Careers

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.

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.

Are you interested in shaping the future of Advertising and B2B Sales? We are a growing team with an exciting AI-first charter and need your passion, innovative thinking, and creativity to help take our products to new heights. Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. Our products are strategically important to our businesses driving long term growth. We break fresh ground in product and technical innovations every day! Within the Advertising Sales organization, we are building a central AI/ML team and are seeking top Applied Science talent to help us build new, science-backed services that drive success for our customers. Our goal is to transform the way account teams operate by creating AI agents that help optimize their end-to-end workflows, and developing actionable insights and recommendations they can share with their advertising accounts As an Applied Scientist on the team with a specific focus on creating autonomous AI agents that can operate accurately at large scale, you will bring deep expertise in Natural Language Processing (inc. tokenization, syntactic parsing, named entity recognition (NER), sentiment analysis, text classification), Large Language Models (inc. foundation model fundamentals, post-training, reward modeling, RAG, transformer architecture), Deep Learning, Reinforcement Learning and/or Recommender Systems. You have the scientific and technical skills to build and refine models that can be implemented in production and you continuously measure the performance of your system to drive continuous improvements. You will contribute to chart new courses with our ad sales support technologies, and you have the communication skills necessary to explain complex technical approaches to a variety of stakeholders and customers. You will be part of a team of fellow scientists and engineers taking on iterative approaches to tackle big, long-term problems. You are fluently able to leverage the latest Generative AI systems and services to accelerate and improve your work while maintaining high quality in your work outputs. Key job responsibilities Scientific Modeling - Conceptualize and lead state-of-the-art research on new Reinforcement Learning, Deep Learning, NLP, LLM, (Generative) Artificial Intelligence and Recommender System solutions to create AI agents and optimize all aspects of the Ad Sales business - Lead the technical approach for the design and implementation of successful models and algorithms in support of expert cross-functional teams delivering on demanding projects - Run regular A/B experiments, gather data, and perform statistical analysis - Improve the scalability, efficiency and automation of large-scale data analytics, model training, deployment and serving - Publish scientific findings in reports and papers that can be shared internally and externally Product Development Support - Partner with software engineering and product management teams to support product and service development, define success metrics and measurement approaches, and help drive adoption of innovative new features for our services. - Lead requirements gathering sessions with product teams and business stakeholders - Maintain scientific documentation and knowledge for product initiatives Collaboration & Communication - Work closely with software engineers to deliver end-to-end solutions into production - Translate complex scientific findings into actionable business recommendations for stakeholders and senior management - Provide clear, compelling reports and presentations on a regular basis with respect to your models and services - Communicate with internal teams to showcase results and identify best practices. About the team Sales AI is a central science and engineering organization within Amazon Advertising Sales that powers selling motions and account team workflows via state-of-the-art of AI/ML services. Sales AI is investing in a range of sales intelligence models, including the development of advertiser insights, recommendations and Generative AI-powered applications throughout account team workflows.

Amazon Seller Assistant is our flagship GenAI-first, multi-agent system that reimagines seller experience. Our vision is to provide each seller with a proactive, autonomous, agentic assistant that understands their business and helps them navigate the complexities of selling by anticipating their needs, surfacing insights, resolving issues, taking actions on their behalf, and helping them grow. Amazon Seller Assistant helps millions of sellers on Amazon serve billions of customers worldwide. We are seeking a world-class Applied Scientist to help define and build the next generation of Amazon Seller Assistant. You will partner with top-tier scientists and engineers to launch production-grade agentic capabilities at Amazon's scale — owning your problem space end-to-end, from a crisp customer insight to a shipped product that millions of sellers rely on. Key job responsibilities - Use state-of-the-art Machine Learning and Generative AI techniques to create the next generation of the tools that empower Amazon's Selling Partners to succeed. - Design, develop and deploy highly innovative models to interact with Sellers and delight them with solutions. - Work closely with teams of scientists and software engineers to drive real-time model implementations and deliver novel and highly impactful features. - Establish scalable, efficient, automated processes for large scale data analyses, model benchmarking, model validation and model implementation. - Research and implement novel machine learning and statistical approaches. - Participate in strategic initiatives to employ the most recent advances in ML in a fast-paced, experimental environment. About the team Amazon Seller Assistant team operates at the very frontier of agentic AI and agentic commerce — not as a research group, but as a team shipping production-grade, multi-agent systems used by millions of sellers worldwide. We move with the urgency of a startup and the resources of the world's most customer-obsessed company, transforming the latest breakthroughs in science and engineering into capabilities that sellers rely on every day.

Amazon's Last Mile Geospatial Science team leverages sate of the art computer vision, generative AI, and deep learning to enhance vehicle navigation and ensure safe, efficient deliveries by enriching map data from billions of satellite, aerial, and street-level images and videos. The role involves building large-scale machine learning systems that analyze terabytes of multimodal data to solve novel problems, translating business requirements into prototypes while prioritizing driver and customer safety. The team seeks scientists who can combine domain expertise with machine learning to invent and implement state-of-the-art solutions in a collaborative environment with direct business impact. Key job responsibilities Successful candidates should have a deep knowledge (both theoretical and practical) of various machine learning algorithms for large scale computer vision problems, the ability to map models into production-worthy code, the communication skills necessary to explain complex technical approaches to a variety of stakeholders and customers, and the excitement to take iterative approaches to tackle big, long term problems. The applied scientist should be proficient with image and video analysis using machine learning, including designing architecture from scratch, modify existing loss functions, full model training, fine-tuning, and evaluating the latest deep learning models. The applied scientist optimizes different models for specific platforms, including edge devices with restricted resources. Generative AI, Multi-modal models, e.g., Large Vision Language Models, zero-shot, few-shot, and semi-supervised learning paradigms are used extensively.

Stores Economics and Science (SEAS) is an interdisciplinary science and engineering team in Amazon's Stores organization with a peak-jumping mission: we apply expertise in science and engineering to move from local to global optima in methods, models, and software. We pursue this mission by leveraging frontier science; collaborating with partner teams; and learning from the tools, experience, and perspective of others. We scale by solving problems, first in the small to prove concepts, and then in the large by building scalable solutions. We also help other teams within Amazon scale by hiring and developing the best and embedding them in other business units. In 2024, we are focused on economics and science in areas related to (1) improving delivery speed and lowering cost-to-serve, (2) seller fees and incentives, and (3) emerging machine learning. We also have some ongoing and highly-leveraged collaborations that help partner teams inside Amazon short-circuit months of R&D or otherwise look around corners. We are looking for an Applied Scientist to build and deliver state-of-the-art science and engineering solutions to improve our Stores business. In this role, you will work in a team of scientists and engineers with backgrounds in machine learning, NLP, IR, statistics, and economics to identify bottlenecks in our business, conceive new ideas to overcome those challenges, and deploy scientific solutions in partnership with product teams. Your responsibilities include developing and maintaining the scientific models, benchmarks, and services. Graduate education or hands-on experience in machine learning, optimization, causal inference, Bayesian statistics, deep learning, or other quantitative scientific fields is a big plus. To be successful in this role, you should be a quick learner and comfortable with a high degree of ambiguity.

Are you looking for an opportunity to build an LLM-based enterprise-grade, highly available, large scale solution? Does it excite you to find patterns and build generic, composable solutions to solve complex problems? Are you looking for inventing newer and simpler ways of building solutions? If so, we are looking for you to fill a challenging position in Alexa Enterprise (AE) team. AE brings the power of Alexa voice assistant to enterprise partners in industries such as hospitality and senior living. We are inventing Large Language Models (LLM)-driven interactions to create memorable moments for users while simultaneously boosting partner revenues and reinforcing brand identity. Beyond managed properties, AE extends Alexa's reach to premium third-party electronic devices. AE team is looking for a highly skilled and inventive Applied Scientist, with a strong machine learning background, to lead the development and implementation of state-of-the-art ML systems for Alexa Enterprise use cases. As an Applied Scientist in the team, you will play a critical role in driving the development of conversational assistants, in particular those based on Large Language Models (LLM's), that meet enterprise standards. You will handle Amazon-scale use cases with significant impact on our customers' experiences. 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.

Are you inspired by invention? Is problem solving through teamwork in your DNA? Do you like the idea of seeing how your work impacts the bigger picture? Answer yes to any of these and you’ll fit right in here at Amazon Robotics. We are a smart team of doers that work passionately to apply advances in robotics and software to solve real-world challenges that will transform our customers’ experiences in ways we can’t even imagine yet. We invent new improvements every day. We are Amazon Robotics and we will give you the tools and support you need to invent with us in ways that are rewarding, fulfilling and fun. Amazon Robotics is seeking experienced and Senior Applied Scientist with a passion for robotic research. Our team works on challenging and high-impact projects within robotics. Examples of projects include allocating resources to complete a million orders a day, coordinating the motion of thousands of robots and identifying objects and damage. Key job responsibilities - Lead research initiatives advancing AI-driven structured field robotics (path planning, fleet coordination, control systems) and translate breakthroughs into production solutions at global scale - Own end-to-end delivery of complex algorithmic solutions from design through production deployment and operational maintenance - Drive technical decisions for Control, Coordination, and Path Planning systems meeting performance, scalability, and reliability requirements - Partner with cross-functional teams to translate business requirements into research problems and assess technical risks - Influence technical direction across the broader robotics organization through design reviews and technical discussions with senior engineers and scientists - Demonstrate measurable impact through AI-driven algorithmic improvements: fleet efficiency gains, operational cost reduction, system reliability improvements, and enhanced customer experience - Publish findings at top-tier AI and robotics conferences representing organizational technical leadership - Mentor junior Applied Scientists on research methodology and balancing innovation with production constraints - Operate independently on ambiguous, multi-quarter problems requiring novel AI approaches while navigating tradeoffs between research innovation and production constraints A day in the life Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: - Medical, Dental, and Vision Coverage - Maternity and Parental Leave Options - Paid Time Off (PTO) - 401(k) Plan If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply! About the team We're the structured field robotics organization powering large-scale mobile robotics operations globally. Our mission is to enable safe, efficient, and reliable robotic operations through intelligent Control, Coordination, and Path Planning systems. We operate at the intersection of planning, algorithmic, and ML research with production systems, owning the full stack from innovation to deployment. Our culture balances research excellence with operational ownership. Applied Scientists partner closely with engineers: reviewing code, contributing to research discussions, and solving problems together. We value deep technical expertise alongside pragmatic engineering judgment. We invest in our people through mentorship and encourage conference participation and knowledge sharing.

We are looking for a passionate, talented, and inventive Data Scientist with a strong machine learning and analytics background to help build industry-leading language technology powering Rufus, our AI-driven search and shopping assistant, helping customers with their shopping tasks at every step of their shopping journey. This innovative role focuses on developing conversation-based, multimodal shopping experiences, utilizing data analysis, statistical modeling, machine learning (ML) technologies, and experimentation to drive product decisions and optimize customer experiences. Our mission in conversational shopping is to make it easy for customers to find and discover the best products to meet their needs by helping with their product research, providing comparisons and recommendations, answering product questions, enabling shopping directly from images or videos, providing visual inspiration, and more. We do this by leveraging advanced analytics, Natural Language Processing (NLP), Machine Learning (ML), A/B testing, causal inference, and data-driven insights to continuously improve our systems. Key job responsibilities Key job responsibilities As a Data Scientist on our team, you will be responsible for the analysis, modeling, and optimization of AI technologies that will shape the future of shopping experiences. You will play a critical role in measuring and improving multimodal conversational systems, in particular those based on large language models, information retrieval, recommender systems and knowledge graphs, to be tailored to customer needs. You will handle Amazon-scale use cases with significant impact on our customers' experiences. You will collaborate with scientists, engineers, and product partners locally and abroad. Your work will include designing experiments, analyzing results, and launching new features, products and systems. A day in the life You will: Perform hands-on analysis and modeling of enormous multimodal datasets to develop insights into how to best help customers throughout their shopping journeys. Use statistical methods, machine learning, and data mining techniques to create scalable solutions for measuring and optimizing shopping assistant systems based on a rich set of structured and unstructured contextual signals. Design and analyze A/B tests and experiments to evaluate new features and model improvements, ensuring statistical rigor and actionable insights. Develop metrics, dashboards, and reporting frameworks to monitor system performance, customer engagement, and business impact. Build predictive models and conduct deep-dive analyses to identify opportunities for improving customer experience, conversion, and satisfaction. Collaborate with Applied Scientists and Engineers to translate analytical insights into production systems, working closely on model evaluation and deployment. Establish automated processes for large-scale data analysis, ETL pipelines, metric generation, and experimentation frameworks. Communicate results and insights to both technical and non-technical audiences, including through presentations, written reports, and data visualizations. About the team The Rufus Features Science team, based in London, works alongside ~150 engineers, designers and product managers, shaping the future of AI-driven shopping experiences at Amazon. The team works on every aspect of the Rufus AI, from making Rufus agentic, enabling customers to set price alerts or empower Rufus to act on their behalf and automatically purchase products when the price is right, to understanding multimodal user queries and generating answers that combine text, image, audio and video, including deep research reports that scour the web and the Amazon catalog to provide detailed and personalised shopping guidance. We utilize and advance state-of-art techniques in the fields of Natural Language Processing, gen AI, Information Retrieval, Machine/Deep Learning, and Data Mining. We validate our work by actively participating in the internal and external scientific communities.

Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the limits. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. As a Senior Applied Scientist on our team, you will focus on building state-of-the-art ML models for healthcare. Our team rewards curiosity while maintaining a laser-focus in bringing products to market. Competitive candidates are responsive, flexible, and able to succeed within an open, collaborative, entrepreneurial, startup-like environment. At the forefront of both academic and applied research in this product area, you have the opportunity to work together with a diverse and talented team of scientists, engineers, and product managers and collaborate with other teams. This role offers a unique opportunity to work on projects that could fundamentally transform healthcare outcomes. Key job responsibilities In this role, you will: • Design and implement novel AI/ML solutions for complex healthcare challenges • Drive advancements in machine learning and data science • Balance theoretical knowledge with practical implementation • Work closely with customers and partners to understand their requirements • Navigate ambiguity and create clarity in early-stage product development • Collaborate with cross-functional teams while fostering innovation in a collaborative work environment to deliver impactful solutions • Establish best practices for ML experimentation, evaluation, development and deployment • Partner with leadership to define roadmap and strategic initiatives You’ll need a strong background in AI/ML, proven leadership skills, and the ability to translate complex concepts into actionable plans. You’ll also need to effectively translate research findings into practical solutions. A day in the life You will solve real-world problems by getting and analyzing large amounts of data, generate insights and opportunities, design simulations and experiments, and develop statistical and ML models. The team is driven by business needs, which requires collaboration with other Scientists, Engineers, and Product Managers across the Special Projects organization. You will prepare written and verbal presentations to share insights to audiences of varying levels of technical sophistication. About the team We represent Amazon's ambitious vision to solve the world's most pressing challenges. We are exploring new approaches to enhance research practices in the healthcare space, leveraging Amazon's scale and technological expertise. We operate with the agility of a startup while backed by Amazon's resources and operational excellence. We're looking for builders who are excited about working on ambitious, undefined problems and are comfortable with ambiguity.