Careers

Come be a part of a rapidly expanding $35 billion-dollar global business. At Amazon Business, a fast-growing startup passionate about building solutions, we set out every day to innovate and disrupt the status quo. We stand at the intersection of tech & retail in the B2B space developing innovative purchasing and procurement solutions to help businesses and organizations thrive. At Amazon Business, we strive to be the most recognized and preferred strategic partner for smart business buying. Bring your insight, imagination and a healthy disregard for the impossible. Join us in building and celebrating the value of Amazon Business to buyers and sellers of all sizes and industries. Unlock your career potential. The Analytics Data Product & Tech (ADAPTech) team is a strategic partner to the WW Sales organization, playing a key role in driving sales productivity through three primary workstreams. First, the Analytics team provides data-driven insights and reporting tools to measure business, customer, and employee performance. Second, the Products and Science team develops transformative tools that help Account Executives (AEs) to prioritize accounts, recommend product features, and engage more effectively with customers. Finally, the Data Management and Governance teams ensure AEs have access to accurate and enriched customer information across our tools. We're seeking an Data Scientist to join our team to improve the productivity and efficiency of AEs. You'll be part of expanding GenAI capabilities and scaling its impact across global markets. A successful Data Scientist at Amazon demonstrates bias for action and operates in a startup environment, with leadership skills, and proven ability to build and manage medium-scale modeling projects, identify data requirements, build methodology and tools that are statistically grounded. We need great leaders to think big and design new solutions to solve complex problems using machine learning (ML) and Generative AI techniques to improve our customers’ experience when using AB. You have hands-on experience making the right decisions about technology, models and methodology choices. Key job responsibilities As a Data Scientist, you will primarily leverage machine learning techniques and generative AI to outreach customers based on their life cycle stage, behavioral patterns, and purchase history. You may also perform text mining and insight analysis of real-time customer conversations and make the model learn and recommend the solutions. Your work will directly impact the trust customers place in Amazon Business. You will partner with product management and technical leadership to identify opportunities to innovate customer journey experiences. You will identify new areas of investment and work to align product roadmaps to deliver on these opportunities. As a science leader, you will not only develop unique scientific solutions, but also play a crucial role in shaping strategies. Additional responsibilities include: - Ability to understand a business problem and the available data and identify what statistical or ML techniques can be applied to answer a business question - Design and lead large projects and experiments from beginning to end, and drive solutions to complex or ambiguous problems - Use broad expertise to recommend the right strategies, methodologies, and solve challenges using statistical modeling, machine learning, optimization, and/or other approaches for quantifiable impact on the business - Build models that measure incremental value, predict growth, define and conduct experiments to optimize engagement of AB customers, and communicate insights and recommendations to product, sales, and finance partners. A day in the life In this role, you will be a technical expert with significant scope and impact. You will work with Technical Product Managers, Data Engineers, other Scientists, and Salesforce developers, to build new and enhance existing ML models to optimize customer experience. You will prototype and test new ideas, iterate quickly, and deploy models to production. Also, you will conduct in-depth data analysis and feature engineering to build robust ML models.

The Customer Engagement Technology (CET) team leads AI/LLM- (Large Language Model) driven customer experience transformation using task-oriented dialog systems. We develop multi-modal, multi-turn, goal-oriented dialog systems that can handle customer issues at Amazon scale across multiple languages. These systems are designed to adapt to changing company policies and invoke correct APIs to automate solutions to customer problems. Additionally, we enhance associate productivity through response/action recommendation, summarization to capture conversation context succinctly, retrieving precise information from documents to provide useful information to the agent, and machine translation to facilitate smoother conversations when the customer and agent speak different languages. Key focus areas include: - Task-Oriented Dialog Systems: Building reliable, scalable, and adaptive LLM-based agents for understanding intents, determining eligibilities, making API calls, confirming outcomes, and exploring alternatives across hundreds of customer service intents, while adapting to changing policies. - Lifelong Learning: Researching continuous learning approaches for injecting new domain knowledge while retaining the model's foundational abilities and preventing catastrophic forgetting. - Agentic Systems: Developing a modular agentic framework to handle multi-domain conversations through appropriate system abstractions. - Complex Multi-turn Instruction Following: Identifying approaches to guarantee compliance with instructions that specify standard operating procedures for handling multi-turn complex scenarios. - Inference-Time Adaptability: Researching inference-time scaling methods and improving in-context learning abilities of custom models to enable real-time adaptability to new features, actions, or bug fixes without solely relying on retraining. - Context Adherence: Exploring methods to ground responses in specific customer attributes, account information, and behavioral data to prevent hallucinations and ensure high-fidelity responses. - Policy Grounding: Investigating techniques to align bot behavior with evolving company policies by grounding on complex, unstructured policy documents, ensuring consistent and compliant actions. - End-to-End Dialog Policy Optimization: Researching alignment approaches to optimize successful dialog completions. - Scalable Evaluations: Developing automated approaches to evaluate the quality of experience, and correctness of agentic resolutions. Key job responsibilities - Research and development of LLM-based chatbots and conversational AI systems for customer service applications. - Design and implement state-of-the-art NLP and ML models for tasks such as language understanding, dialogue management, and response generation. - Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to integrate LLM-based solutions into Amazon's customer service platforms. - Develop and implement strategies for data collection, annotation, and model training to ensure high-quality and robust performance of chatbot systems. - Conduct experiments and evaluations to measure the performance of developed models and systems to identify areas for improvement. - Stay up-to-date with the latest advancements in NLP, LLMs, and conversational AI, and explore opportunities to incorporate new techniques and technologies into Amazon's customer service solutions. - Collaborate with internal and external research communities, participate in conferences and publications, and contribute to the advancement of the field. A day in the life We thrive on solving challenging problems to innovate for our customers. By pushing the boundaries of technology, we create unparalleled experiences that enable us to adapt rapidly in a dynamic environment. Our decisions are guided by data, and we collaborate with engineering, science, and product teams to foster an innovative learning environment. 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! Benefits Summary: 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: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan About the team Join our team of scientists and engineers who develop and deploy LLM-based Conversational AI systems to enhance Amazon's customer service experience and effectiveness. We work on innovative solutions that help customers solve their issues and get their questions answered efficiently, as well as associate-facing products that support our customer service associate workforce.

Amazon is looking for a passionate, talented, and inventive Applied Scientist with a strong machine learning background to help build industry-leading technology in generative AI and foundational models. As part of our AI team in Amazon AWS, you will work alongside internationally recognized experts to develop novel algorithms and modeling techniques to advance the state-of-the-art in generative AI. Your work will directly impact millions of our customers in the form of products and services that make use of speech, vision and language technology. You will gain hands on experience with Amazon’s heterogeneous speech, text, image and structured data sources, and large-scale computing resources to accelerate advances in machine learning and foundation models. More specifically, you will have the opportunity to impact millions of our customers by researching and building innovative solutions using Agentic AI. Agentic AI drives innovation at the forefront of artificial intelligence, enabling customers to transform their businesses through cutting-edge generative AI solutions. We build and deliver the foundational AI services that power the future of cloud computing, helping organizations harness the potential of AI to solve their most complex challenges. Join our dynamic team of AI/ML practitioners, applied scientists, software engineers, and solution architects who work backwards from customer needs to create groundbreaking technologies. If you're passionate about shaping the future of AI while making a meaningful impact for customers worldwide, we want to hear from you. A day in the life A day in the life Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why 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 Here at AWS, 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) 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 we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

Are you seeking an environment where you can drive innovation? Do you want to apply inference, advanced statistical modeling and techniques to solve world's most challenging problems in? Do you want to play a crucial role in the future of Amazon's Retail business? Do you want to be a part of a journey that develops a new technology from scratch for answering critical business question in Amazon Retail? Every time an Amazon customer makes a purchase, a number of systems are involved: these systems help optimize acquisition, enable a number of purchase options, ensure great , store products so they are available for fast delivery, and minimize package frustration. The Technology (SCOT) Group develops and manages these systems. We are central to Amazon customers' ability to find what they want and get it when they want it. The Consumer Instock Value (CIV) team within Amazon's Supply Chain Optimization Technology (SCOT) Group develops and manages systems that estimate the long-term impact of inventory availability and delivery speed changes at the product level. Our estimates are crucial inputs for multiple production systems across Amazon's supply chain planning, helping teams make critical decisions about inventory management, selection, and placement. Key responsibilities of a Data Scientist in CIV Team include: - Developing new statistical, causal, and machine learning techniques and develop solution prototypes to drive innovation - Working with technical and non-technical customers to design model improvements and communicate results - Collaborating with our dedicated software team to create production implementations for large-scale data analysis - Developing an understanding of key business metrics / KPIs and providing clear, compelling analysis that shapes the direction of our business - Presenting research results to our internal research community - Leading training and informational sessions on our science and capabilities - Your contributions will be seen and recognized broadly within Amazon, contributing to the Amazon research corpus and patent portfolio.

As a Senior Applied Scientist for Last Hundred Yards Automation, you will be at the forefront of developing cutting-edge AI and ML solutions that power our autonomous delivery robots. This role combines deep expertise in machine learning, computer vision, and robotics to solve complex challenges in real-world autonomous navigation, obstacle detection, and dynamic path planning. You will work closely with robotics engineers, software developers, and product teams to research, design, and implement sophisticated algorithms that enable safe and efficient last-yard delivery operations. This position requires a unique blend of theoretical knowledge and practical implementation skills, with a focus on transforming research concepts into production-ready solutions that can operate reliably in diverse real-world environments. Key job responsibilities The Senior Applied Scientist will lead the development and implementation of advanced AI/ML models for autonomous navigation, focusing on critical areas such as real-time object detection, semantic scene understanding, and predictive movement planning. You will be responsible for designing and conducting experiments, analyzing complex datasets, and developing novel algorithms to improve robot performance and reliability. The role involves collaborating with cross-functional teams to integrate ML solutions into the robotics platform, optimizing model performance for edge computing, and establishing metrics for continuous improvement. You will also mentor junior scientists, contribute to research publications, and stay current with latest developments in the field. Key activities include developing robust ML pipelines, implementing state-of-the-art deep learning architectures, and creating innovative solutions for challenging problems such as adverse weather navigation, multi-robot coordination, and human-robot interaction. Success in this role requires balancing research excellence with practical implementation, while maintaining a strong focus on safety and reliability in autonomous systems. About the team LMDA (Last Mile Delivery Automation) is a cutting-edge automation system designed to revolutionize the final phase of package delivery, focusing specifically on the last hundred yards from delivery vehicle to customer doorstep. The system integrates autonomous robots equipped with advanced AI/ML algorithms, real-time navigation capabilities, and smart obstacle avoidance technology to efficiently transport packages to their final destination. These robots are designed to navigate various terrains, including sidewalks, building entrances, and residential complexes, while adhering to local safety regulations and maintaining secure delivery protocols. LMDA incorporates cloud-based fleet management, real-time tracking, and dynamic route optimization to ensure seamless coordination between delivery vehicles and robots. The system features a user-friendly interface for both delivery personnel and customers, providing live tracking, delivery notifications, and interactive robot communication. As labor costs rise and delivery volumes increase, LMDA represents a scalable, cost-effective solution that addresses the growing challenges of last-mile delivery while significantly improving operational efficiency and customer satisfaction.

Are you fascinated by the power of Large Language Models (LLM) and applying Generative AI to solve complex challenges within one of Amazon's most significant businesses? Amazon Selection and Catalog Systems (ASCS) builds the systems that host and run the world’s largest e-Commerce products catalog - it powers the online buying experience for customers worldwide so they can find, discover and buy anything they want. Amazon’s customers rely on the completeness, consistency and correctness of Amazon's product data to make well-informed purchase decisions. We develop LLM applications that make Catalog the best-in-class source of product information for all products worldwide. This problem is challenging due to sheer scale (billions of products in the catalog), diversity (products ranging from electronics to groceries) and multitude of input sources (millions of sellers contributing product data with different quality). You will lead the Amazon Catalog Science team and own devising the strategy and execution plans that power initiatives ranging from: developing tuning artifacts on top of foundational LLMs, training ML models, performing fact extraction, automatic detection of missing product information, active learning mechanisms for scaling human tasks, building applications for distilling product information, building mechanisms to analyze product composition, ingest images, text, and unstructured data to drive deep understanding of products at scale. The right candidate will be a leader who lives and breathes innovation. They'll foster a culture where creative thinking is celebrated and bold ideas can take root. Most importantly, they'll be able to transform this innovative spirit into tangible results, skillfully guiding the team from inspiring vision to real-world impact through careful execution of our strategic roadmap.

Are you a AI-focused data scientist that wants to think fast, dive deep, and build? We are seeking a data scientists to join our the Amazon Nova Solutions team to work with Foundation Model (FM) teams alongside internal and external Generative AI customers to customize foundation models and build the applications of the future. In this role, you will be the voice of the builder, with ownership for working alongside Amazon businesses to develop GenAI solutions that deliver their immediate business value and realize the future of customer experience. You will help your customers understand best practices and develop new best-practice patterns as you encounter new problem spaces. With your day to day focus on the builder, you will be expected to provide insights to product, science, and engineering on how customers build with our FM's and how we can improve. You will be empowered to invent on behalf of our customers and advocate for their needs throughout design, build, and launch of next gen FM's. You must have deep technical experience working with technologies related to large language models including LLM architectures, model evaluation, and fine-tuning techniques. You should be proficient with design, deployment, and evaluation of foundation models - including evaluation dataset design, metric design, implementation, failure analysis. Ideal candidate has hands on experience with both AI Frameworks (e.g. Strands, LangGraph, CrewAI, DSPy) and model customization tools including PyTorch, TensorBoard, MLFlow/W&B, Bedrock, and SageMaker This position has a high level of visibility, so you will need to be able to communicate clearly and compellingly at all levels of the company. Additionally, you will be responsible for measuring business impact by diving deep into metrics and customer inputs. You should have a positive attitude and strong work ethic; you will work fast and smart, and adapt and iterate quickly. Key job responsibilities - Customer Advisor- Implement, and deploy state of the art machine learning solutions under Gen AI. You will build prototypes, PoCs, and explore new solutions. You will interact closely with our customers. - Thought Leadership – Evangelize AWS GenAI services and share best practices through forums such as AWS blogs, white-papers, reference architectures and public-speaking events such as AWS Summit, AWS re:Invent, etc. - Ensure success in designing, building and migrating applications, software, and services with Amazon Nova FM's, AWS Bedrock, and other AWS GenAI capabilities. - Interact with customers directly to understand their business problems and help them implement durable GenAI systems. - Educate customers on the value proposition of amazon Nova FM ecosystem and showcase the art of possible. - Drive evaluation strategy, metric design, and evaluation data design for real-world use cases - Drive deep architectural discussions and design exercises to create solutions built with Amazon Nova FM's - Author and contribute to AWS customer-facing publications such as whitepapers, workshops, demos and proof of concepts. - Build deep relationships with customer engineering, product, and science leaders. About the team Amazon Nova Applied AI Solutions Team serves as a bridge between Foundation Model science, engineering, and product teams and the internal Amazon teams using these models to deliver business value to Amazon's customers. We help customers build GenerativeAI applications and apply the learning from these engagemetns to help make the Foundation Models better every day.

Amazon is seeking an exceptional Applied Scientist to join AGI Info Content team. In this role, you will be at the forefront of developing and enhancing the intelligence of AmazonBot crawler and content processing. The team is a key enabler of Amazon's AGI initiatives such as data pipelines for Olympus model training and collecting data for AGI Info grounding services. Our systems operate on web scale. This requires great combination of innovation to utilize all SOTA ML techniques in combination with model optimization to operate on 100k+ requests/decision per second. Your work will directly impact the quality and efficiency of our data acquisition efforts, ultimately benefiting millions of customers worldwide. Key job responsibilities - Design, develop, and implement advanced algorithms and machine learning models to improve the intelligence and effectiveness of our web crawler and content processing pipelines. - Collaborate with cross-functional teams to identify and prioritize crawling targets, ensuring alignment with business objectives - Analyze and optimize crawling strategies to maximize coverage, freshness, and quality of acquired data while minimizing operational costs as well as dive deep into data to select the highest quality data for LLM model training and grounding. - Conduct in-depth research to stay at the forefront of web acquisition and processing. - Develop and maintain scalable, fault-tolerant systems to handle the vast scale of Amazon's web crawling operations - Monitor and analyze performance metrics, identifying opportunities for improvement and implementing data-driven optimizations - Mentor and guide junior team members, fostering a culture of innovation and continuous learning

Join our Generative AI focus team to revolutionize Software Development at Amazon Are you ready to be part of a team that's redefining the future of software engineering? Our team is Amazon's ambitious initiative to pioneer AI development practices that will fundamentally transform how we build software at scale. 🎯 Our Mission We're creating the next generation of development tools and practices that will deliver unprecedented efficiency gains through AI-powered automation, intelligent code generation, and advanced developer experiences. 💫 What Makes Us Different * Ground-floor opportunity to shape the future of software development * Direct impact on Amazon's global engineering productivity * Working with the latest AI technologies and large language models * Culture of experimentation and innovative thinking 🔍 What We're Looking For We are looking for world class researchers with experience in one or more of the following areas - autonomous agents, conversational AI, Search and Recommendation, RAG, large multimodal models (especially vision-language models), reinforcement learning (RL) and sequential decision making. 💡 What You'll Do * Design and implement AI-powered development tools and frameworks * Create intelligent automation systems for code generation and testing * Develop new methodologies for AI-assisted software development * Collaborate with teams across Amazon to drive adoption of new tools and practices 🌱 Impact Your work will directly influence how Amazon's vast engineering organization builds software, enabling faster, more reliable software delivery. Join us in writing the next chapter of software engineering history. The future of development is AI, and it starts here. and yes, what you just read was written in 15 seconds using AI... #AmazonTech #AIInnovation #SoftwareEngineering #FutureOfTech

Do you want to leverage your expertise in translating innovative science into impactful products to improve the lives and work of over a million people worldwide? If so, People eXperience Technology Central Science (PXTCS) would love to discuss how you can make that a reality. PXTCS is an interdisciplinary team that uses economics, behavioral science, statistics, and machine learning to identify products, mechanisms, and process improvements that enhance Amazonians' well-being and their ability to deliver value for Amazon's customers. We collaborate with HR teams across Amazon to make Amazon PXT the most scientific human resources organization in the world. In this role, you will spearhead science design and technical implementation innovations across our predictive modeling and forecasting work-streams. You'll enhance existing models and create new ones, empowering leaders throughout Amazon to make data-driven business decisions. You'll collaborate with scientists and engineers to deliver solutions while working closely with business stakeholders to address their specific needs. Your work will span various business domains (corporate, operations, safety) and analysis levels (individual, group, organizational), utilizing a range of modeling approaches (linear, tree-based, deep neural networks, and LLM-based). You'll develop end-to-end ML solutions from problem formulation to deployment, maintaining high scientific standards and technical excellence throughout the process. As a Sr. Applied Scientist, you'll also contribute to the team's science strategy, keeping pace with emerging AI/ML trends. You'll mentor junior scientists, fostering their growth by identifying high-impact opportunities. Your guidance will span different analysis levels and modeling approaches, enabling stakeholders to make informed, strategic decisions. If you excel at building advanced scientific solutions and are passionate about developing technologies that drive organizational change in the AI era, join us as we work hard, have fun, and make history.