Careers

The Pricing and Promotions Optimization Science team is hiring an incrementality applied scientist with experience in causal inference, experimentation, and ML development to help us expand our causal modeling solutions for understanding promotion effectiveness. Our work is foundational to providing seller-facing promotional tools, furthering internal research & development, and building out Amazon's promotion optimization measurement offerings. Incrementality measurement is a lynchpin for the next generation of Amazon Promotion solutions and this role will play a key role in the release and expansion of these offerings. - Partner with principals and senior team members to drive science improvements and implement technical solutions at the state-of-the-art of machine learning and econometrics - Partner with engineering and other science collaborators to design, implement, prototype, deploy, and maintain large-scale causal ML models. - Carry out in-depth research and analysis exploring promotion-related data sets, including large sets of real-world experimental data, to understand behavior, highlight model improvement opportunities, and understand shortcomings and limitations. - Define data quality standards for understanding typical behavior, capturing outliers, and detecting model performance issues. - Work with product stakeholders to help improve our ability to provide quality measurement of promotion effectiveness for our customers. About the team The Pricing and Promotions Optimization science team owns price quality, discovery and discount optimization initiatives across Amazon’s internal pricing and promotions architectures as well as upwards into the customer discovery funnel. We leverage planet scale data on billions of Amazon and external competitor products to build advanced optimization models for pricing, elasticity estimation, product substitutability, and optimization. We preserve long term customer trust by ensuring Amazon's prices and promotions are always competitive and error free.

Our team leads the development and optimization of on-device ML models for Amazon's hardware products, including audio, vision, and multi-modal AI features. We work at the critical intersection of ML innovation and silicon design, ensuring AI capabilities can run efficiently on resource-constrained devices. Currently, we enable production ML models across multiple device families, including Echo, Ring/Blink, and other consumer devices. Our work directly impacts Amazon's customer experiences in consumer AI device market. The solutions we develop determine which AI features can be offered on-device versus requiring cloud connectivity, ultimately shaping product capabilities and customer experience across Amazon's hardware portfolio. This is a unique opportunity to shape the future of AI in consumer devices at unprecedented scale. You'll be at the forefront of developing industry-first model architectures and compression techniques that will power AI features across millions of Amazon devices worldwide. Your innovations will directly enable new AI features that enhance how customers interact with Amazon products every day. Come join our team! Key job responsibilities As a Principal Applied Scientist, you will: • Own the technical architecture and optimization strategy for ML models deployed across Amazon's device ecosystem, from existing to yet-to-be-shipped products. • Develop novel model architectures optimized for our custom silicon, establishing new methodologies for model compression and quantization. • Create an evaluation framework for model efficiency and implement multimodal optimization techniques that work across vision, language, and audio tasks. • Define technical standards for model deployment and drive research initiatives in model efficiency to guide future silicon designs. • Spend the majority of your time doing deep technical work - developing novel ML architectures, writing critical optimization code, and creating proof-of-concept implementations that demonstrate breakthrough efficiency gains. • Influence architecture decisions impacting future silicon generations, establish standards for model optimization, and mentor others in advanced ML techniques.

Come be a part of a rapidly expanding $35 billion dollar global business. At Amazon Business, a fast-growing startup passionate about building solutions, we set out every day to innovate and disrupt the status quo. We stand at the intersection of tech & retail in the B2B space developing innovative purchasing and procurement solutions to help businesses and organizations thrive. At Amazon Business, we strive to be the most recognized and preferred strategic partner for smart business buying. Bring your insight, imagination and a healthy disregard for the impossible. Join us in building and celebrating the value of Amazon Business to buyers and sellers of all sizes and industries. Unlock your career potential. We are seeking an Applied Scientist who has a solid background in applied Machine Learning and Data Science, deep passion for building data-driven products, ability to formulate data insights and scientific vision, and has a proven track record of executing complex projects and delivering business impact. Key job responsibilities • Data driven insights to accelerate acquisition of new members. • Develop and implement personalized marketing strategies and campaigns tailored to individual customer preferences, behaviors, and demographics to enhance engagement and drive customer loyalty. • Develop, implement, and optimize marketing attribution models to accurately measure the impact of various marketing channels and campaigns, and create valuation frameworks to assess the ROI and contribution of each channel to overall business objectives. • Work with a group of both applied scientists and software engineers to deliver machine-learning and data science solutions to production. • Advance team's engineering craftsmanship and drive continued scientific innovation as a thought leader and practitioner. • Mentor talented members, provide technical and career development guidance to both scientists and engineers in the organization. About the team The Marketing Science team applies scientific methods and research techniques to enhance our understanding of AB consumer behavior, market trends, and the effectiveness of marketing strategies. Our goal is to develop and advance theories and models that can be used to make informed decisions in marketing and to provide insights into consumer decision-making processes. Additionally, we seek to identify and explore emerging trends and technologies in marketing, and to develop innovative approaches for addressing the challenges and opportunities in the field.

AWS AI/ML is looking for world class scientists and engineers to join its AI Research and Education group working on foundation models, large-scale representation learning, and distributed learning methods and systems. At AWS AI/ML you will invent, implement, and deploy state of the art machine learning algorithms and systems. You will build prototypes and innovate on new representation learning solutions. You will interact closely with our customers and with the academic and research communities. You will be at the heart of a growing and exciting focus area for AWS and work with other acclaimed engineers and world famous scientists. Large-scale foundation models have been the powerhouse in many of the recent advancements in computer vision, natural language processing, automatic speech recognition, recommendation systems, and time series modeling. Developing such models requires not only skillful modeling in individual modalities, but also understanding of how to synergistically combine them, and how to scale the modeling methods to learn with huge models and on large datasets. Join us to work as an integral part of a team that has diverse experiences in this space. We actively work on these areas: * Hardware-informed efficient model architecture, training objective and curriculum design * Distributed training, accelerated optimization methods * Continual learning, multi-task/meta learning * Reasoning, interactive learning, reinforcement learning * Robustness, privacy, model watermarking * Model compression, distillation, pruning, sparsification, quantization About the team Why AWS Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Utility Computing (UC) AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (IoT), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. 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 we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Mentorship 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, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

The Amazon Web Services (AWS) Center for Quantum Computing in Pasadena, CA, is looking to hire a Quantum Research Scientist. You will join a multi-disciplinary team of theoretical and experimental physicists, materials scientists, and hardware and software engineers working at the forefront of quantum computing. You should have a deep and broad knowledge of experimental measurement techniques. Candidates with a track record of original scientific contributions in experimental condensed matter physics will be preferred. We are looking for candidates with strong engineering principles, resourcefulness and a bias for action, superior problem solving, and excellent communication skills. Working effectively within a team environment is essential. As a research scientist you will be expected to work on new ideas and stay abreast of the field of experimental quantum computation. AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services. Key job responsibilities As a research scientist you will be responsible for building experiments that encompass the integrated stack: design, fabrication, cryogenics, signal chain, and control stack software. Based on your tests you will provide recommendations that improve our next-generation quantum processors. About the team Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Mentorship & 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, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. 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 we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Hybrid Work We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices. 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 US export license. If you are unsure if you meet these requirements, please apply and Amazon will review your application for eligibility.

The Artificial General Intelligent team (AGI) seeks a passionate, talented, and resourceful Applied Scientist in the field of LLM, Artificial Intelligence (AI), Natural Language Processing (NLP) and/or Information Retrieval, to invent and build scalable solutions for a state-of-the-art context-aware conversational AI. As part of this team, you will collaborate with talented peers to create scalable solutions for an innovative conversational assistant, aiming to revolutionize user experiences for millions of Alexa customers. The ideal candidate possesses a solid understanding of machine learning fundamentals and a passion for pushing boundaries in the field. They thrive in fast-paced environments, possess the drive to tackle complex challenges, and excel at swiftly delivering impactful solutions while iterating based on user feedback. Join us in our mission to redefine industry standards and provide unparalleled experiences for our customers. Key job responsibilities . You will analyze, understand and improve user experiences by leveraging Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in artificial intelligence. . You will work on core LLM technologies, including developing best-in-class modeling, prompt optimization algorithms to enable Conversation AI use cases · Build and measure novel online & offline metrics for personal digital assistants and customer scenarios, on diverse devices and endpoints · Create, innovate and deliver deep learning, policy-based learning, and/or machine learning based algorithms to deliver customer-impacting results · Perform model/data analysis and monitor metrics through online A/B testing · Research and implement novel machine learning and deep learning algorithms and models.

We are looking for a Data Scientist for Rufus team who will focus specifically on building signals to measure customer shopping journey and progressions for analytical purposes, an area that is seeing accelerated adoption.You will have the opportunity to dive deep into the vast data generated and applying current data analysis methods to produce insights that will improve customer experience, and business value. You will get exposed to exciting challenges and opportunities for innovation that arise as we look into complicated customer journeys. As a member of this team, you’ll work closely with data engineers , economist and analytics team, have fun, and help build a framework for offline use cases enabling multiple teams in shopping org to measure success of their CXs specifically where traditional amazon metrics do not work in quantifying the value of CX. Key job responsibilities Improving quality of customer journey and shopping progression by refining and leveraging additional amazon engagement signals site wide to be used for analytical purposes.

Amazon Ads is one of Amazon's fastest growing and most profitable businesses. As a core product offering within our advertising portfolio, Sponsored Products (SP) helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The SP team's 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 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 Bespoke Shopping Experience team within SP develops customer facing experiences and machine learning models to better understand and address the diverse needs and behaviors of various shopper cohorts. As an Applied Scientist on the team, you will: - Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity. - 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. - 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.

The JP Retail Science team is looking for an Senior Applied Scientist to expand our efforts in vendor tooling. To help vendors grow their business, Amazon provides multiple programs such as deals, ads, etc. In this position, you will be expected to research, design and build new models to evaluate the downstream impact of those programs, and provide recommendation on the most appropriate programs depending on the vendor need. It will require working in the areas of ML and causal inference for downstream impact estimation. The ideal candidate will have knowledge of at least one of ray, spark or rapidsai framework to accelerate model training. A background in causal inference (e.g. Double ML) is a plus but not required. This is the ideal role if you are excited about leveraging science for tangible business impact. You will work within an international team of scientists and engineers, all based in Tokyo, Japan. We are a team that thrives on growth, both personal and professional. Engage in academic collaborations, spark innovation in hackathons, and expand your horizons with conference visits. Key job responsibilities As a Senior Applied Scientist, your responsibilities will be: - Work closely with other scientists and engineers to review and improve your model design proposals. - Partner with product managers and other business stakeholders, documenting and explaining your progress in business reviews, and being the technical voice in charge of your product. - Spot opportunities for innovation and scientific publications, and publish to internal or external conferences. - Be active in the community, participating in science education/growth activities. - Keep up to date with scientific development in the field. About the team JP Retail Science is a team of Applied Scientists, Science Managers, and Business Intelligence Engineers. The team's charter is to develop science-based models to help all Amazon vendors to maximize their growth. From our base office in Tokyo, Japan, we build for all vendors worldwide, and collaborate with other science teams in Europe and US. Because we are not tied to a specific technology, such as Search or Alexa, our projects and the science required change dynamically depending on the vendor needs. In the past we have worked on initiatives drawing from multiple disciplines, including causal inference, LLM, forecasting, and optimization. A large fraction of the team consists of former academic researchers, and we maintain that culture through collaboration with universities, exchange programs, and conference participation.

The JP Retail Science team is looking for a Senior Data Scientist to lead the science development of deal recommendation. Deals and promotion is one of the key tool to help vendors grow their business on Amazon. We want to leverage science to evaluate promotion scenarios, ROI and help vendors find the best promotion that fit their needs. In this position, you will be expected to review existing literature, analyze data and prototype predictive analytics for promotion. You will have access to our vast historical transaction data and vendor tools interaction to formulate hypotheses, build prototypes and train new models for deal promotion and evaluation. You will work within an international team of scientists and engineers, all based in Tokyo, Japan. We are a team that thrives on growth, both personal and professional. Engage in academic collaborations, spark innovation in hackathons, and expand your horizons with conference visits. Key job responsibilities As a Senior Data Scientist, your responsibilities will be: * Lead the analysis, prototyping and implementation of recommendation models for amazon vendors. * Work closely with other scientists and engineers to review and improve your model design proposals. * Partner with product managers and other business stakeholders, documenting and explaining your progress in business reviews, and being the technical voice in charge of your product. * Spot opportunities for innovation and scientific publications, and publish to internal or external conferences. * Be active in the community, participating in science education/growth activities. * Keep up to date with scientific development in the field. About the team JP Retail Science is a team of Scientists, Science Managers, and Business Intelligence Engineers. The team's charter is to develop science-based models to help all Amazon vendors to maximize their growth. From our base office in Tokyo, Japan, we build for all vendors worldwide, and collaborate with other science teams in Europe and US. Because we are not tied to a specific technology, such as Search or Alexa, our projects and the science required change dynamically depending on the vendor needs. In the past we have worked on initiatives drawing from multiple disciplines, including causal inference, LLM, forecasting, and optimization. A large fraction of the team consists of former academic researchers, and we maintain that culture through collaboration with universities, exchange programs, and conference participation.