Careers

We are looking for an Economist to work on exciting and challenging business problems related to Amazon Retail’s worldwide product assortment. You will build innovative solutions based on econometrics, machine learning, and experimentation. You will be part of a interdisciplinary team of economists, product managers, engineers, and scientists, and your work will influence finance and business decisions affecting Amazon’s vast product assortment globally. If you have an entrepreneurial spirit, you know how to deliver results fast, and you have a deeply quantitative, highly innovative approach to solving problems, and long for the opportunity to build pioneering solutions to challenging problems, we want to talk to you. Key job responsibilities * Work on a challenging problem that has the potential to significantly impact Amazon’s business position * Develop econometric models and experiments to measure the customer and financial impact of Amazon’s product assortment * Collaborate with other scientists at Amazon to deliver measurable progress and change * Influence business leaders based on empirical findings

AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we’re looking for talented people who want to help. You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion. Do you love problem solving? Are you looking for real world Supply Chain challenges? Do you have a desire to make a major contribution to the future, in the rapid growth environment of Cloud Computing? Amazon Web Services is looking for a highly motivated, Data Scientist to help build scalable, predictive and prescriptive business analytics solutions that supports AWS Supply Chain and Procurement organization. You will be part of the Supply Chain Analytics team working with Global Stakeholders, Data Engineers, Business Intelligence Engineers and Business Analysts to achieve our goals. We are seeking an innovative and technically strong data scientist with a background in optimization, machine learning, and statistical modeling/analysis. This role requires a team member to have strong quantitative modeling skills and the ability to apply optimization/statistical/machine learning methods to complex decision-making problems, with data coming from various data sources. The candidate should have strong communication skills, be able to work closely with stakeholders and translate data-driven findings into actionable insights. The successful candidate will be a self-starter, comfortable with ambiguity, with strong attention to detail and ability to work in a fast-paced and ever-changing environment. Key job responsibilities - Demonstrate thorough technical knowledge on feature engineering of massive datasets, effective exploratory data analysis, and model building using industry standard time Series Forecasting techniques like ARIMA, ARIMAX, Holt Winter and formulate ensemble model. - Design and deploy AI agents for supply chain optimization. Build evaluation frameworks with guardrails and benchmarks ensuring reliability. Own the full development lifecycle adhering to responsible AI principles. Drive the AI roadmap leveraging emerging agentic AI trends. - Proficiency in both Supervised(Linear/Logistic Regression) and UnSupervised algorithms(k means clustering, Principle Component Analysis, Market Basket analysis). - Experience in solving optimization problems like inventory and network optimization . Should have hands on experience in Linear Programming. - Work closely with internal stakeholders like the business teams, engineering teams and partner teams and align them with respect to your focus area - Detail-oriented and must have an aptitude for solving unstructured problems. You should work in a self-directed environment, own tasks and drive them to completion. - Excellent business and communication skills to be able to work with business owners to develop and define key business questions and to build data sets that answer those questions - Work with distributed machine learning and statistical algorithms to harness enormous volumes of data at scale to serve our customers About the team 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. 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. 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. Inclusive Team Culture AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do. 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.

The Amazon Web Services (AWS) Center for Quantum Computing in Pasadena, CA, is looking to hire an Applied Scientist on the Device Team, focused on packaging and environmental R&D for quantum devices. 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 deep expertise in the design, modeling, and testing of packaging and off-chip environments for microelectronic or quantum devices, with a strong understanding of how packaging and environmental factors impact qubit performance at cryogenic operating conditions. Candidates with a track record of original scientific contributions in packaging, microwave engineering, or quantum cryogenic hardware will be preferred. We are looking for candidates with strong scientific and engineering principles, resourcefulness and a bias for action, superior problem solving, and excellent communication skills. Working effectively within a team environment is essential. As an applied scientist at CQC, you will be expected to drive packaging and environmental R&D from concept through hardware demonstration and stay abreast of advances in quantum hardware packaging and cryogenic measurement science. Key job responsibilities In this role, you will develop packaging and environmental R&D for superconducting quantum devices. Your responsibilities will span four interconnected areas: Packaging R&D: Design, model, and test packaging solutions for superconducting quantum devices. Build electromagnetic and mechanical models to predict and optimize packaging performance, and characterize packaging at cryogenic temperatures. Environmental Test Standards: Design and develop test standards for characterizing the DC and microwave qubit environment, ensuring rigorous and reproducible assessment of off-chip environmental contributions to qubit decoherence and loss. Measurement Automation: Automate data collection for environmental test standards and develop automated reporting pipelines to enable efficient, scalable characterization across devices and configurations. Environmental Improvement: Collaborate with hardware engineers, PCB designers, and circuit designers to identify and mitigate the most significant sources of environmental noise and integration uncertainty, driving improvements in qubit performance through off-chip environment optimization. You will contribute to multi-year roadmap planning for packaging and environmental capabilities aligned with CQC objectives, and help establish the scientific foundation for this capability area within the Device team. About the team 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. 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. Within AWS UC, Amazon Dedicated Cloud (ADC) roles engage with AWS 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 (diversity) conferences, inspire us to never stop embracing our uniqueness. Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the 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. 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.

The Sponsored Products and Brands (SPB) team at Amazon Ads is re-imagining the advertising landscape through state-of-the-art 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. Curious about our advertising solutions? Discover more about Sponsored Products and Sponsored Brands to see how we’re helping businesses grow on Amazon.com and beyond! Key job responsibilities This role will be pivotal in redesigning how ads contribute to a personalized, relevant, and inspirational shopping experience, with the customer value proposition at the forefront. Key responsibilities include, but are not limited to: - Contribute to the design and development of GenAI, deep learning, multi-objective optimization and/or reinforcement learning empowered solutions to transform ad retrieval, auctions, whole-page relevance, and/or bespoke shopping experiences. - Collaborate cross-functionally with other scientists, engineers, and product managers to bring scalable, production-ready science solutions to life. - Stay abreast of industry trends in GenAI, LLMs, and related disciplines, bringing fresh and innovative concepts, ideas, and prototypes to the organization. - Contribute to the enhancement of team’s scientific and technical rigor by identifying and implementing best-in-class algorithms, methodologies, and infrastructure that enable rapid experimentation and scaling. - Mentor and grow junior scientists and engineers, cultivating a high-performing, collaborative, and intellectually curious team. A day in the life As an Applied Scientist on the Sponsored Products and Brands Off-Search team, you will contribute to the development in Generative AI (GenAI) and Large Language Models (LLMs) to revolutionize our advertising flow, backend optimization, and frontend shopping experiences. This is a rare opportunity to redefine how ads are retrieved, allocated, and/or experienced—elevating them into personalized, contextually aware, and inspiring components of the customer journey. You will have the opportunity to fundamentally transform areas such as ad retrieval, ad allocation, whole-page relevance, and differentiated recommendations through the lens of GenAI. By building novel generative models grounded in both Amazon’s rich data and the world’s collective knowledge, your work will shape how customers engage with ads, discover products, and make purchasing decisions. If you are passionate about applying frontier AI to real-world problems with massive scale and impact, this is your opportunity to define the next chapter of advertising science. About the team The Off-Search team within Sponsored Products and Brands (SPB) is focused on building delightful ad experiences across various surfaces beyond Search on Amazon—such as product detail pages, the homepage, and store-in-store pages—to drive monetization. Our vision is to deliver highly personalized, context-aware advertising that adapts to individual shopper preferences, scales across diverse page types, remains relevant to seasonal and event-driven moments, and integrates seamlessly with organic recommendations such as new arrivals, basket-building content, and fast-delivery options. To execute this vision, we work in close partnership with Amazon Stores stakeholders to lead the expansion and growth of advertising across Amazon-owned and -operated pages beyond Search. We operate full stack—from backend ads-retail edge services, ads retrieval, and ad auctions to shopper-facing experiences—all designed to deliver meaningful value.

Do you want to join the team working on the bleeding edge technology? Have you ever wondered how we can give voice to the devices? Or join the team developing GenAI models? Our team is working on all of the above, join us to see yourself. Text-to-Speech on Device team is responsible for development AI based voice models working locally on the devices. This require specific mix of skills between devices integration, voice generation technologies and machine learning. We are delivering solutions for multiple customers, including offline solutions for Alexa, automotive customers and accessibility voices for visually impaired users. All our models are integrated for devices and working with limited hardware resources. Key job responsibilities We are looking for an Applied Scientist with experience in building highly optimized Machine Learning models for speech generation. As an Applied Scientist, you will: - Work with the team on end-to-end development of an ML models for speech generation, from early experimentation to building production ready models - Engage in state-of-the-art and innovative research in areas such as Speech Generation, Gen AI, model compression, and knowledge distillation - Invent optimization techniques to push the boundaries of deep learning model training and inference - Create and propose detailed theoretical specifications for novel research ideas and directions, and rigorously justify their correctness - Train custom Speech Generation and Gen AI models that beat the state-of-the-art and paves path for developing production models - Collaborate with other science teams to bring state-of-the-art Speech Generation models from cloud to devices About the team Text-to-Speech on Device team is focused on delivery of low-footprint AI models for speech generation that can work locally on devices (Android, FireOS, etc.). These models require much less computation power then the ones hosted in cloud. We are cooperating directly with the teams developing devices and with scientists responsible for the cloud models in order to provide our customers best possible experience.

Amazon Science gives you insight into the company’s approach to customer focused 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. Are you an expert in Computer Vision (CV), Natural Langugage Procesing (NLP) or Multi-Modality Large Language Models (MLLM)? Are you interested in building Generative AI solutions on complex business problems that have significant global benefit. The Brand Protection Science team designs and builds highly performing and scalable AI models using machine learning, deep learning, LLM/Gen AI to identify and prevent infringement abuse and counterfeit on behalf of buyer, seller and brand owners worldwide. As an Applied Science Manager, you will be lead a group of highly talented scientists, and partner with Tech, Business and Operations, to build the strategic vision for brand protection, drive execution and launch scalable AI solutions operating on billions of Amazon product listings WW for Brand Protection. Key job responsibilities You will lead a team of Applied Scientist to work backwards from customer needs and solve complex scientific problems that have a high business and customer impact. As a manager, You will be the thought leader for inventing novel science solutions using SOTA ML techniques including LLM and GenAI. You partner with your stakeholders and leadership to define the science vision and strategies for your team. You have excellent communication skills to explain complex scientific approaches to a variety of stakeholders and customers, and bridge the gap between science, tech, and business,. You are accountable for the science vision and strategic direction of your team, the artifacts they provide, and any technologies owned. You will establish structures that enable your team to consistently deliver. You will also lead your team to leverage the broader Amazon scientific community, and build a team culture that focuses on bringing research to production, removing road blockers, and delivering more results for Amazon customers. You are strategic about the team members' growth and provide those interested with opportunities to demonstrate higher level role scope, impact, complexity and leadership.

The Amazon Center for Quantum Computing (CQC) is a multi-disciplinary team of scientists, engineers, and technicians, all working to innovate in quantum computing for the benefit of our customers. We are looking to hire an Applied Scientist to design and model novel superconducting quantum devices (including qubits), readout and control schemes, and advanced quantum processors. The ideal candidate will have a track record of original scientific contributions, strong engineering principles, and/or software development experience. Resourcefulness, as well as strong organizational and communication skills, is essential. About the team About the team The Amazon 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. Inclusive Team Culture Here at Amazon, 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 conferences, inspire us to never stop embracing our uniqueness. 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. 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. 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. 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.

Amazon Music is an immersive audio entertainment service that deepens connections between fans, artists, and creators. From personalized music playlists to exclusive podcasts, concert livestreams to artist merch, Amazon Music is innovating at some of the most exciting intersections of music and culture. We offer experiences that serve all listeners with our different tiers of service: Prime members get access to all the music in shuffle mode, and top ad-free podcasts, included with their membership; customers can upgrade to Amazon Music Unlimited for unlimited, on-demand access to 100 million songs, including millions in HD, Ultra HD, and spatial audio; and anyone can listen for free by downloading the Amazon Music app or via Alexa-enabled devices. Join us for the opportunity to influence how Amazon Music engages fans, artists, and creators on a global scale. Come join a team at the nexus of AI, machine learning, visual and audio technologies within Amazon Music's Artificial Intelligence & Personalization organization. We're transforming how customers experience music by creating context-rich, intelligently assembled content that powers every surface—from AI-generated playlists and insights to interactive experiences and visual storytelling. Key job responsibilities * Work backwards from customer needs to research and develop novel machine learning approaches for music and spoken word multimodal content generation * Design, develop, evaluate, and deploy scalable AI and ML solutions for customer problems including training LLMs, reasoning models, and diffusion models, agentic and RAG systems, diffusion models * Ship production quality code for models and collaborate with software engineering teams to drive implementation and experimentation in complex Amazon production systems * Improve upon existing methods by developing new data sources, testing model enhancements, and fine-tuning model parameters * Analyze and extract relevant information from large amounts of structured and unstructured, complex and interrelated datasets describing customer behavior and content * Advocate technical solutions to business stakeholders, engineering teams, as well as executive level decision makers * Communicate results, insights and recommendations to audiences of varying levels of technical sophistication * Conduct literature reviews and stay current with advancements in the field, adapting latest in literature to build efficient and scalable models * Promote the culture of experimentation and scientific rigor at Amazon * Contribute to progress of the Amazon and broader research communities by publishing papers A day in the life Lead innovation in AI/ML to shape Amazon Music experiences for millions. Develop state of the art models leveraging and advancing the latest developments in machine learning and genAI including post-training of LLMs, diffusion models. Collaborate with talented engineers and scientists to guide research and build scalable models across our audio portfolio - music, podcasts, live streaming, and more. Drive experiments and rapid prototyping, leveraging Amazon's data at scale. Innovate daily alongside world-class teams to delight customers worldwide through personalization. About the team We are a team of deeply technical Applied Scientists and Machine Learning Engineers passionate about improving CX through state of the art AI methods. We work on multimodal generation to enhance the audio listening experience on several surfaces Alexa, mobile, fireTV - from AI-generated playlists and insights to interactive experiences and visual storytelling.

Alexa+ is the world’s best Generative AI powered personal assistant / agent for consumers. We are seeking an experienced Applied Science Manager to build and lead a new team of scientists in India dedicated to Alexa Conversational Ads and Personalization. As the leader of this team, you will shape both the scientific roadmap and the product strategy, working closely with global product stakeholders to ensure your team is delivering high-impact, scalable solutions. Key job responsibilities - Hire, develop, and mentor a high-performing team of applied scientists. - Partner with product management and engineering leadership to define the mid-to-long-term scientific roadmap for conversational ads and personalization. - Manage the execution of complex ML projects, ensuring rigorous experimental design, high modeling standards, and on-time delivery. - Bridge the gap between science, engineering, and product, translating business metrics into scientific goals and vice versa. - Establish best practices for ML lifecycle management, code quality, and technical documentation within the team.

Alexa+ is the world’s best Generative AI powered personal assistant / agent for consumers. We are looking for a Senior Applied Scientist to provide technical leadership for our Alexa Conversational Ads and Personalization initiatives. You will be responsible for tackling our most ambiguous scientific challenges, setting the technical architecture for new ML systems, and pushing the boundaries of what is possible in voice-based advertising. Key job responsibilities - Define the scientific vision and lead the technical execution for complex, multi-quarter ML projects in conversational ads and personalization. - Architect end-to-end machine learning systems that operate at Alexa's massive scale. - Mentor and guide junior scientists on modeling techniques, experimental design, and best practices. - Partner closely with product and engineering stakeholders to translate ambiguous business requirements into rigorous scientific problem statements. - Contribute to the broader scientific community through internal technical papers and external publications.