Careers

At Audible, we believe stories have the power to transform lives. It’s why we work with some of the world’s leading creators to produce and share audio storytelling with our millions of global listeners. We are dreamers and inventors who come from a wide range of backgrounds and experiences to empower and inspire each other. Imagine your future with us. ABOUT THIS ROLE As an Applied Scientist, you will solve large complex real-world problems at scale, draw inspiration from the latest science and technology to empower undefined/untapped business use cases, delve into customer requirements, collaborate with tech and product teams on design, and create production-ready models that span various domains, including Machine Learning (ML), Artificial Intelligence (AI) and Generative AI, Natural Language Processing (NLP), Reinforcement Learning (RL), real-time and distributed systems. ABOUT YOU Your work will focus on inventing or adapting scientific approaches, models, and algorithms driven by customer needs at the project level. You will develop components and/or end-to-end solutions that are deployed into production or directly support production systems, delivering consistently high-quality work that meets both scientific and engineering best practices. You will develop reusable science components and services that resolve architecture deficiencies and customers’ pain points, while making technical trade-offs for long-term/short- term. You will work semi-autonomously to deliver solutions, contribute to research papers at peer-reviewed venues when appropriate, and document your work thoroughly to enable others to understand and reproduce it. Your decision-making will consistently incorporate robust, data-driven business and technical judgment. You will collaborate with other scientists to raise the bar of both scientific and engineering complexity for the team and to foster valuable scientific partnership opportunities to help/guide science decisions. We work in a highly collaborative, fast-paced environment where scientists, engineers, and product managers work to test and build scalable foundational capabilities, as well as customer facing experiences. You will have the opportunity to innovate and think big within your projects scope, implement optimization services and algorithms, and influence the experiences of millions of customers. We are looking for a results-oriented Applied Scientist with deep knowledge in ML, NLP, Deep Learning, GenAI, and/or large-scale distributed computation. As an Applied Scientist, you will... - Understand use cases across the business and adopt/extend/design/invent solutions/models that are scalable, efficient, and automated for difficult problems that are not well defined - Work closely with fellow scientists and software engineers (at Audible and Amazon) to build and productionize models, deliver novel and highly impactful features - Review models of peers for the purpose of reducing and managing risk to the business, while improving customer experience - Design, develop, and deploy modeling techniques and solutions for Content Understanding, Recommendations, GenAI-based product features, by employing a wide range of methodologies, working from simple to complex - Contribute to initiatives that employ the most recent advances in ML/AI in a fast-paced, experimental environment - Push the boundary of innovation ABOUT AUDIBLE Audible is the leading producer and provider of audio storytelling. We spark listeners’ imaginations, offering immersive, cinematic experiences full of inspiration and insight to enrich our customers daily lives. We are a global company with an entrepreneurial spirit. We are dreamers and inventors who are passionate about the positive impact Audible can make for our customers and our neighbors. This spirit courses throughout Audible, supporting a culture of creativity and inclusion built on our People Principles and our mission to build more equitable communities in the cities we call home.

We are open to hiring candidates to work out of one of the following locations: New York, NY, USA Amazon Secure Tool Foundations is looking for world-class scientists to join the Truffle team. You will join a team of scientists and engineers building agentic AI systems that automate how Amazon protects its applications at scale. Our systems convert security knowledge into automated, continuous protection that strengthens over time and enables development teams to ship secure software faster. You will design and build agentic systems that reason about code, identify patterns, and produce security intelligence consumable by both scanning infrastructure and AI code agents. In some cases, you will invent new approaches for automated security analysis and secure code generation. In other cases, you will adapt existing AI/ML techniques to solve hard problems in security automation. You will work closely with security engineers, platform teams, and scanning infrastructure owners to integrate these techniques into Amazon's security mechanisms. Your work will directly determine how effectively AI-assisted development produces secure software at scale. While you may not be a security expert yet, in this role you will develop deep understanding of vulnerability patterns, application security, and how AI systems can prevent entire classes of risk. Our team puts a high value on work-life balance. Striking a healthy balance between your personal and professional life is crucial to your happiness and success here, which is why we aren't focused on how many hours you spend at work or online. Instead, we're happy to offer a flexible schedule so you can have a more productive and well-balanced life—both in and outside of work. Key job responsibilities * Rapidly design, prototype and test advanced security analysis and repair techniques in a high-ambiguity environment, making use of both quantitative and business judgment. * Collaborate with software engineers and security engineers to integrate successful experiments into large scale production services. * Report results in a scientifically rigorous way. * Interact with security engineers and related domain experts to dive deep into the types of challenges that need innovative solutions. * Track relevant research in other Amazon science teams and in the broader research community. About the team Diverse Experiences Amazon Security 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. Why Amazon Security? At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon’s products and services. We offer talented security professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores Inclusive Team Culture In Amazon Security, it’s in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices. Training & 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, training, 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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.

Amazon's EU International Technology (EU INTech) organisation is creating new ways for customers to discover products through innovative customer experiences. We are a science-only team within EU INTech, responsible for designing and developing AI/ML science solutions that support business needs across Amazon's global search and discovery experiences. Our mission is to make Amazon navigation easier for customers worldwide. We achieve this through two strategic pillars: making Amazon navigation more visual and improving Amazon navigation with more inspiring discovery tools and narrowing navigation. To support this vision, we build and deploy AI/ML models that surface the most relevant content to hundreds of millions of Amazon customers worldwide. Our team comprises Applied Scientists and we partner with other teams, collaborating with ML Engineers, Software Developers, Product Managers, Technical Product Managers, and UX Designers. We are located in the Madrid Technical Hub. We are looking for Applied Scientists who are passionate about solving highly ambiguous and challenging problems at global scale. This is a hands-on, end-to-end applied science role where you will own the full lifecycle of science solutions — from business problem analysis and science plan design, through development and experimentation, to production deployment. We are looking for AI/ML experts with knowledge on ranking, computer vision, recommendation systems, search, and customer experience design. What makes this role unique: • End-to-end ownership – You will analyse business problems, map them to science plans, and design and develop solutions from ideation to production. We are owners of the full science lifecycle. • Applied science with a research edge – While our focus is on delivering applied science solutions that drive measurable business impact, our team actively pushes the state of the art in areas such as computer vision and Generative AI. • Hands-on execution – We need scientists who thrive in building, experimenting, and shipping. What are we looking for? • A scientist who can independently analyse any business problem and design a rigorous science approach to solve it • Strong hands-on engineering skills — you build and ship, not just theorise • Deep expertise in one or more of: computer vision, generative AI, recommendation systems, ranking, or NLP • Experience taking ML models from research to production at scale • Comfort with ambiguity and the ability to structure complex, undefined problems • A passion for customer-centric innovation and measurable impact • A strong communicator capable to adapt the message from a science audience, to engineering or leadership Key job responsibilities • Analyse complex business problems and translate them into well-defined science plans with clear milestones and success criteria • Design, develop, and deliver ML/AI models end-to-end — from research and prototyping through to production systems at Amazon scale and extending solutions going beyond the state of the art • Work with state-of-the-art models in computer vision, ranking and generative AI to power new customer experiences globally • Own major science challenges for the team, driving solutions from ideation through experimentation to production deployment • Collaborate with a variety of roles and partner teams around the world to deliver integrated solutions • Influence scientific direction and best practices across the team • Maintain high quality standards on team deliverables • Contribute to expanding the state of the art in computer vision, ranking and GenAI through publications and internal knowledge sharing

Amazon's EU International Technology (EU INTech) organisation is creating new ways for customers to discover products through innovative customer experiences. We are a science-only team within EU INTech, responsible for designing and developing AI/ML science solutions that support business needs across Amazon's global search and discovery experiences. Our mission is to make Amazon navigation easier for customers worldwide. We achieve this through two strategic pillars: making Amazon navigation more visual and improving Amazon navigation with more inspiring discovery tools and narrowing navigation. To support this vision, we build and deploy AI/ML models that surface the most relevant content to hundreds of millions of Amazon customers worldwide. Our team comprises Applied Scientists and we partner with other teams, collaborating with ML Engineers, Software Developers, Product Managers, Technical Product Managers, and UX Designers. We are located in the Madrid Technical Hub. We are looking for Applied Scientists who are passionate about solving highly ambiguous and challenging problems at global scale. This is a hands-on, end-to-end applied science role where you will own the full lifecycle of science solutions — from business problem analysis and science plan design, through development and experimentation, to production deployment. We are looking for AI/ML experts with knowledge on ranking, computer vision, recommendation systems, search, and customer experience design. What makes this role unique: • End-to-end ownership – You will analyse business problems, map them to science plans, and design and develop solutions from ideation to production. We are owners of the full science lifecycle. • Applied science with a research edge – While our focus is on delivering applied science solutions that drive measurable business impact, our team actively pushes the state of the art in areas such as computer vision and Generative AI. • Hands-on execution – We need scientists who thrive in building, experimenting, and shipping. What are we looking for? • A scientist who can independently analyse any business problem and design a rigorous science approach to solve it • Strong hands-on engineering skills — you build and ship, not just theorise • Deep expertise in one or more of: computer vision, generative AI, recommendation systems, ranking, or NLP • Experience taking ML models from research to production at scale • Comfort with ambiguity and the ability to structure complex, undefined problems • A passion for customer-centric innovation and measurable impact • A strong communicator capable to adapt the message from a science audience, to engineering or leadership Key job responsibilities • Analyse complex business problems and translate them into well-defined science plans with clear milestones and success criteria • Design, develop, and deliver ML/AI models end-to-end — from research and prototyping through to production systems at Amazon scale and extending solutions going beyond the state of the art • Work with state-of-the-art models in computer vision, ranking and generative AI to power new customer experiences globally • Own major science challenges for the team, driving solutions from ideation through experimentation to production deployment • Collaborate with a variety of roles and partner teams around the world to deliver integrated solutions • Influence scientific direction and best practices across the team • Maintain high quality standards on team deliverables • Contribute to expanding the state of the art in computer vision, ranking and GenAI through publications and internal knowledge sharing

Amazon is seeking a passionate and inventive Applied Scientist II with a strong machine learning background to build industry-leading Speech and Language technology. Our mission is to deliver delightful customer experiences by advancing Automatic Speech Recognition (ASR), Natural Language Understanding (NLU), Machine Learning (ML), and Computer Vision (CV). You will work alongside internationally recognized experts to develop novel algorithms and modeling techniques that advance the state-of-the-art in human language technology. Your work will directly impact millions of customers through products and services powered by speech and language technology. You will gain hands-on experience with Amazon's heterogeneous speech, text, and structured data sources, and leverage large-scale computing resources to accelerate advances in spoken language understanding. We are hiring across all areas of human language technology: ASR, Machine Translation (MT), NLU, Text-to-Speech (TTS), Dialog Management, and Computer Vision. We also seek talent experienced in building large-scale, high-performing systems. Key job responsibilities Basic Qualifications PhD or M.Tech in Computer Science, Electrical Engineering, Mathematics, or Physics with specialization in one or more of: speech recognition, natural language processing, machine translation, time series analysis, signal processing, or machine learning 1-2 years of industry or research experience (including internships, co-ops, or post-doctoral work) in applied ML or related areas Proficiency in programming languages such as Python, C/C++, or Java Strong foundation in machine learning fundamentals and statistical modeling Preferred Qualifications Experience building speech recognition, machine translation, or natural language processing systems (e.g., commercial products, government projects, or published research with working prototypes) Hands-on experience with deep learning frameworks (e.g., PyTorch, TensorFlow) Track record of publications in top-tier conferences (e.g., NeurIPS, ICML, ACL, Interspeech, CVPR) Scientific thinking with demonstrated ability to innovate and contribute to advancing the field Solid software development practices and experience shipping production-quality code Strong written and verbal communication skills A day in the life 0

The Traffic and Network Modeling team builds the science and software that helps AWS decide how to grow and maintain one of the world's largest networks. We combine rigorous scientific modeling with modern ML and solid engineering to solve problems like: How much network capacity do we need, and where? What infrastructure should be built, and when? As an Applied Scientist on the team, you will: Build and validate ML models for network demand forecasting, topology planning, and capacity optimization Work alongside network engineers, software developers, and supply chain specialists to translate complex infrastructure problems into elegant, production-ready scientific solutions We're part of AWS Infrastructure Services - the team that keeps the cloud running. You'll join an inclusive culture that welcomes bold ideas and empowers you to own them to completion. Key job responsibilities Drive hypothesis-driven research - Propose and validate hypotheses to inform business and product roadmap decisions for network traffic modeling. Build production systems - Work with engineers to deliver low-latency network forecast predictions and scale system throughput. Own problems end-to-end - Understand the needs of networking teams, distill them into coherent projects, and implement solutions with long-term impact in mind. Raise the bar - Use your expertise to set high standards for scientific rigor, and contribute to the growth of teammates through code reviews, design discussions, and knowledge sharing. Tackle hard problems eagerly - Seek out ambiguous, high-impact challenges and drive them to resolution. Learn broadly - Collaborate with network engineers, applied scientists, and software engineers. Your impact will depend on learning from diverse perspectives and leveraging Amazon's vast technical resources effectively. Work backwards from customers - Start with customer problems, design elegant solutions, and implement them for speed and scalability. 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, which is why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. 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 empowers 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. 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 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.

Are you excited about making business decisions using science and data? Are you interested in supporting consumer device concepts from idea inception to launch? Do you want to work on a Science Product team focused on scaling statistics and econometrics with custom tools? If so, this may be the role for you! Amazon.com strives to be Earth's most customer-centric company. The Amazon Devices and Services team focuses on delighting customer by enabling seamless functionality in supplying, entertaining, and managing the home -- and beyond. We seek and hire the world's brightest minds, offering them a fast-paced, technologically-sophisticated, and friendly work environment, where economic theory meets real-world industry. The Decision Science team in Devices owns demand estimates and pricing recommendations of concept devices before customers know they exist. We support devices and services ranging from Echo Frames to Kindle Paperwhite to Blink Video Camera …all prior to launch. We are a cross-functional Product team working to scale Econometrics through Amazon and beyond by incorporating Science into internal facing tools and making it easier for others to do so as well. In this role, you will have input in decision meetings with Amazon senior leadership, which include go/no-go decisions for brand new devices and services and build volume decisions for manufacture prior to receiving any customer signal. You will have direct input to pricing decisions. You will leverage Science and Tools produced by the Decision Science team such as conjoint demand models to produce these recommendations. You will work with Scientists, Economists, Product Managers, and Software Developers to provide meaningful feedback about stakeholder problems to inform business solutions and increase the velocity, quality, and scope behind our recommendations. You will also have the opportunity to work on special projects to both guide the business and advance your own knowledge and understanding of specific topics. Key job responsibilities Applies expertise to develop econometric/machine learning models to measure the demand of devices and the business; Reviews models and results for other scientists, mentors junior scientists; Generates economic insights for the Devices and Services business and work with stakeholders to run the business for effectively; Describes strategic importance of vision inside and outside of team; and, Identifies business opportunities, defines the problem and how to solve it; Engages with senior scientists, business leadership outside Devices and Services to understand interplay between different business units.

Join Amazon's International Seller Services (ISS) Economics team and shape how millions of sellers succeed in the worldwide marketplace through causal inference, LLMs, and generative AI. You'll combine rigorous economic methods with real business impact, building the frameworks and measurement systems that define the future of Amazon's seller services. Key job responsibilities In this role, you will be a people manager and a technical leader in Econometric research with significant scope, impact, and high visibility. You will own developing the economics charter in ISS combining scientific methods with business needs. Your solution will deliver to business leaders accurate and actionable insights and recommendations to optimize and expand their business. As a successful Science Manager, you can navigate ambiguity, lead problem solving, guide development of new frameworks, and credibly interface between technical teams and business stakeholders. You are an innovator who can push the limits on what’s scientifically possible with a razor sharp focus on measurable business impact. You will coach and guide scientists in your team across different job families including Economists, Data Scientists and Applied Scientists to grow the team’s talent and scale the impact of your work. About the team The International Seller Services (ISS) Economics team shapes Amazon's global seller ecosystem through sophisticated economic analysis and data-driven insights. Our mission is to transform how Amazon empowers millions of sellers to succeed in the worldwide digital marketplace.

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

The Amazon Fulfillment Technologies (AFT) Science team is seeking an exceptional Sr. Applied Scientist with strong operations research and optimization expertise to develop production solutions for one of the most complex systems in the world: Amazon's Fulfillment Network. At AFT Science, we design, build, and deploy optimization, statistics, machine learning, and GenAI/LLM solutions that power production systems running across Amazon Fulfillment Centers worldwide. We tackle a wide range of challenges throughout the network, including labor planning and staffing, pick scheduling, stow guidance, and capacity risk management. Our mission is to develop innovative, scalable, and reliable science-driven production solutions that exceed the published state of the art, enabling systems to run optimally and continuously (from every few minutes to every few hours) across our large-scale network. Key job responsibilities As a Senior Applied Scientist, you will collaborate with scientists, software engineers, product managers, and operations leaders to drive the end-to-end lifecycle of optimization-driven solutions that directly impact process efficiency and associate experience in the worldwide fulfillment network. Your key responsibilities include: * Develop deep understanding and domain knowledge of operational processes, system architecture, and business requirements * Dive deep into data and code to identify opportunities for continuous improvement and disruptive new approaches * Design and develop scalable mathematical models for production systems to derive optimal or near-optimal solutions for existing and emerging challenges * Create prototypes and simulations for agile experimentation of proposed solutions * Advocate for technical solutions with business stakeholders, engineering teams, and senior leadership * Partner with software engineers to integrate prototypes into production systems * Design and execute experiments to test new or incremental solutions launched in production * Build and monitor metrics to track solution performance and business impact About the team Amazon Fulfillment Technologies (AFT) designs, develops, and operates end-to-end fulfillment technology solutions that power Amazon Fulfillment Centers worldwide. AFT integrates software, science, and operational processes to optimize how inventory is received, stored, picked, packed, and shipped, enabling Amazon customers to receive the right products at the right time. AFT Science is the central science organization driving scientific solution empowering across all critical AFT charters including inbound, outbound, and labor planning. The Fulfillment Operations Research (FOR) team within AFT Science specializes in optimization, statistics, machine learning, and GenAI/LLM. The team partners closely with software engineering, product, and operations teams to deliver scalable and reliable production solutions while advancing the state of the art in optimization, machine learning, and decision science.