Careers

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

The Artificial General Intelligence (AGI) Customization Team is seeking a highly skilled and experienced Applied Scientist to support adoption and enable customization of Amazon Nova. The role focuses on developing state-of-the-art services and tools for model customization, including supervised fine-tuning, reinforcement learning, and knowledge distillation across large language models. As an Applied Scientist, you will play a important role in developing advanced customization capabilities that enable enterprises to build highly performant application-specific models without the need for training models from scratch. Your work will directly impact how companies leverage Amazon Nova models for their specific use cases. Key job responsibilities - Contribute to the development of novel customization techniques including extended post-training, continued pre-training, and advanced knowledge distillation - Collaborate with cross-functional teams to design and implement enterprise-ready tooling for various training techniques on Amazon SageMaker - Design and execute experiments to optimize model accuracy, latency, and cost across different customization approaches (SFT, DPO, PPO) - Develop and enhance preference learning algorithms and training curricula for customer-specific applications - Create robust evaluation frameworks for assessing model performance across different domains and use cases - Contribute to the development of the Responsible AI toolkit, including creating training and evaluation datasets for model alignment - Design and implement secure access mechanisms for early model checkpoints and weights - Communicate technical insights and results to both technical and non-technical stakeholders through presentations and documentation

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

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 our Amazon Private Brands Selection Guidance organization in building science and tech solutions at scale to delight our customers with products across our leading private brands such as Amazon Basics, Amazon Essentials, and by Amazon. The Selection Guidance team applies Generative AI, Machine Learning, Statistics, and Economics solutions to drive our private brands product assortment, strategic business decisions, and product inputs such as title, price, merchandising and ordering. We are an interdisciplinary team of Scientists, Economists, Engineers, and Product Managers incubating and building day one solutions using novel technology, to solve some of the toughest business problems at Amazon. As an Applied Scientist you apply state-of-the-art research to business problems, invent novel solutions and prototypes, and directly contribute to bringing your ideas to life through production implementation. Current research areas include named entity recognition, product substitutes, pricing optimization, agentic AI, and large language models. You will review and guide scientists across the team on their designs and implementations, and raise the team bar for science research and development. This is a unique, high visibility opportunity for someone who wants to develop ambitious science solutions and have direct business and customer impact. Key job responsibilities - Partner with business stakeholders to deeply understand APB business problems and frame ambiguous business problems as science problems and solutions. - Adapt and apply state-of-the-art machine learning solutions to business problems. - Invent novel science solutions, develop prototypes, and deploy production software to solve business problems. - Review and guide science solutions across the team. - Publish and socialize your and the team's research across Amazon and external avenues as appropriate - Leverage industry best practices to establish repeatable applied science practices, principles & processes.

Amazon is on a mission to redefine the future of automation — and we're looking for exceptional talent to help lead the way. We are building the next generation of advanced robotic systems that seamlessly blend cutting-edge AI, sophisticated control systems, and novel mechanical design to create adaptable, intelligent automation solutions capable of operating safely alongside humans in dynamic, real-world environments. At Amazon, we leverage the power of machine learning, artificial intelligence, and advanced robotics to solve some of the most complex operational challenges at a scale unlike anywhere else in the world. Our fleet of robots spans hundreds of facilities globally, working in sophisticated coordination to deliver on our promise of customer excellence — and we're just getting started. As a Scientist in Robot Navigation, you will be at the forefront of this transformation — architecting and delivering navigation systems that are intelligent, safe, and scalable. You will bring deep expertise in learning-based planning and control, a strong understanding of foundation models and their application to embodied agents, and as well as have in-depth understanding of control-theoretic approaches such as model predictive control (MPC)-based trajectory planning. You will develop navigation solutions that seamlessly blend data-driven intelligence with principled control-theoretic guarantees. Our vision is bold: to build navigation systems that allow robots to move fluidly and safely through dynamic environments — understanding context, anticipating change, and adapting in real time. You will lead research that bridges the gap between cutting-edge academic advances and production grade deployment, collaborating with world-class teams pushing the boundaries of robotic autonomy, manipulation, and human-robot interaction. Join us in building the next generation of intelligent navigation systems that will define the future of autonomous robotics at scale. Key job responsibilities - Design, develop, and deploy perception algorithms for robotics systems, including object detection, segmentation, tracking, depth estimation, and scene understanding - Lead research initiatives in computer vision, sensor fusion and 3D perception - Collaborate with cross-functional teams including robotics engineers, software engineers, and product managers to define and deliver perception capabilities - Drive end-to-end ownership of ML models — from data collection and labeling strategy to training, evaluation, and deployment - Mentor junior scientists and engineers; contribute to a culture of technical excellence - Define and track key metrics to measure perception system performance in real-world environments - Publish research findings in top-tier venues (CVPR, ICCV, ECCV, ICRA, NeurIPS, etc.) and contribute to patents A day in the life - Train ML models for deployment in simulation and real-world robots, identify and document their limitations post-deployment - Drive technical discussions within your team and with key stakeholders to develop innovative solutions to address identified limitations - Actively contribute to brainstorming sessions on adjacent topics, bringing fresh perspectives that help peers grow and succeed — and in doing so, build lasting trust across the team - Mentor team members while maintaining significant hands-on contribution to technical solutions About the team Our team is a group is a diverse group of scientists and engineers passionate about building intelligent machines. We value curiosity, rigor, and a bias for action. We believe in learning from failure and iterating quickly toward solutions that matter.

Alexa for Shopping (Rufus) is Amazon's new AI-powered shopping assistant that combines the capabilities of Rufus and Alexa+ to provide a more personalized and intelligent shopping experience. We are building the future of AI-powered commerce, where every customer interaction is conversational, personalized, and proactive. We are seeking a Director, Applied Science to lead the science vision and execution for the next-generation conversational AI platform. This leader will own the end-to-end science roadmap for a multi-agent architecture powered by large language models (LLMs), SLMs, reinforcement learning (RL), and post-training optimization to deliver the most helpful, accurate, and fastest AI shopping assistant in the industry. This is a transformational leadership role. You will lead the science that makes this possible: distilling Amazon's vast data assets into rich context, building specialized models through fine-tuning and RL that match frontier model quality at a fraction of the latency, and architecting intelligent agent routing across diverse use cases (pre-purchase, post-purchase, cross-Amazon services). The ideal candidate is deeply steeped in LLM-based architectures, post-training techniques (RLHF, DPO, fine-tuning), and multi-agent systems. They are passionate about applied science, working back from customer experience to define what matters, and building teams that ship production AI at scale. This leader will shape the science philosophy for one of Amazon's highest-visibility AI initiatives. Key job responsibilities - Define and execute the science strategy for Alexa for Shopping conversational AI platform - Lead a large, multidisciplinary organization of Applied Scientists, Research Scientists, and Machine Learning Engineers. - Architect and scale multi-agent systems - Partner with Product, Engineering, and senior leadership (including S-team) to align AI investments with long-term business goals and the vision of conversational commerce replacing traditional shopping paradigms. - Establish scientific best practices across experimentation, evaluation, model iteration, and production deployment for a high-traffic, latency-sensitive customer-facing system. - Mentor and develop senior technical leaders; foster a culture of innovation, customer obsession, and operational excellence.

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.

Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video subscriptions such as Apple TV+, HBO Max, Peacock, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video team member, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! Key job responsibilities - Lead research and development of speech and audio generation technology and end-to-end speech-to-speech architecture - Develop audio processing solutions for production environments, including source separation, enhancement, and mixing - Define the research roadmap for your area, identify high-impact problems, and communicate technical direction to senior leadership - Publish research, contribute to the broader scientific community, and bring external advances into production systems - Hire, mentor, and develop applied scientists. Grow the team's capabilities to meet evolving customer and business needs About the team This team's mission is to deeply understand all content and empower all customers with relevant language options, innovative accessibility assists, and rich title-information across all their content-experiences on Prime Video. We create and publish content on-time that's meaningful, accurate, and accessible to every customer globally. We delight our customers by pushing the boundaries of content understanding and enrichment. Through inclusion and innovation, we do the most fulfilling work of our career.

Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video technologist, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! As a Applied Scientist in the Prime Video Playback Intelligence organization, you will have deep subject matter expertise in applied machine learning and data science, with specializations in video streaming optimization, information retrieval, anomaly detection and root-causing systems, large language models, and generative AI across various modalities. Key job responsibilities * You will work with multiple teams of scientists, engineers, and product managers to translate business and functional requirements into concrete deliverables leading strategic efforts to enhance customer quality of experiences. * Problem spaces you will be working on include: improving the customer playback quality of experience across Video on Demand, Live Events and Linear Content. You’ll aim to reduce the time/cost/effort to optimize the customer experience as well as detect, root-cause, and mitigate defects in the customer experience. You’ll seek to understand the depth and nuance of streaming video at scale and identify opportunities to grow our business and improve customer quality of experience via principled ML/AI solutions. You will also lead integration of new algorithms and processes into existing modeling stacks, simplify and streamline the existing modeling stacks, and develop testing and evaluation strategies. Ultimately, you'll work backwards from the desired outcomes and lead the way on determining the ideal solution (statistical techniques, traditional ML, GenAI, etc). * You will be responsible for defining key research directions, adopting or inventing new machine learning techniques, conducting rigorous experiments, publishing results, and ensuring that research is translated into practice. You will develop long-term strategies, persuade teams to adopt those strategies, propose goals and deliver on them.