Careers

Amazon Shipping is hiring Applied Scientists to help improve our ability to plan and execute package movements. As an Applied Scientist in Amazon Shipping, you will work on multiple challenging machine learning problems spread across a wide spectrum of business problems. You will build ML models to help our transportation cost auditing platforms effectively audit off-manifest (discrepancies between planned and actual shipping cost). You will build models to improve the quality of financial and planning data by accurately predicting ship cost at a package level. Your models will help forecast the packages required to be pick from shipper warehouses to reduce First Mile shipping cost. Using signals from within the transportation network (such as network load, and velocity of movements derived from package scan events) and outside (such as weather signals), you will build models that predict delivery delay for every package. These models will help improve buyer experience by triggering early corrective actions, and generating proactive customer notifications. Your role will require you to demonstrate Think Big and Invent and Simplify, by refining and translating Transportation domain-related business problems into one or more Machine Learning problems. You will use techniques from a wide array of machine learning paradigms, such as supervised, unsupervised, semi-supervised and reinforcement learning. Your model choices will include, but not be limited to, linear/logistic models, tree based models, deep learning models, ensemble models, and Q-learning models. You will use techniques such as LIME and SHAP to make your models interpretable for your customers. You will employ a family of reusable modelling solutions to ensure that your ML solution scales across multiple regions (such as North America, Europe, Asia) and package movement types (such as small parcel movements and truck movements). You will partner with Applied Scientists and Research Scientists from other teams in US and India working on related business domains. Your models are expected to be of production quality, and will be directly used in production services. You will work as part of a diverse data science and engineering team comprising of other Applied Scientists, Software Development Engineers and Business Intelligence Engineers. You will participate in the Amazon ML community by authoring scientific papers and submitting them to Machine Learning conferences. You will mentor Applied Scientists and Software Development Engineers having a strong interest in ML. You will also be called upon to provide ML consultation outside your team for other problem statements. If you are excited by this charter, come join us!

Amazon.com strives to be Earth's most customer-centric company where customers can shop in our stores to find and discover anything they want to buy. We hire the world's brightest minds, offering them a fast paced, technologically sophisticated and friendly work environment. Economists at Amazon 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. Amazon Economists 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. You will work in a fast moving environment to solve business problems as a member of either a cross-functional team embedded within a business unit or a central science and economics organization. You will be expected to develop techniques that apply econometrics to large data sets, address quantitative problems, and contribute to the design of automated systems around the company. About the team The International Seller Services (ISS) Economics team is a dynamic group at the forefront of shaping Amazon's global seller ecosystem. As part of ISS, we drive innovation and growth through sophisticated economic analysis and data-driven insights. Our mission is critical: we're transforming how Amazon empowers millions of international sellers to succeed in the digital marketplace. Our team stands at the intersection of innovative technology and practical business solutions. We're leading Amazon's transformation in seller services through work with Large Language Models (LLMs) and generative AI, while tackling fundamental questions about seller growth, marketplace dynamics, and operational efficiency. What sets us apart is our unique blend of rigorous economic methodology and practical business impact. We're not just analyzing data – we're building the frameworks and measurement systems that will define the future of Amazon's seller services. Whether we're optimizing the seller journey, evaluating new technologies, or designing innovative service models, our team transforms complex economic challenges into actionable insights that drive real-world results. Join us in shaping how millions of businesses worldwide succeed on Amazon's marketplace, while working on problems that combine economic theory, advanced analytics, and innovative technology.

Amazon is investing heavily in building a world class advertising business and we are responsible for defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities. This position will be part of the Conversational Ad Experiences team within the Amazon Advertising organization. Our cross-functional team focuses on designing, developing and launching innovative ad experiences delivered to shoppers in conversational contexts. We utilize leading-edge engineering and science technologies in generative AI to help shoppers discover new products and brands through intuitive, conversational, multi-turn interfaces. We also empower advertisers to reach shoppers, using their own voice to explain and demonstrate how their products meet shoppers' needs. We collaborate with various teams across multiple Amazon organizations to push the boundary of what's possible in these fields. We are seeking a science leader for our team within the Sponsored Products & Brands organization. You'll be working with talented scientists, engineers, and product managers to innovate on behalf of our customers. An ideal candidate is able to navigate through ambiguous requirements, working with various partner teams, and has experience in generative AI, large language models (LLMs), information retrieval, and ads recommendation systems. Using a combination of generative AI and online experimentation, our scientists develop insights and optimizations that enable the monetization of Amazon properties while enhancing the experience of hundreds of millions of Amazon shoppers worldwide. If you're fired up about being part of a dynamic, driven team, then this is your moment to join us on this exciting journey! Key job responsibilities - Serve as a tech lead for defining the science roadmap for multiple projects in the conversational ad experiences space powered by LLMs. - Build POCs, optimize and deploy models into production, run experiments, perform deep dives on experiment data to gather actionable learnings and communicate them to senior leadership. - Work closely with software engineers on detailed requirements, technical designs and implementation of end-to-end solutions in production. - Work closely with product managers to contribute to our mission, and proactively identify opportunities where generative AI can help improve customer experience. - Research new machine learning approaches to drive continued scientific innovation - Be a member of the Amazon-wide machine learning community, participating in internal and external meetups, hackathons and conferences. - Help attract and recruit technical talent, mentor scientists and engineers in the team.

Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply cutting edge Generative AI algorithms to solve real world problems with significant impact? The AWS Industries Team at AWS helps AWS customers implement Generative AI solutions and realize transformational business opportunities for AWS customers in the most strategic industry verticals. This is a team of data scientists, engineers, and architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI. The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, select and train and fine tune the right models, define paths to navigate technical or business challenges, develop proof-of-concepts, and build applications to launch these solutions at scale. The AWS Industries team provides guidance and implements best practices for applying generative AI responsibly and cost efficiently. You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. In this Data Scientist role you will be capable of using GenAI and other techniques to design, evangelize, and implement and scale cutting-edge solutions for never-before-solved problems. Key job responsibilities - Collaborate with AI/ML scientists, engineers, and architects to research, design, develop, and evaluate cutting-edge generative AI algorithms and build ML systems to address real-world challenges - Interact with customers directly to understand the business problem, help and aid them in implementation of generative AI solutions, deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and paths to production - Create and deliver best practice recommendations, tutorials, blog posts, publications, sample code, and presentations adapted to technical, business, and executive stakeholder - Provide customer and market feedback to Product and Engineering teams to help define product direction About the team Diverse Experiences Amazon 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. 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. 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 (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship and 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.

We’re working on the future. If you are seeking an iterative fast-paced environment where you can drive innovation, apply state-of-the-art technologies to solve large-scale real world delivery challenges, and provide visible benefit to end-users, this is your opportunity. Come work on the Amazon Prime Air Team! We are seeking a highly skilled weather scientist to help invent and develop new models and strategies to support Prime Air’s drone delivery program. In this role, you will develop, build, and implement novel weather solutions using your expertise in atmospheric science, data science, and software development. You will be supported by a team of world class software engineers, systems engineers, and other scientists. Your work will drive cross-functional decision-making through your excellent oral and written communication skills, define system architecture and requirements, enable the scaling of Prime Air’s operation, and produce innovative technological breakthroughs that unlock opportunities to meet our customers' evolving demands. About the team Prime air has ambitious goals to offer its service to an increasing number of customers. Enabling a lot of concurrent flights over many different locations is central to reaching more customers. To this end, the weather team is building algorithms, tools and services for the safe and efficient operation of prime air's autonomous drone fleet.

Are you passionate about leveraging your applied science skills to deliver actionable insights that impact daily business decisions? Do you thrive using causal inference, experimentation, and Machine Learning/AI to answer challenging product and customer behavior questions? Do you want to be a technical leader and build flexible and global solutions for complex financial, risk, and causal problems? If so, here is a great opportunity to consider! Amazon B2B Payments & Lending is seeking a Senior Applied Scientist who will combine their technical expertise with business intuition to generate critical insights that will set the strategic direction of the business. You will be a thought leader on the team, help set the team's strategic focus and roadmaps, and design and build systems/solutions that support financial products, working closely with business/product partners and engineers. You will utilize causal inference/experimentation/ML/AI methodologies, data and coding skills, problem solving and analytical skills, and excellent communication to deliver customer value. As a Senior Applied Scientist on our team, you'll play a pivotal role in uncovering actionable insights that shape the strategic direction of our products and services. You'll work closely with business stakeholders, data scientists, and engineers to tackle complex problems at the intersection of finance, risk modeling, and customer behavior. A day in the life - Collaborate with product, data, and engineering teams to identify key business and customer questions that can be answered through advanced analytics and machine learning - Design and build flexible, scalable solutions that leverage causal inference, experimentation, and applied ML/AI to provide critical insights that drive strategic decisions - Present analyses and recommendations to stakeholders, while also mentoring more junior data scientists and innovating on the team's capabilities About the team The Amazon B2B Payments & Lending team is a fast-paced, highly collaborative group focused on enabling seamless financial experiences for our business customers. We're building innovative solutions that leverage the power of data, AI, and automation to deliver frictionless payment processing, credit decisioning, and financial management tools. Our team culture is one of curiosity, creativity, and a relentless drive to delight our customers. We value bold thinking, data-driven decision making, and a willingness to experiment and learn. If you're passionate about using your technical expertise to drive meaningful business impact, this is an exciting opportunity to make a difference.

Amazon Q Business is an AI assistant powered by generative technology. It provides capabilities such as answering queries, summarizing information, generating content, and executing tasks based on enterprise data. We are seeking a Language Data Scientist II to join our data team. Our mission is to engineer high-quality datasets that are essential to the success of Amazon Q Business. From human evaluations and Responsible AI safeguards to Retrieval-Augmented Generation and beyond, our work ensures that Generative AI is enterprise-ready, safe, and effective for users. As part of our diverse team—including language engineers, linguists, data scientists, data engineers, and program managers—you will collaborate closely with science, engineering, and product teams. We are driven by customer obsession and a commitment to excellence. In this role, you will leverage data-centric AI principles to assess the impact of data on model performance and the broader machine learning pipeline. You will apply Generative AI techniques to evaluate how well our data represents human language and conduct experiments to measure downstream interactions. Key job responsibilities * oversee end-to-end evaluation data pipeline and propose evaluation metrics and methods * incorporate your knowledge of linguistic fundamentals, NLU, NLP to the data pipeline * process and analyze diverse media formats including audio recordings, video, images and text * perform statistical analysis of the data * write intuitive data generation & annotation guidelines * write advanced and nuanced prompts to optimize LLM outputs * write python scripts for data wrangling * automate repetitive workflows and improve existing processes * perform background research and vet available public datasets on topics such as long text retrieval, text generation, summarization, question-answering, and reasoning * leverage and integrate AWS services to optimize data collection workflows * collaborate with scientists, engineers, and product managers in defining data quality metrics and guidelines. * lead dive deep sessions with data annotators

Amazon Q Business is an AI assistant powered by generative technology. It provides capabilities such as answering queries, summarizing information, generating content, and executing tasks based on enterprise data. We are seeking a Language Data Scientist II to join our data team. Our mission is to engineer high-quality datasets that are essential to the success of Amazon Q Business. From human evaluations and Responsible AI safeguards to Retrieval-Augmented Generation and beyond, our work ensures that Generative AI is enterprise-ready, safe, and effective for users. As part of our diverse team—including language engineers, linguists, data scientists, data engineers, and program managers—you will collaborate closely with science, engineering, and product teams. We are driven by customer obsession and a commitment to excellence. In this role, you will leverage data-centric AI principles to assess the impact of data on model performance and the broader machine learning pipeline. You will apply Generative AI techniques to evaluate how well our data represents human language and conduct experiments to measure downstream interactions. Key job responsibilities * oversee end-to-end evaluation data pipeline and propose evaluation metrics and methods * incorporate your knowledge of linguistic fundamentals, NLU, NLP to the data pipeline * process and analyze diverse media formats including audio recordings, video, images and text * perform statistical analysis of the data * write intuitive data generation & annotation guidelines * write advanced and nuanced prompts to optimize LLM outputs * write python scripts for data wrangling * automate repetitive workflows and improve existing processes * perform background research and vet available public datasets on topics such as long text retrieval, text generation, summarization, question-answering, and reasoning * leverage and integrate AWS services to optimize data collection workflows * collaborate with scientists, engineers, and product managers in defining data quality metrics and guidelines. * lead dive deep sessions with data annotators 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 position is open to all candidates in NYC and Arlington, VA Amazon Ads Response Prediction team is your choice, if you want to join a highly motivated, collaborative, and fun-loving team with a strong entrepreneurial spirit and bias for action. We are seeking an experienced and motivated Machine Learning Applied Scientist who loves to innovate at the intersection of customer experience, deep learning, and high-scale machine-learning systems. Amazon Advertising operates at the intersection of eCommerce and advertising, and is investing heavily in building a world-class advertising business. We are defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long-term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products to improve both shopper and advertiser experience. With a broad mandate to experiment and innovate, we grow at an unprecedented rate with a seemingly endless range of new opportunities. We are looking for a talented Machine Learning Applied Scientist for our Amazon Ads Response Prediction team to grow the business. We are providing advanced real-time machine learning services to connect shoppers with right ads on all platforms and surfaces worldwide. Through the deep understanding of both shoppers and products, we help shoppers discover new products they love, be the most efficient way for advertisers to meet their customers, and helps Amazon continuously innovate on behalf of all customers. Key job responsibilities As a Machine Learning Applied Scientist, you will: * Conduct deep data analysis to derive insights to the business, and identify gaps and new opportunities * Develop scalable and effective machine-learning models and optimization strategies to solve business problems * Run regular A/B experiments, gather data, and perform statistical analysis * Work closely with software engineers to deliver end-to-end solutions into production * Improve the scalability, efficiency and automation of large-scale data analytics, model training, deployment and serving * Conduct research on new machine-learning modeling to optimize all aspects of Sponsored Products business About the team We are pioneers in applying advanced machine learning and generative AI algorithms in Sponsored Products business. We empower every customer with a customized discovery experiences from back-end optimization (such as customized response prediction models) to front-end CX innovation (such as widgets), to help shoppers feel understood and shop efficiently on and off Amazon.

The Data and Artificial Intelligence (AI) team is a new function within Customer Engagement Technology. We own the end-to-end process of defining, building, implementing, and monitoring a comprehensive data strategy. We also develop and apply Generative Artificial Intelligence (GenAI), Computer Vision, Machine Learning (ML), Ontology, and Natural Language Processing (NLP) to customer service associate experiences and foundational technologies. As an Applied Scientist, you'll own the definition and implementation of customer-focused, AI-driven innovation in Amazon Customer Service globally, leveraging GenAI, ML, and/or NLP to transform complex business requirements and customer needs into innovative technology solutions. Your expertise will be key in shaping data-driven strategies and addressing complex data challenges. With expertise in AI, text analysis, text embedding, language modeling, and generation, you'll design and develop scalable AI-powered technology solutions, prioritize initiatives, drive data-driven insights, and deliver business impact. This position will advance applied science best practices, leverage data and AI to drive customer experience (CX) improvements, and set new global standards for customer experience. This role requires working with a cross-functional team including scientists, engineers, and product management to develop scalable and maintainable AI solutions for both structured and unstructured data. The ideal candidate has strong technological skills in ML, NLP, and GenAI, excellent written documentation skills, and experience with big data technologies. You should care deeply about customers and strive to deliver customer value through applied science. You should work well in a fast-paced setting, using your skills to create effective solutions. With a combination of deep business know-how and hands-on skills, you will tackle complex challenges and drive continuous improvement. Key job responsibilities - Provide technical leadership, driving innovation and strategic direction for large-scale AI initiatives. - Architect and develop ground-breaking ML modeling and engineering techniques, pushing boundaries of AI research and applications. - Collaborate with senior leaders to identify high-impact opportunities, aligning AI research with business objectives. - Develop and execute strategic plans, leveraging Amazon's vast data sources and computing resources. - Foster a culture of technical excellence, mentoring senior scientists and engineers. - Communicate complex technical concepts to executive stakeholders, influencing business decisions. - Lead science hiring, attracting top talent and building high-performing teams. Collaborate with product management and engineering teams to integrate and optimize models in production systems. Come join a team of bright, passionate, and customer-obsessed individuals who are having fun and making history. We would love to talk to you! A day in the life A typical day for a Principal Applied Scientist in the Customer Service Data and AI team involves a combination of gaining business know-how and hands-on problem-solving in NLP and GenAI. You'll tackle complex data initiatives, ensuring alignment with customer needs and business objectives, and translating business requirements into practical AI-driven solutions. Collaborating with cross-functional teams, you'll design and enhance AI models, focusing on efficiency, precision, and scalability. You'll mentor team members, fostering skill growth and encouraging innovative solutions. Your day involves monitoring data quality, evaluating model performance, and generating actionable insights from vast amounts of information. By the end of the day, you will have resolved complex technical issues, advanced important AI projects, and conceived new ideas to improve how Amazon utilizes data to transform the customer experience. 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 The Data and Artificial Intelligence (AI) team is a new function within Customer Engagement Technology. We own the end-to-end process of defining, building, implementing, and monitoring a comprehensive data strategy. We also develop and apply Generative AI (GenAI), Computer Vision, Machine Learning, Ontologies, and Natural Language Processing (NLP) to customer service associate experiences and foundational technologies.