Careers

RBS (Retail Business Services) Tech team works towards enhancing the customer experience (CX) and their trust in product data by providing technologies to find and fix Amazon CX defects at scale. Our platforms help in improving the CX in all phases of customer journey, including selection, discoverability & fulfilment, buying experience and post-buying experience (product quality and customer returns). The team also develops GenAI platforms for automation of Amazon Stores Operations. As a Sciences team in RBS Tech, we focus on foundational ML research and develop scalable state-of-the-art ML solutions to solve the problems covering customer experience (CX) and Selling partner experience (SPX). We work to solve problems related to multi-modal understanding (text and images), task automation through multi-modal LLM Agents, supervised and unsupervised techniques, multi-task learning, multi-label classification, aspect and topic extraction for Customer Anecdote Mining, image and text similarity and retrieval using NLP and Computer Vision for product groupings and identifying duplicate listings in product search results. Key job responsibilities As an Applied Scientist, you will be responsible to design and deploy scalable GenAI, NLP and Computer Vision solutions that will impact the content visible to millions of customer and solve key customer experience issues. You will develop novel LLM, deep learning and statistical techniques for task automation, text processing, image processing, pattern recognition, and anomaly detection problems. You will define the research and experiments strategy with an iterative execution approach to develop AI/ML models and progressively improve the results over time. You will partner with business and engineering teams to identify and solve large and significantly complex problems that require scientific innovation. You will help the team leverage your expertise, by coaching and mentoring. You will contribute to the professional development of colleagues, improving their technical knowledge and the engineering practices. You will independently as well as guide team to file for patents and/or publish research work where opportunities arise. The RBS org deals with problems that are directly related to the selling partners and end customers and the ML team drives resolution to organization level problems. Therefore, the Applied Scientist role will impact the large product strategy, identifies new business opportunities and provides strategic direction which is very exciting.

RBS (Retail Business Services) Tech team works towards enhancing the customer experience (CX) and their trust in product data by providing technologies to find and fix Amazon CX defects at scale. Our platforms help in improving the CX in all phases of customer journey, including selection, discoverability & fulfilment, buying experience and post-buying experience (product quality and customer returns). As a Sciences team in RBS Tech, we focus on foundational ML research and develop scalable state-of-the-art ML solutions to solve the problems covering customer experience (CX) and Selling partner experience (SPX). We work to solve problems related to multi-modal understanding (text and visual), supervised and unsupervised techniques, multi-task learning, multi-label classification, aspect and topic extraction for Customer Anecdote Mining, product similarity, using GenAI, LLMs, NLP and Computer Vision. Key job responsibilities As an Applied Science Manager, you will be responsible to design and deploy scalable GenAI, NLP and Computer Vision solutions that will impact the content visible to millions of customer and solve key customer experience issues. You will Lead scientists on the team and oversee research and development projects at various stages ranging from initial exploration to deployment into production systems. You will partner with business and engineering teams to identify and solve large and significantly complex problems that require scientific innovation. You will help the team leverage your expertise, by coaching and mentoring. You will contribute to the professional development of colleagues, improving their technical knowledge and the engineering practices. You will create the environment in the team to file for patents and/or publish research work where opportunities arise. You will impact the large product strategy, identifies new business opportunities and provides strategic direction to the team.

As part of the AWS Applied AI Solutions organization, we have a mission to build delightful AI solutions that improve human capabilities and business outcomes. We will accomplish this by accelerating our customers' businesses through delivery of intuitive and differentiated AI solutions that solve enduring business challenges. We blend vision with curiosity and Amazon's real-world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are no-brainers to buy and easy to use. The Applied Scientist will contribute to the development of Agentic AI solutions leveraging Gen AI. The role requires extending existing scientific techniques and inventing new ones to address specific customer needs. You should be comfortable working semi-autonomously on difficult problems with visible risks or roadblocks. You'll work closely with technical leaders within the team. We're looking for scientists who can maintain high standards while moving quickly, prioritizing both rapid experimentation and responsible AI development to deliver measurable customer impact. Key job responsibilities * Design and implement solutions that extend or adapt scientific approaches for customer needs * Deliver components into production that meet high quality standards (efficient, reproducible, testable code) * Produce science outputs demonstrating correctness, scholarship, and scientific rigor * Work with product, engineering, and science teams to deliver impactful AI features * Contribute to operational excellence in the team's deliverables About the team AWS Solutions As part of the AWS solutions organization, we have a vision to provide business applications, leveraging Amazon's unique experience and expertise, that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers' businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. We blend vision with curiosity and Amazon's real-world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are no-brainers to buy and easy to use.

Amazon’s Middle Mile Science group is looking for a Senior Applied Scientist specializing in design and evaluation of algorithms for predictive modeling and optimization applied to large-scale transportation planning systems. This includes the development of novel machine learning, pattern detection, and artificial intelligence techniques to improve on marketplace optimization solutions. The Middle Mile Science group is charged with developing an evolving suite of optimization tools to facilitate the design of efficient air and ground transport networks, optimize the flow of packages within the network to efficiently align network capacity and shipment demand, set prices, and effectively utilize scarce resources, such as aircraft and trucks. The scale of Amazon’s fulfillment operations challenges us to design, build and operate robust transportation networks that minimize the overall operational cost while meeting all customer deadlines. Real-time execution of our network depends on state-of-the-art artificial intelligence tools to coordinate the actions of thousands of operators and drivers in real time. Amazon often finds existing techniques do not effectively match our unique business needs, which necessitates the innovation and development of new approaches and algorithms to find an adequate solution. As a Sr. Applied Scientist responsible for middle mile transportation, you will be working closely with different teams including business leaders and engineers to design and build scalable products operating across multiple transportation modes. You will create experiments and prototype implementations of new learning algorithms and prediction techniques. You will have exposure to top level leadership to present findings of your research. You will also work closely with other scientists and engineers to implement your models within our production system. You will implement solutions that are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility, and make decisions that affect the way we build and integrate algorithms across our product portfolio. About the team Our Middle Mile Marketplace Science team builds the algorithms for Amazon’s rapidly growing freight marketplace. Amazon contracts with 3P shippers and a network of independent carriers, using a mix of contract structures with varying service and risk profiles. Our work focuses on mechanisms and learning algorithms to optimize pricing and matching in this complex marketplace, and continually improve the experience for carriers and shippers. This is an area with many challenging problems and a huge business impact for Amazon!

At Amazon Search, we discover experience that connects millions of customers to the products they seek across our global marketplace. Our team develops sophisticated search solutions that make Amazon's vast product catalog easily accessible to customers worldwide. We're building next-generation search infrastructure that enables seamless expansion into new markets and product categories. Our mission is to ensure every customer enjoys an exceptional search experience from day one, whether they're shopping in an established market or a newly launched region. We develop intelligent, scalable systems that optimize search quality and effectiveness across Amazon's diverse product ecosystem. Our innovations help customers find exactly what they're looking for, while enabling Amazon to rapidly expand its global presence with consistent, high-quality search capabilities. We are seeking a strong applied scientists to join the Search Relevance India team. This team’s charter is to increase the pace at which Amazon expands and improve the search experience at launch. In practice, we aim to invent universally applicable signals and algorithms for training machine-learned ranking models and improve the machine-learning framework for training and offline evaluation that is used for all new relevance models. Key job responsibilities * Build machine learning models for Product Search. * Develop new ranking features and techniques building upon the latest results from the academic research community. * Propose and validate hypothesis to direct our business and product road map. Work with engineers to make low latency model predictions and scale the throughput of the system. * Focus on identifying and solving customer problems with simple and elegant solutions. * Design, develop, and implement production level code that serves billions of search requests. Own the full development cycle: design, development, impact assessment, A/B testing (including interpretation of results) and production deployment. * Take ownership. Understand the needs of various search teams, distill those into coherent projects, and implement them with an eye on long-term impact. * Be a leader. Use your expertise to set a high bar for the team, mentor team members, set the tone for how to take on and deliver on large impossible-sounding projects. * Be curious. You will work alongside systems engineers, machine learning scientists, and data analysts. Your effectiveness and impact will depend on discussing problems with and learning from them. You will have access to the advanced edge technologies and vast technical tools and resources of Amazon and will need to learn how to use them effectively.

Amazon has launched a new research lab in San Francisco to develop foundational capabilities for useful AI agents. We’re enabling practical AI to make our customers more productive, empowered, and fulfilled. In particular, our work combines large language models (LLMs) with reinforcement learning (RL) to solve reasoning, planning, and world modeling in both virtual and physical environments. Our research builds on that of Amazon’s broader AGI organization, which recently introduced Amazon Nova, a new generation of state-of-the-art foundation models (FMs). Our lab is a small, talent-dense team with the resources and scale of Amazon. Each team in the lab has the autonomy to move fast and the long-term commitment to pursue high-risk, high-payoff research. We’re entering an exciting new era where agents can redefine what AI makes possible. We’d love for you to join our lab and build it from the ground up! Key job responsibilities You will be responsible for maintaining our task management system which supports many internal and external stakeholders and ensures we are able to continue adding orders of magnitude more data and reliability.

Selection Monitoring team is responsible for making the biggest catalog on the planet even bigger. In order to drive expansion of the Amazon catalog, we develop advanced ML/AI technologies to process billions of products and algorithmically find products not already sold on Amazon. We work with structured, semi-structured and Visually Rich Documents using deep learning, NLP and image processing. The role demands a high-performing and flexible candidate who can take responsibility for success of the system and drive solutions from research, prototype, design, coding and deployment. We are looking for Applied Scientists to tackle challenging problems in the areas of Information Extraction, Efficient crawling at internet scale, developing models for website comprehension and agents to take multi-step decisions. You should have depth and breadth of knowledge in text mining, information extraction from Visually Rich Documents, semi structured data (HTML) and advanced machine learning. You should also have programming and design skills to manipulate Semi-Structured and unstructured data and systems that work at internet scale. You will encounter many challenges, including: - Scale (build models to handle billions of pages), - Accuracy (requirements for precision and recall) - Speed (generate predictions for millions of new or changed pages with low latency) - Diversity (models need to work across different languages, market places and data sources) You will help us to - Build a scalable system which can algorithmically extract information information from world wide web. - Intelligently cluster web pages, segment and classify regions, extract relevant information and structure the data available on semi-structured web. - Build systems that will use existing Knowledge Base to perform open information extraction at scale from visually rich documents. Key job responsibilities: - Use AI, NLP and advances in LLMs/SLMs and agentic systems to create scalable solutions for business problems. - Efficiently Crawl web, Automate extraction of relevant information from large amounts of Visually Rich Documents and optimize key processes. - Design, develop, evaluate and deploy, innovative and highly scalable ML models. - Work closely with software engineering teams to drive real-time model implementations. - Establish scalable, efficient, automated processes for large scale model development, model validation and model maintenance. - Lead projects and mentor other scientists, engineers in the use of ML techniques. - Publish innovation in research forums. Basic qualifications: - 3+ years experience building ML models for business application. - PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience. - Experience programming in Python, Java, C++ or related languages. - Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing. Preferred qualifications: - Experience using Unix/Linux. - Experience in professional software development. - Experience in patents or publications at top-tier peer-reviewed conferences or journals. - Master's degree or above in computer science, computer engineering, or related field.

Join us at the Amazon's sustainability initiatives to work on environmental and social advancements to support Amazon's long term worldwide sustainability strategy. At Amazon, we're working to be the most customer-centric company on earth. To get there, we need exceptionally talented, bright, and driven people. The Worldwide Sustainability (WWS) organization capitalizes on Amazon’s scale and speed to build a more resilient and sustainable company. We manage our social and environmental impacts globally, and drive solutions that enable our customers, businesses, and the world to become more sustainable. Sustainability Science and Innovation (SSI) is a multi-disciplinary team within WW Sustainability combining science, analytics, economics, statistics, machine learning, product development, and engineering expertise. We use data across the sustainability imperatives (carbon, water, waste, biodiversity, environmental risk and more) and these skills and capabilities to identify, develop, experiment, and scale the scientific solutions and innovations necessary for Amazon, customers and partners to help them solve their hardest unmet and evolving sustainability needs and goals. The Sustainability Science and Innovation team is looking for a Sr. Applied Scientist to collaborate closely with Economists and Environmental Scientists to build the AI/ML foundation of the future. You will define strategy and implement tooling to identify, ingest, harmonize, store, and maintain strategic models and data from both internal and external sources. These models and datasets must cover a wide range of topics in emerging areas and applications of AI for sustainability. This AI solutions development will support Amazon-wide sustainability initiatives like carbon footprint, climate risk monitoring, and social responsibility through the supply chain. These datasets must cover a wide range of topics such as geographic regions and data formats to unlock foundational AI research in emerging areas and applications. These solutions development will support Amazon-wide sustainability initiatives like carbon footprinting, climate risk monitoring, and social responsibility through the supply chain. If you see yourself as a hands-on leader and innovator at the intersection of AI, data, and sustainability, we'd like to connect with you. You don't necessarily have to be an expert in sustainability and climate domains. Key job responsibilities - Designing, implementing, and maintaining data and AI/ML infrastructure to support a wide variety of large and complex data sets, ensuring high performance, availability, and integrity. - Identifying and solving data needs for Gen AI and foundational model training and benchmarking for tasks across the sustainability domain. - Developing and optimizing robust data pipelines for internal data from sources such as Product Lifecycle Management tools, Product Details (images, text, and structured data), Inventory Management Platforms, and financial systems. - Design and implement web-scale data collection for images, text, structured data across locations and sustainability domains. - Develop comprehensive monitoring, alarming, and data quality controls for all of the above. - Partnering with Scientists and Software Engineers to create our data collection strategy and ML Ops best practices. About the team Diverse Experiences: World Wide Sustainability 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. Inclusive Team Culture: It’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (inclusive diversity) conferences, inspire us to never stop embracing our uniqueness. 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 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.

You will be working with a unique and gifted team developing exciting products for consumers. The team is a multidisciplinary group of engineers and scientists engaged in a fast paced mission to deliver new products. The team faces a challenging task of balancing cost, schedule, and performance requirements. You should be comfortable collaborating in a fast-paced and often uncertain environment, and contributing to innovative solutions, while demonstrating leadership, technical competence, and meticulousness. Your deliverables will include development of thermal solutions, concept design, feature development, product architecture and system validation through to manufacturing release. You will support creative developments through application of analysis and testing of complex electronic assemblies using advanced simulation and experimentation tools and techniques. Key job responsibilities In this role, you will: - Own thermal design for consumer electronics products at the system level, proposing thermal architecture and aligning with functional leads - Perform CFD simulations using tools such as Star-CCM+ or FloEFD to assess thermal feasibility, identify risks, and propose mitigation options - Generate data processing, statistical analysis, and test automation scripts to improve data consistency, insight quality, and team efficiency - Plan and execute thermal validation activities for devices and SoC packages, including test setup definition, data review, and issue tracking - Work closely with cross-functional and cross-geo teams to support product decisions, generate thermal specifications, and align on thermal requirements - Prepare clear summaries and reports on thermal results, risks, and observations for review by cross-functional leads About the team Amazon Lab126 is an inventive research and development company that designs and engineers high-profile consumer electronics. Lab126 began in 2004 as a subsidiary of Amazon.com, Inc., originally creating the best-selling Kindle family of products. Since then, we have produced innovative devices like Fire tablets, Fire TV and Amazon Echo. What will you help us create?

Employer: Amazon.com Services LLC Position: Economist III (multiple positions available) Location: Seattle, Washington Multiple Positions Available: 1. 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; 2. 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; 3. Work in a fast moving environment to solve business problems as a member of either a crossfunctional team embedded within a business unit or a central science and economics organization; 4. Develop techniques that apply econometrics to large data sets, address quantitative problems, and contribute to the design of automated systems around the company; and 5. Utilize deep knowledge in time series econometrics, asset pricing, empirical macroeconomics, or the use of micro and panel data to improve and validate traditional aggregative models. (40 hours / week, 8:00am-5:00pm, Salary Range $159,200.00/year to $215,300.00/year) Amazon.com is an Equal Opportunity – Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation