Careers

Amazon Stores is looking for exceptional Applied Scientists to join our efforts in developing generative AI solutions in marketing. In this role, you will be part of a team that designs, implements, and evaluates state-of-the-art agentic AI solutions to enhance customer experiences through intelligent, personalized interactions. Key job responsibilities * Research, develop, and deploy novel approaches using large language models (LLMs) and multi-agent AI systems * Design and implement scalable solutions for personalized recommendations and customer insights * Create innovative evaluation frameworks for complex AI systems * Collaborate with cross-functional teams to integrate AI solutions into production environments * Conduct rigorous experimentation and data analysis to improve model performance * PhD in Computer Science, Machine Learning, AI, or related field; OR Master's degree with 2+ years of relevant industry experience * Strong programming skills in Python and experience with ML frameworks (PyTorch, TensorFlow, etc.) * Experience building and deploying machine learning models in production environments * Proficiency in natural language processing techniques and applications * Strong publication record or demonstrated practical experience in machine learning * Experience working with large language models (LLMs) and prompt engineering * Knowledge of multi-agent systems and their applications * Background in recommendation systems or personalization technologies * Experience with uncertainty quantification in AI systems * Ability to design and implement automated testing frameworks for ML systems * Previous experience in AI labs or AI-focused startups * Strong communication skills and ability to translate complex technical concepts to diverse audiences * Experience with model evaluation and validation methodologies * Track record of innovation in applied machine learning

The WW Operations IPAT team is revolutionizing Amazon's financial forecasting through TrendCast, an innovative, automated, science based top-down forecast modeling that's transforming how we predict Worldwide Operations costs. This cutting-edge approach leverages key performance indicators to generate automated, transparent forecasts with unprecedented frequency. By moving beyond traditional bottom-up planning, TrendCast empowers leadership with real-time insights, enabling swift identification of both risks and opportunities. This game-changing model not only delivers more agile and precise financial projections but also significantly reduces the workload on finance teams. By providing more frequent forecasts, this model will facilitate leadership's decision-making process, allowing for more timely and informed strategic choices. Key job responsibilities As our operational scope rapidly expands, we're seeking a Senior Data Scientist to spearhead the development of advanced analytical solutions. In this role, you will: • Drive model development and improvement through machine learning and statistical techniques, creating scalable solutions for complex business problems • Design, develop, and evaluate novel forecasting models, with a focus on large-scale operational challenges • Lead projects through the entire data science lifecycle, from problem formulation to production deployment, working with both technical and non-technical stakeholders • Implement advanced ML models, including supervised and unsupervised learning approaches, and optimization algorithms for supply chain and operational systems • Develop a deep understanding of key business metrics and KPIs, connecting them to actionable levers that inform strategic decisions • Collaborate closely with finance, product, and BIEs teams to build and deploy robust models and algorithms • Architect scalable data pipelines and work with distributed computing frameworks to handle petabyte-scale datasets The ideal candidate will have expertise in ML model development, optimization techniques, statistical analysis, and database design. Proficiency in working with large, complex datasets and visualization tools is essential. Experience with cloud computing, MLOps, and production model deployment is highly valued. Join our team as we tackle unprecedented challenges in global operations, driving data-driven decision making at scale.

The Amazon Web Services (AWS) Center for Quantum Computing (CQC) is a multi-disciplinary team of scientists, engineers, and technicians on a mission to develop a fault-tolerant quantum computer. You will be joining a team located in Pasadena, CA that conducts materials research to improve the performance of superconducting quantum processors. We seek a Quantum Research Scientist to investigate how material defects affect qubit performance. In this role, you will combine expertise in numerical simulations and materials characterization to study materials loss mechanisms such as two-level systems, quasiparticles, vortices, etc. Key job responsibilities Provide subject matter expertise on integrated experimental and computational studies of materials defects Develop and use computational tools for large-scale simulations of disordered structures Develop and implement multi-technique materials characterization workflows for thin films and devices, with a focus on the surfaces and interfaces Identify material properties that can be a reliable proxy for the performance of superconducting resonators and qubits Communicate findings to teammates, the broader CQC team and, when appropriate, publish findings in scientific journals A day in the life At the AWS CQC, we understand that developing quantum computing technology is a marathon, not a sprint. The work/life integration within our team encourages a culture where employees work hard and also have ownership over their downtime. We are committed to the growth and development of every employee at the AWS CQC, and that includes our research scientists. You will receive management and mentorship from within the team that is geared toward career growth, and also have the opportunity to participate in Amazon's mentorship programs for scientists and engineers. Working closely with other quantum research scientists in other disciplines – like design, measurement and cryogenic hardware – will provide opportunities to dive deep into an education on quantum computing. About the team Our team contributes to the fabrication of processors and other hardware that enable quantum computing technologies. Doing that necessitates the development of materials with tailored properties for superconducting circuits. Research Scientists and Engineers on the Materials team operate deposition and characterization systems in order to develop and optimize thin film processes for use in these devices. They work alongside other Research Scientists and Engineers to help deliver the fabricated devices for quantum computing experiments. Export Control Requirement: Due to applicable export control laws and regulations, candidates must be either 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, or be able to obtain a U.S export license. If you are unsure if you meet these requirements, please apply and Amazon will review your application for eligibility.

The Customer Behavior Analytics team designs innovative machine learning solutions to enhance customer experiences and strengthen their relationship with Amazon. This interdisciplinary team of scientists and engineers incubates and develops disruptive solutions using state-of-the-art technology to tackle some of the most challenging scientific problems in customer behavior analysis at Amazon. To achieve this, the team utilizes methods from deep learning, large language models (LLMs), natural language models, recommendation systems, affinity models, reinforcement learning, and econometrics to drive personalized experiences throughout the customer journey. As a Customer Behavior Analytics Scientist, you will have the opportunity to make a significant business impact, delve into large-scale problems, drive measurable actions, and collaborate closely with other scientists and engineers. You will be responsible for designing and developing state-of-the-art models and working with business, marketing, and engineering teams to address key challenges in customer behavior analytics. Key responsibilities include: - Creating of innovative deep learning and generative models for recommender systems to provide personalized experiences, including fine-tuning, efficient contextualization, adapters, evaluations. - Developing innovative statistical methods to calibrate our predictions and corroborate them with data sources and behavioral signals. - Designing and implementing models that improve the overall relationship between customers and Amazon, focusing on long-term customer value and satisfaction. - Applying reinforcement learning methods in production to continuously improve and adapt customer behavior models. - Developing and deploying sophisticated incentive recommendation models to optimize customer engagement and loyalty. - Leveraging state-of-the-art AI/ML techniques to extract insights from vast amounts of customer data. In this role, you will be an analytical problem solver who enjoys exploring data, participating in problem-solving efforts, developing new frameworks, and engaging in investigations and algorithm development. You should be capable of effectively collaborating with technical teams and business stakeholders, pushing the boundaries of what is scientifically possible, and maintaining a sharp focus on measurable customer satisfaction and business impact. Your work will be crucial in shaping the future of customer behavior analytics at Amazon, driving innovation that directly impacts millions of customers worldwide. This position offers a high-visibility opportunity to contribute to solutions that are vital to improving customer satisfaction and loyalty, serving as a model for customer-centric solutions across the company.

Employer: Amazon.com Services LLC Position: Data Scientist III Location: Santa Clara, CA Multiple Positions Available: Own the data science elements of various products to help with data-based decision making, product performance optimization, and product performance tracking. Work directly with product managers to help drive the design of the product. Work with Technical Product Managers to help drive the build planning. Translate business problems and products into data requirements and metrics. Initiate the design, development, and implementation of scientific analysis projects or deliverables. Own the analysis, modelling, system design, and development of data science solutions for products. Write documents and make presentations that explain model/analysis results to the business. Bridge the degree of uncertainty in both problem definition and data scientific solution approaches. Build consensus on data, metrics, and analysis to drive business and system strategy.

We are looking for a passionate, talented, and resourceful Applied Scientist in the field of LLM, Artificial Intelligence (AI), Natural Language Processing (NLP), Recommender Systems and/or Information Retrieval, Multi-Agent and Multi-Modality research to invent and build scalable solutions for a context-aware AI-Native application. A successful candidate will have strong machine learning background and a desire to push the envelope in one or more of the above areas. The ideal candidate would also have hands-on experiences in building Multi-Agent solutions with LLMs, enjoy operating in dynamic environments, be self-motivated to take on challenging problems to improve customer experience, moving fast to ship solutions and then iterating on user feedback and interactions. Key job responsibilities - Leverage your technical expertise to lead the development of Large Language Model (LLM) and AI Agent technologies. - Tackle complex problems in LLM modeling and engineering. - Research and develop techniques to reduce friction and enable scientific solutions for products - Analyze and improve customer experiences using Amazon's diverse data sources and computing resources. - Your work will directly impact customers through novel products and services. A day in the life As an Applied Scientist at Amazon, your day revolves around leveraging machine learning methods to solve complex international business challenges. You collaborate with stakeholders to understand critical business problems, then design and implement machine learning solutions to address customer experience risks across global markets. A significant part of your role involves developing innovative evaluation metrics and rapidly setting up experiments to test and validate model performance. Working closely with engineering teams, you ensure successful deployment of these models to production environments. Throughout this process, you support peer scientists and drive technological innovation forward. About the team Customer Experience and Business Trends (CXBT) is an organization made up of a diverse suite of functions dedicated to deeply understanding and improving customer experience, globally. We are a team of builders that develop products, services, ideas, and various ways of leveraging data to influence product and service offerings – for almost every business at Amazon – for every customer (e.g., consumers, developers, sellers/brands, employees, investors, streamers, gamers). Our approach is based on determining the customer need, along with problem solving, and we work backwards from there. We use technical and non-technical approaches and stay aware of industry and business trends. We are a global team, made up of a diverse set of profiles, skills, and backgrounds – including: Product Managers, Software Developers, Computer Vision experts, Solutions Architects, Data Scientists, Business Intelligence Engineers, Business Analysts, Risk Managers, and more.

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 extreme. 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. 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.

The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Senior Applied Scientist; to lead the development and implementation of Generative AI (GenAI) algorithms and models for supervised fine-tuning, and advance the state of the art with Large Language Models (LLMs), As a Senior Applied Scientist, you will play a critical role in driving the development of GenAI technologies that can handle Amazon-scale use cases and have a significant impact on our customers' experiences. Key job responsibilities - Collaborate with cross-functional teams of engineers, product managers, and scientists to identify and solve complex problems in GenAI - Design and execute experiments to evaluate the performance of different algorithms and models, and iterate quickly to improve results - Think big about the arc of development of GenAI over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems - Communicate results and insights to both technical and non-technical audiences, including through presentations and written reports - Mentor and guide junior scientists and engineers, and contribute to the overall growth and development of the team

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! As an Applied Scientist on this team, you will: - Be a strong contributor to Machine Learning; lending effort 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 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! As an Applied Scientist on this team, you will: - Be a strong contributor to Machine Learning; lending effort 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