Careers

The Amazon Smart Vehicles (ASV) science team is seeking a passionate and skilled Applied Scientist with extensive expertise in advanced LLM technologies. This role involves innovating in rapidly evolving areas of AI research, focusing on creating personalized services to enhance drivers' and passengers' experiences. Your work will aim to simplify their lives, keep them informed, entertained, productive, and safe on the road, with direct application to prominent Amazon products. If you have extensive expertise in LLMs, natural language processing, and machine learning, along with experience in high-performing research teams, this could be the perfect opportunity for you. Our dynamic and fast-paced environment demands a high level of independence in decision-making and the ability to drive ambitious research initiatives through to production. You will collaborate closely with other science and engineering teams, as well as business stakeholders, to ensure your contributions are both impactful and delivered with maximum efficiency. Key job responsibilities - Leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in generative artificial intelligence (GenAI) - Work with talented peers to lead the development of novel algorithms and modeling techniques to advance the state of the art with LLMs - Collaborate with other science and engineering teams as well as business stakeholders to maximize the velocity and impact of your contributions About the team This is an exciting moment to lead in AI research and application. As part of the Amazon Smart Vehicles science team, you have the opportunity to shape the future by enhancing information-driven experiences for Amazon customers around the globe. Your work will directly influence customers through innovative products and services powered by language and multimodal technology!

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.

At Amazon, we strive to be Earth's most customer-centric company, where customers can find and discover anything they want to buy online. Our mission in International Seller Services (ISS) is to provide technology solutions for improving the seller and customer experience, drive seller compliance, maximize seller success, and improve internal workforce productivity. Team's main focus is to build products that are scalable across different regions of the world, while working in partnership with ISS regional stakeholders and multiple partner teams across Amazon. As a Data Scientist, you will be responsible for modeling complex problems, discovering insights, and building risk algorithms that identify opportunities through statistical models, machine learning, and visualization techniques to improve operational efficiency. As a Data Scientist, you will leverage your expertise in Machine Learning, Natural Language Processing (NLP), and Large Language Models (LLM) to develop innovative solutions for Amazon's ISS team. You'll be responsible for modeling complex problems, building innovative algorithms, and discovering actionable insights through statistical models and visualization techniques to enhance operational efficiency in the e-commerce space. The role combines usage of latest AI technology with practical business applications, requiring someone passionate about transforming the way we interact with technology while delivering measurable impact through advanced analytics and machine learning solutions. You will need to collaborate effectively with business and product leaders within ISS and cross-functional teams to build scalable solutions against high organizational standards. The candidate should be able to apply a breadth of tools, data sources, and Data Science techniques to answer a wide range of high-impact business questions and proactively present new insights in concise and effective manner. The candidate should be an effective communicator capable of independently driving issues to resolution and communicating insights to non-technical audiences. This is a high impact role with goals that directly impacts the bottom line of the business. Responsibilities: - Analyze terabytes of data to define and deliver on complex analytical deep dives to unlock insights and build scalable solutions through Data Science to ensure security of Amazon’s platform and transactions - Build Machine Learning and/or statistical models that evaluate the transaction legitimacy and track impact over time - Ensure data quality throughout all stages of acquisition and processing, including data sourcing/collection, ground truth generation, normalization, transformation, and cross-lingual alignment/mapping - Define and conduct experiments to validate/reject hypotheses, and communicate insights and recommendations to Product and Tech teams - Develop efficient data querying infrastructure for both offline and online use cases - Collaborate with cross-functional teams from multidisciplinary science, engineering and business backgrounds to enhance current automation processes - Learn and understand a broad range of Amazon’s data resources and know when, how, and which to use and which not to use. - Maintain technical document and communicate results to diverse audiences with effective writing, visualizations, and presentations Key job responsibilities Analyze terabytes of data to define and deliver on complex analytical deep dives to unlock insights and build scalable solutions through Data Science to ensure security of Amazon’s platform and transactions Build Machine Learning and/or statistical models that evaluate the transaction legitimacy and track impact over time Ensure data quality throughout all stages of acquisition and processing, including data sourcing/collection, ground truth generation, normalization, transformation, and cross-lingual alignment/mapping Define and conduct experiments to validate/reject hypotheses, and communicate insights and recommendations to Product and Tech teams Develop efficient data querying infrastructure for both offline and online use cases Collaborate with cross-functional teams from multidisciplinary science, engineering and business backgrounds to enhance current automation processes Learn and understand a broad range of Amazon’s data resources and know when, how, and which to use and which not to use. Maintain technical document and communicate results to diverse audiences with effective writing, visualizations, and presentations

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.

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

Are you interested in building the measurement foundation that proves whether targeted, cohort-based marketing actually changes customer behavior at Amazon scale? We are seeking an Applied Scientist to own measurement and experimentation for our Lifecycle Marketing Experimentation roadmap within the PRIMAS (Prime & Marketing Analytics and Science) team. In this role, you will design and execute rigorous experiments that measure the effectiveness of audience-based marketing campaigns across multiple channels, providing the evidence that guides marketing strategy and investment decisions. This is a high-impact role where you will build measurement frameworks from scratch, design experiments that isolate causal effects, and establish the experimental standards for lifecycle marketing across EU. You will work closely with business leaders and the senior science lead to answer critical questions: does targeting specific cohorts (Bargain hunters, Young adults) improve efficiency vs. broad campaigns? Which creative strategies drive behavior change? How should we optimize marketing spend across channels? Key job responsibilities Measurement & Experimentation Ownership: 1. Own measurement end-to-end for lifecycle marketing campaigns – design experiments (RCTs, geo-tests, audience holdouts) that measure campaign effectiveness across marketing channels 2. Build measurement frameworks and experimental best practices that work across different activation platforms and can scale to multiple campaigns 3. Establish experimental standards and tooling for lifecycle marketing, ensuring statistical rigor while balancing business constraints Causal Inference & Analysis: 1. Apply causal inference methods to measure incremental impact of marketing campaigns vs. counterfactual 2. Navigate measurement challenges across different platforms (Meta attribution, LiveRamp, clean rooms, onsite tracking) 3. Analyze experiment results and provide optimization recommendations based on statistical evidence 4. Establish guardrails and success criteria for campaign evaluation About the team 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.

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.

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’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. In this role, you will be developing Multimodal and Agentic LLMs to unlock new shopping experiences. Experience in Vision-Language Multimodal Modeling and Reinforcement Learning is preferred. 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!