance with various legal regulations. The Classification and Policy Platform team is looking for Applied Scientists to build technology to automatically monitor the billions of products on the Amazon platform. The software and processes built by this team are a critical component of building a catalog that our customers trust. You will have an opportunity to work with machine learning algorithms on large datasets. You will need to build Amazon scale applications running on Amazon Cloud that both leverage and create new technologies to process large volumes of data that derive patterns and conclusions from the data. We are looking for highly motivated applied scientists and engineers interested in delivering the next level of innovation to product search for Amazon. As an Applied Scientist on the CPP team, you will be responsible for working across backend, client, business development, and data engineering teams to coordinate deep-dives, inform roadmaps, visualize metrics, and create predictive models to determine how we can best serve our customers. Key job responsibilities Designing and implementing new features and machine learned models, including the application of state-of-art deep learning to solve search matching and ranking problems, including filtering, new content indexing, and apply document understanding Conducting and coordinating process development leading to improved and streamlined processes for model development. Strong customer focus is essential Working closely with Product Managers to expand depth of our product insights with data, create a variety of experiments, and determine the highest-impact projects to include in planning roadmaps Providing technical and scientific guidance to your team members Communicating effectively with senior management as well as with colleagues from science, engineering, and business backgrounds Being a cultural leader that ensures teams are collecting, understanding, and using data to inform every decision that impacts our customers The successful candidate will have an established background in developing customer-facing experiences, a strong technical ability, a start-up mentality, excellent project management skills, and great communication skills. Amazon Science gives you insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work. Please visit https://www.amazon.science for more information.

We are scaling an advanced team of talented Machine Learning Scientists in Melbourne. This is your chance to join our a wider international community of ML experts changing the way our customers experience Amazon. Amazon's International Machine Learning team partners with businesses across the diverse Amazon ecosystem to drive innovation and deliver exceptional experiences for customers around the globe. Our team works on a wide variety of high-impact projects that deliver innovation at global scale, leveraging unrivalled access to the latest technology, whilst actively contributing to the research community by publishing in top machine learning conferences. As part of Amazon's Research and Development organization, you will have the opportunity to push the boundaries of applied science and deploy solutions that directly benefit millions of Amazon customers worldwide. Whether you are exploring the frontiers of generative AI, developing next-generation recommender systems, or optimizing agentic workflows, your work at Amazon has the power to truly change the world. Join us in this exciting journey as we redefine the present and the future of innovative applied science. Key job responsibilities - You will take on complex problems, work on solutions that either leverage or extend existing academic and industrial research, and utilize your own out-of-the-box pragmatic thinking. - In addition to coming up with novel solutions and building prototypes, you will deliver these to production in customer facing applications, in partnership with product and development teams. - You will publish papers internally and externally, contributing to advancing knowledge in the field of applied machine learning and generative AI. About the team Our team is composed of scientists with PhDs, with a strong publication profile and an appetite to see the impact of innovation on real-world systems at scale.

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 ranging from Amazon Web Services, Kindle, Prime, inventory planning, international retail, third party merchants, search, pricing, labor and employment planning, effective benefits (health, retirement, etc.) and beyond. Amazon Economists build econometric models using our world class data systems and apply approaches from a variety of skillsets – applied macro/time series, applied micro, econometric theory, empirical IO, empirical health, labor, public economics and related fields are all highly valued skillsets at Amazon. You will work in a fast moving environment to solve business problems as a member of either a cross-functional team embedded within a business unit or a central science and economics organization. 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. About the team The International Seller Services (ISS) Economics team is a dynamic group at the forefront of shaping Amazon's global seller ecosystem. As part of ISS, we drive innovation and growth through sophisticated economic analysis and data-driven insights. Our mission is critical: we're transforming how Amazon empowers millions of international sellers to succeed in the WW digital marketplace. Our team stands at the intersection of innovative technology and practical business solutions. We're leading Amazon's transformation in seller services through work with Large Language Models (LLMs) and generative AI, while tackling fundamental questions about seller growth, marketplace dynamics, and operational efficiency. What sets us apart is our unique blend of rigorous economic methodology and practical business impact. We're not just analyzing data – we're building the frameworks and measurement systems that will define the future of Amazon's seller services. Whether we're optimizing the seller journey, evaluating new technologies, or designing innovative service models, our team transforms complex economic challenges into actionable insights that drive real-world results. Join us in shaping how millions of businesses worldwide succeed on Amazon's marketplace, while working on problems that combine economic theory, advanced analytics, and innovative technology.

Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the next-level. We focus on creating entirely new products and services with a goal of positively impacting the lives of our customers. No industries or subject areas are out of bounds. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have thirteen employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We are constantly learning through programs that are local, regional, and global. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. Key job responsibilities * Partner with laboratory science teams on design and analysis of experiments * Originate and lead the development of new data collection workflows with cross-functional partners * Develop and deploy scalable bioinformatics analysis and QC workflows * Evaluate and incorporate novel bioinformatic approaches to solve critical business problems About the team Our team highly values work-life balance, mentorship and career growth. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We care about your career growth and strive to assign projects and offer training that will challenge you to become your best.