Careers

"We see our customers as invited guests to a party, and we are the hosts. It's our job every day to make every important aspect of the customer experience a little bit better." - Jeff Bezos, Founder & CEO. We didn’t make Amazon a trillion-dollar company, our customers did and we want to ensure that our customers always have a positive experience that keeps them coming back to Amazon. To help achieve this, the Worldwide Defect Elimination (WWDE) team relentlessly focuses on maintaining customer trust by building products that offer appropriate resolutions to resolve issues faced by our customers. WWDE scientists solve complex problems and build scalable solutions to eliminate systemic defects and prevent future issues. As a Sr. Applied Scientist, your role is pivotal in leveraging advanced Artificial Intelligence (AI) and Machine Learning (ML) techniques to address customer issues at scale. You'll lead the development of innovative solutions that detect and organize issues, identify root causes, and route them to resolving teams across the company. You will leverage a spectrum of scientific techniques across both classical ML and Natural Language Processing/Generative AI (NLP/GenAI) to comb over our billions of customer interactions (using a combination of media). In this role, you will collaborate with cross-functional teams (Product, Engineering, Program) and contribute to advancing the state of defect elimination research. Key job responsibilities - Deliver solutions to the core business problems and influencing business partners - Research and develop modeling techniques for NLP, DL, and ML - Establish scientific culture and standards for all the scientists (publication, best practices, reviews, etc.) - Develop scientific talent on the team 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

The Worldwide Defect Elimination (WWDE) team within Amazon Customer Service is seeking a highly skilled economist to estimate the customer impact of each customer service action. Your analysis will assist teams across Amazon to prioritize defect elimination efforts and optimize how we respond to customer contacts. You will partner closely with our product, program, and engineering teams to deliver your findings to users via systems and dashboards that guide Customer Service planning and policies. Key job responsibilities - Develop causal, economic, and machine learning models at scale. - Engage in economic analysis; raise the bar for research. - Inform strategic discussions with senior leaders across the company to guide policies. A day in the life 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! 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 About the team The WWDE team's mission is to understand and resolve all issues impacting customers and connect all organizations in Amazon to customer experiences. Our vision is to be the ultimate steward of the Voice of the Customer (VoC), empowering customer service, and Amazon teams to easily measure, listen, and act on customer feedback. The team broadly supports defect detection, root cause identification, and resolution to earn customer trust. The Customer Service Economics & Optimization team is a force multiplier within this group. Through causal analysis, we estimate the effectiveness of our efforts to delight the customer.

We have an exciting position within Alexa for an Applied Scientist with a strong background NLP and Large Language Models to help us develop state-of-the-art conversational systems. As part of this team, you will collaborate with talented scientists and software engineers to enable conversational assistants capabilities to support the use of external tools and sources of information, and develop novel reasoning capabilities to revolutionise the user experience for millions of Alexa customers. Key job responsibilities As an Applied Scientist, you will develop innovative solutions to complex problems to extend the functionalities of conversational assistants . You will use your technical expertise to research and implement novel algorithms and modelling solutions in collaboration with other scientists and engineers. You will analyse customer behaviours and define metrics to enable the identification of actionable insights and measure improvements in customer experience. You will communicate results and insights to both technical and non-technical audiences through written reports, presentations and external publications.

Want to help develop the next generation of intelligent assistant products? Join us! We are looking for a talented Applied Science Manager to help us. Key job responsibilities You will lead a team of scientists to improve our RAG applications. You will be responsible for: (i) developing novel retrieval and ranking models and partnering closely with engineering to improve model performance; (ii) improve content and query understanding models to deliver improved signal to retrieval and ranking models; (iii) partner closely with content acquisition and LLM client teams to ensure our dependencies are met and we’re delivering value to the end customers, enhancing information grounding for LLMs; (iv) develop a science roadmap, including publication opportunities and how we can accelerate delivery of customer impact; (v) coach and develop the team, hire, and hold the bar on scientific rigor throughout the team. A day in the life A mix of (i) technical deep dives: working with the team to develop the right models, setup good experiments, debug models, etc. (ii) coaching and development: providing feedback, setting up mechanisms to ensure the team’s success, and (iii) working with customers and dependency teams to ensure delivery.

In Stores Security, we develop authorization solutions using attribute-based access control (ABAC) to enable Amazon to enforce fine-grained access control (FGAC) on sensitive data. We create logging solutions that generate access events from thousands of services for evidence collection. Additionally, we implement rule-based and machine learning systems to monitor access to customer data, detect anomalous activities, and demonstrate compliance. We are seeking a talented, self-directed Applied Scientist to work on the cutting edge security technologies. You'll design and run experiments, research new algorithms, and find new ways of protecting Amazon's customer trust. Besides theoretical analysis and innovation, you will work closely with talented engineers to put your algorithms and models into practice. You should thrive in ambiguous environments that require to find solutions to problems that have not been solved before. You enjoy and succeed in fast paced environments where learning new concepts quickly is a must. You leverage your exceptional technical expertise, a sound understanding of the fundamentals of Computer Science, and practical experience in building large-scale distributed systems. Your strong communication skills enable you to work effectively with both business and technical partners. Key job responsibilities - Process and analyze large data sets using as many techniques as necessary - Deliver scalable models that can analyze large data sets efficiently - Build mathematical models to detect and classify specific data elements with high accuracy - Prototype these models by using high-level modeling languages such as Python. A software team will be working with you to transform prototypes into production. - Create, enhance, and maintain technical documentation, and present to other scientists and business leaders.

The Worldwide Defect Elimination (WWDE) Team within Amazon Customer Service is seeking a highly skilled economist to estimate the customer impact of each Customer Service action. Your analysis will assist teams across Amazon to prioritize defect elimination efforts and optimize how we respond to customer contacts. You will partner closely with our product, program, and engineering teams to deliver your findings to users via systems and dashboards that guide Customer Service planning and policies. Key job responsibilities - Develop causal, economic, and machine learning models at scale. - Engage in economic analysis; raise the bar for research. - Inform strategic discussions with senior leaders across the company to guide policies. A day in the life 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! 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 About the team The WWDE team's mission is to understand and resolve all issues impacting customers and connect all organizations in Amazon to customer experiences. Our vision is to be the ultimate steward of the Voice of the Customer (VoC), empowering CS and Amazon teams to easily measure, listen, and act on customer feedback. The team broadly supports defect detection, root cause identification, and resolution to earn customer trust. The Customer Service Economics & Optimization team is a force multiplier within this group. Through causal analysis, we estimate the effectiveness of our efforts to delight the customer.

Amazon AI is looking for an Applied Scientist to join our science team in the area of Multimodal Learning, Large Language Models, Natural Language Processing and Speech/Audio Representation Learning. Our organization develops the science that drives the cloud-based AI services of AWS. Our mission is to put the power of AI into the hands of every developer. We seek to advance the state of the art in machine learning to create services that delight our customers and meet real-world business needs. As an Applied Scientist you will partner with talented scientists and engineers to design, train, test, and deploy machine learning models. You will contribute to innovative features, improve our services based on customer requirements and help maintain a highly scalable data and model management infrastructure that supports cutting-edge research. You will be responsible for translating business and engineering requirements into deliverables and software products. We are looking for candidates who thrive in an exciting, fast-paced environment and who have a strong personal interest in learning, researching, and creating new technologies with high customer impact. Prior domain knowledge in multimodal learning, unsupervised speech/audio representations, natural language processing, or computer vision is strongly preferred; solid knowledge of fundamentals of statistics, machine learning, and deep learning is required. Candidates should possess strong software engineering skills and several years of industry experience. About the team About AWS Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. 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. 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 & 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. This team is part of AWS Utility Computing: Utility Computing (UC) AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services.

Are you passionate about pushing the boundaries of computer vision and machine learning to create innovative consumer products? Join Amazon Lab126's Camera and Sensors Group in shaping the future of wearables, Echo devices, Fire TVs, and consumer robotics. About the Role: As a Principal Applied Scientist, you will lead cutting-edge productization of computer vision and machine learning, directly impacting millions of customers worldwide. You'll work with a diverse team of engineers and scientists to solve complex problems and bring revolutionary products to market. Key job responsibilities Key Responsibilities: * Drive strategic vision and long-term roadmap for camera and sensor technologies, influencing product teams and aligning direction across technology, silicon, and devices organizations * Lead groundbreaking ML/CV innovations, focusing on differentiated hardware technologies for advanced camera and sensor capabilities * Architect and implement state-of-the-art ML models for edge computing in consumer products, optimizing for performance and efficiency * Guide the development of next-generation AI-enabled devices, including wearables, Echo devices, Fire TVs, and robotics * Guide the invention and design of next-generation wearables, Echo devices, Fire TVs, and robotics * Collaborate with cross-functional teams to integrate ML solutions into hardware designs * Mentor and develop team members, fostering innovation and technical excellence About the team At Amazon, we're guided by our Leadership Principles, including "Customer Obsession," "Invent and Simplify," and "Learn and Be Curious." We value innovative thinking and diverse perspectives to solve complex challenges. This role offers a unique opportunity to work on ML applications that directly improve people's daily lives. You'll be part of a collaborative team integrating AI into everyday devices, making advanced technology accessible to all. We're committed to fostering an inclusive environment where everyone can do their best work and maintain a healthy work-life balance.

The Amazon Postdoctoral Science Program offers recent PhD graduates an exciting opportunity to gain hands-on industry experience, apply their specialized knowledge, and collaborate with Amazon's leading scientists. This program is designed for researchers who have completed their PhD within the past two years and are eager to bridge academia and industry, driving innovation at scale. “This program provides an excellent and fun opportunity to work on cutting-edge customer-obsessed research and learn from and collaborate with some of the brightest researchers and leading experts at Amazon,” said Sareh Nabi, a postdoctoral scientist in Amazon Ads who is participating in a postdoc pilot program. “It also provides a great platform to take the skillset I learned and apply it to a wide range of real-world applications on a large scale.” “This is an opportunity for outstanding researchers to work with us on our hardest scientific challenges,” said Jeremy Wyatt, senior manager of Amazon Robotics AI. “Amazon postdoctoral scientists will pursue exploratory work on our hardest problems, gaining industry experience and publishing the results in the best scientific venues.” Postdoctoral scientists will contribute to high-impact research initiatives, advance cutting-edge scientific developments, and publish their work in top-tier scientific journals. Participants will benefit from mentorship, access to Amazon's world-class resources, and exposure to real-world challenges with immediate customer impact. **Focus Areas** We are seeking candidates with expertise in foundational and applied research, particularly in: - Large Language Models (LLMs): Experience developing, fine-tuning, and scaling LLMs for diverse applications. - Graph Databases: Strong understanding of graph theory, data modeling, and implementation of graph database technologies in complex systems. - Mathematical Optimization: Good understanding of mathematical optimization, including mixed-integer optimization, combinatorial optimization, and robust optimization. **Basic Qualifications** - PhD in a relevant field (e.g., Computer Science, Operations Research, Mathematics, Statistics) received within 2 years of program start date. - Proven publication record in areas such as LLM, NLP, Generative AI, Graph Database, or other relevant domains. - Hands-on experience with technologies related to large language models, graph databases, and mathematical optimization. Preferred qualifications Postdocs demonstrate the following preferred job qualifications: - Ability to independently deliver results in a fast-paced environment - Publications at top-tier, peer-reviewed conferences and/or journals such as NurIPS, ICML, ICLR, CIKM, ICDE - Exceptional verbal and written communication skills - Expert knowledge in modeling and performance, operationalization, and scalability of scientific techniques and establishing decision strategies Required application materials: - CV, which lists all peer-reviewed publications and conferences - Research statement that outlines your research achievements and future research interests, and - A journal article or book chapter that demonstrates your domain expertise

We are looking for a passionate, talented, and inventive Applied Scientist with a strong machine learning 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 multimodal large language models (MLLMs), generative AI, advanced machine learning (ML) technologies and computer vision. 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 pushing the SoTA in Natural Language Processing (NLP), Generative AI, Multimodal Large Language Model (MLLM), Natural Language Understanding (NLU), Machine Learning (ML), Retrieval-Augmented Generation (RAG), Computer Vision, Responsible AI, LLM Agents, Evaluation, and Model Adaptation. Key job responsibilities As an Applied Scientist on our team, you will be responsible for the research, design, and development of new AI technologies that will shape the future of shopping experiences. You will play a critical role in driving the development of multimodal conversational systems, in particular those based on large language models, information retrieval, recommender systems and knowledge graph, 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 inventing, experimenting with, and launching new features, products and systems. You will: - Perform hands-on analysis and modelling of enormous multimodal datasets to develop insights into how to best help customers throughout their shopping journeys. - Use deep learning, ML and MLLM techniques to create scalable language model centric solutions for building shopping assistant systems based on a rich set of structured and unstructured contextual signals. - Innovate new methods for understanding, extracting, retrieving and summarising contextual information that allows for the effective grounding of MLLMs, considering memory, compute, latency and quality. - Drive end-to-end MLLM projects that have a high degree of ambiguity, scale and complexity. - Build models, perform offline and A/B test experiments, optimize and deploy your models into production, working closely with software engineers. - Establish automated processes for large-scale data analysis and generation, machine-learning model development, model validation and serving. - Communicate results and insights to both technical and non-technical audiences, including through presentations and written reports and publish your work at internal and external conferences. About the team You will be part of a dynamic science team based in London, working alongside over 100 engineers, designers and product managers, focused on shaping the future of AI-driven shopping experiences at Amazon. This team works on every aspect of the shopping experience, from understanding multimodal user queries to planning and generating answers that combine text, image, audio and video.