Careers

The Selling Partner Experience (SPX) organization strives to make Amazon the best place for Selling Partners to do business. The SPX AI Lab team is building the AI capabilities powering the Selling Assistant, Amazon's conversational assistant experience for Selling Partners. The Selling Assistant is a trusted partner and a seasoned advisor that’s always available to enable our partners to thrive in Amazon’s stores. It takes away the cognitive load of selling on Amazon by providing a single interface to handle a diverse set of selling needs. The assistant always stays by the seller's side, talks to them in their language, enables them to capitalize on opportunities, and helps them accomplish their business goals with ease. It is powered by the latest advances in Generative AI, going beyond a typical chatbot to provide an intuitive, intelligent, agentic and personalized experience to sellers running real businesses, large and small. Do you want to join an innovative group of scientists, engineers, and product managers who use advanced analytical, statistical, and machine learning techniques to help Amazon create a delightful Selling Partner experience? Are you excited about uncovering insights from massive-scale data, measuring the impact of AI-driven features, and shaping product strategy through rigorous analysis? Do you want to be part of one of Amazon’s most strategic initiatives to understand and improve seller experience? If yes, the SPX AI Lab may be the perfect fit for you. Key job responsibilities -- Respond to Seller feedback and implement fix in Gen AI solution to enhance Seller experience -- Drive deep-dive analytical studies to understand seller pain points, evaluate feature performance, and identify opportunities to improve the Selling Partner experience. -- Design and execute robust causal inference and measurement frameworks, including A/B testing, quasi-experiments, and observational causal methods (e.g., diff-in-diff, synthetic control, propensity score methods). -- Develop scalable analytical pipelines for impact measurement, KPI development, metric integrity validation, and long-term business monitoring. -- Apply NLP and statistical modeling techniques—including topic modeling, clustering, semantic similarity, and classification—to uncover insights from unstructured seller interactions, feedback, and content. -- Partner with scientists, engineers, economists, and product managers to translate ambiguous problems into structured analytical approaches and influence product roadmaps with data-driven recommendations. -- Build and maintain automated analytics tools and dashboards to democratize insights for product, science, and engineering teams. -- Collaborate scientists to evaluate model-driven features, quantify impact, and ensure mechanisms are grounded in rigorous measurement. -- Research and experiment with new analytical and measurement methodologies, ensuring Amazon leverages the latest best practices in causal inference, NLP, and GenAI. About the team SPX AI Lab is a growing team of scientists driving the research and development of the next generation of GenAI experiences that empower Amazon's Selling Partners to succeed. We draw from many science domains, from Natural Language Processing to Computer Vision to Optimization to Economics, to create solutions that seamlessly and automatically engage with Sellers, solve their problems, and help them grow. We strive to radically simplify the seller experience, lowering the cognitive burden of selling on Amazon by making it easy to accomplish critical tasks such as launching new products, understanding and complying with Amazon’s policies and taking actions to grow their business.

Are you passionate to join an innovative team of scientists and engineers who use machine learning and AI techniques to create state-of-the-art solutions to help seller succeed on Amazon? The Selling Partner Growth org is looking for a Senior Applied Scientist to lead us on our mission to understand demand side signals on Amazon, and empower sellers to grow their business and provide a great customer experience. As a Senior Applied Scientist on our team of scientists and engineers, you will have opportunities to create significant impact on our systems, our business and most importantly, our customers as we take on challenges that can revolutionize the e-commerce industry. You will identify specific and actionable opportunities to solve business problems, propose state-of-the-art solutions and collaborate with engineering, and business teams for future innovation. You need to be a great translation between ambiguous business domains and rigorous scientific solutions, an expert at inventing and simplify, and a good communicator to surface insights and recommendations to audiences of varying levels of technical sophistication. Major responsibilities - Use machine learning and AI techniques to create scalable seller-facing solutions - Analyze and extract relevant information from large amounts of Amazon's historical business data to help automate and optimize key processes - Design, development and evaluation of highly innovative models - Work closely with software engineering teams to drive real-time model implementations and new feature creations To know more about Amazon science, Please visit https://www.amazon.science

Do you want to join an innovative team of scientists who use machine learning and statistical techniques to create state-of-the-art solutions for providing better value to Amazon’s customers? Do you want to build and deploy advanced algorithmic systems that help optimize millions of transactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data to solve real world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Machine Learning and Data Sciences team for India Consumer Businesses. If you have an entrepreneurial spirit, know how to deliver, love to work with data, are deeply technical, highly innovative and long for the opportunity to build solutions to challenging problems that directly impact the company's bottom-line, we want to talk to you. Major responsibilities - Use machine learning and analytical techniques to create scalable solutions for business problems - Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes - Design, development, evaluate and deploy innovative and highly scalable models for predictive learning - Research and implement novel machine learning and statistical approaches - Work closely with software engineering teams to drive real-time model implementations and new feature creations - Work closely with business owners and operations staff to optimize various business operations - Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation - Mentor other scientists and engineers in the use of ML techniques A day in the life You will solve real-world problems by getting and analyzing large amounts of data, generate insights and opportunities, design simulations and experiments, and develop statistical and ML models. The team is driven by business needs, which requires collaboration with other Scientists, Engineers, and Product Managers across the International Emerging Stores organization. You will prepare written and verbal presentations to share insights to audiences of varying levels of technical sophistication. About the team Central Machine Learning team works closely with the IES business and engineering teams in building ML solutions that create an impact for Emerging Marketplaces. This is a great opportunity to leverage your machine learning and data mining skills to create a direct impact on millions of consumers and end users.

Amazon is looking for creative Applied Scientists to tackle some of the most interesting problems in Artificial Intelligence (AI), natural language processing (NLP), knowledge graph curation, search, recommendation and related areas with our Amazon Books team. At Amazon Books we believe that reading is essential for a healthy society. As such, we aim to inspire readers by making it easy to read more and get more out of reading. We do this by creating an unmatched book discovery experience for our customers worldwide. We enable customers to discover new books, authors and genres through smart search tools, intelligent interactions and sophisticated recommendations, and we need your help to keep innovating in this space. If you are looking for an opportunity to solve deep technical problems and build innovative solutions in a fast-paced environment working within a smart and passionate team, this might be the role for you. You will develop and implement novel algorithms, agentic systems and modeling techniques to advance the state-of-the-art in technology areas at the intersection of AI, LLMs, NLP, search, and deep learning. You will innovate at scale, help move the needle for research in these exciting areas and build state-of-the-art technologies that enable delightful experiences for hundreds of millions of people. Key job responsibilities In this role you will: - Work collaboratively with other scientists and developers to design and implement scalable and reliable pipelines for ensuring our vast knowledge base of books meets the highest levels of accuracy and is aligned with how customers think about books; - set the scientific roadmap needed to sustain state-of-the-art quality and efficiency. Stay up-to-date with the latest technologies and adopt the most appropriate long-term solution to a variety of use cases. - set the standard for science rigor and quality, deal with ambiguity and competing objectives, and mentor other members to achieve their career growth potential. - Drive scalable solutions: from understanding the customer and business needs, to prototyping, production testing and through engineering directly to production. A day in the life Day-to-day work varies, but on a typical day you will: - run (or supervise) experiments. Depending on the stage or project, this may involve designing the experiments, collecting data, training models, prompt/spec engineering/optimization, error analysis, online system analysis, etc. - drive decisions by interpreting and communicating experimental results with stakeholders (managers, subject matter experts, other scientists, and engineers) and seeking/listening to their feedback. - strategic thinking: review results, identify trends and what step-changes are needed. You'll contribute to regular meetings, activities and conferences with the wider science team, organization as well as internal and external communities. About the team The team consists of a collaborative group of scientists, product leaders, and dedicated engineering teams. Our aim is to maintain the world’s most accurate and descriptive set of books metadata, where every title in our catalog is uniquely characterized via a set of high-quality, concise attributes. We believe this is a foundational capacity for any bookstore. We work with sister teams to leverage our systems to drive a diverse array of customer experiences, owned both by ourselves and others, that enable customers to easily identify their ideal next read.

At AWS Healthcare AI, we're revolutionizing healthcare delivery through AI solutions that serve millions globally. As a pioneer in healthcare technology, we're building next-generation services that combine Amazon's world-class AI infrastructure with deep healthcare expertise. Our mission is to accelerate our healthcare businesses by delivering intuitive and differentiated technology solutions that solve enduring business challenges. The AWS Healthcare AI organization includes services such as HealthScribe, Comprehend Medical, HealthLake, and more. We're seeking a Senior Applied Scientist to join our team working on our AI driven clinical solutions that are transforming how clinicians interact with patients and document care. Key Job Responsibilities To be successful in this mission, we are seeking an experienced Applied Scientist to lead pioneering research and development of new, highly confidential AI applications that re-imagine experiences for end-customers (e.g., consumers, patients), frontline workers (e.g., customer service agents, clinicians), and back-office staff (e.g., claims processing, medical coding). As a leading subject matter expert in NLU, deep learning, knowledge representation, foundation models, and reinforcement learning, you will guide a team of scientists to invent novel, generative AI-powered experiences. This role involves defining research directions, developing new ML techniques, conducting rigorous experiments, and ensuring research translates to impactful products. You will be a hands-on technical innovator who is passionate about building scalable scientific solutions. You will set the standard for excellence, invent scalable, scientifically sound solutions across teams, define evaluation methods, and lead complex reviews. This role wields significant influence across AWS, Amazon, and the global research community.

Have you ever wondered how that Amazon box with the smile arrives so quickly, where it came from, and how much it cost Amazon to deliver? The WW Amazon Logistics, Business Analytics team manages the delivery of tens of millions of products every week to Amazon's customers, achieving on-time delivery in a cost-effective manner. We are seeking an enthusiastic, customer-obsessed Sr. Manager Research Science with strong analytical skills to join our team. This role is crucial in optimizing Amazon's vast delivery network and will have significant impact on the customer experience, particularly in the final phase of delivery. As a Sr. Manager Research Science, you will: 1. Address business challenges through building compelling cases and using data to influence change across the organization 2. Develop input and assumptions based on preexisting models to estimate costs and savings opportunities associated with varying levels of network growth and operations 3. Create metrics to measure business performance, identify root causes and trends, and prescribe action plans 4. Manage multiple high-impact projects simultaneously 5. Work with technology teams and product managers to develop new tools and systems supporting business growth 6. Communicate with and support various internal stakeholders and external audiences 7. Implement scheduling solutions, improve metrics, and develop scalable processes and tools The ideal candidate will have: - Extensive experience in operations research and data-driven decision making - Strong analytical and problem-solving skills - Robust program management and research science skills - Ability to work with a team and make independent decisions in ambiguous environments - Customer-obsessed mindset with a focus on improving the Amazon delivery experience This role offers the autonomy to think strategically and make data-driven decisions from day one. Join us in shaping the future of e-commerce delivery and addressing the core challenges in our world-class operations space! Key job responsibilities 1. Advanced Modeling and Algorithm Development: - Design and implement sophisticated machine learning models for logistics optimization - Develop complex time series forecasting algorithms for demand prediction and resource allocation 2. AI and Machine Learning Integration: - Architect and deploy AI-powered systems to enhance decision-making in logistics operations - Implement deep learning techniques for image recognition in package sorting and handling - Develop reinforcement learning algorithms for adaptive scheduling and resource management 3. Big Data Analytics and Processing: - Design and implement distributed computing solutions for processing massive logistics datasets - Utilize cloud computing platforms (e.g., AWS) for scalable data processing and analysis 4. AI-Driven Workflow Optimization: - Design and implement AI agents for autonomous decision-making in logistics processes - Create machine learning models for customer behavior analysis and personalized delivery options 5. Software Development and System Architecture: - Write efficient, scalable code in languages such as Python, Java, or C++ - Develop and maintain complex software systems for logistics optimization - Stay at the forefront of AI and ML research - Publish research findings in top-tier conferences and journals About the team We are Amazon's Last Mile Science and Analytics team, dedicated to improving e-commerce delivery. We work to optimize our vast network, forecast demand using machine learning, and enhance route efficiency. Our efforts focus on developing innovative delivery methods, applying AI to solve complex problems, and conducting geospatial analysis. We create simulations to refine processes and plan capacity effectively. Operating globally, we strive to develop adaptable solutions for diverse markets. We aim to advance logistics science, continually improving speed, efficiency, and customer satisfaction, in support of Amazon's mission to be Earth's most customer-centric company.

This position requires that the candidate selected be a US Citizen and currently possess and maintain an active Top Secret security clearance. The Amazon Web Services Professional Services (ProServe) team is seeking an experienced Delivery Practice Manager (DPM) to join our ProServe Shared Delivery Team (SDT) at Amazon Web Services (AWS). In this role, you'll manage a team of ProServe Delivery Consultants while supporting AWS enterprise customers through transformative projects. You'll leverage your IT and/or Management Consulting background to serve as a strategic advisor to customers, partners, and internal AWS teams. As a DPM you will be responsible for building and managing a team of Delivery Consultants and/or Engagement Managers working with customers and partners to architect and implement innovative solutions. You’ll routinely engage with Director, C-level executives, and governing boards, whilst being responsible for opportunity capture and driving engagement delivery. You’ll work closely with partner teams; drive business development initiatives through thought leadership; provide portfolio guidance and oversight; and meet and exceed customer satisfaction targets. As a DPM you are primarily focused directly or through their teams, on understanding and defining business outcomes for customers by building trust, identifying applicable AWS Professional Services offerings, and creating proposals and SOW’s. Your experience gained leading teams within the technology sector, will equip you with the ability to optimize team performance through implementing tailored people development plans, ensuring your teams are aligned to customer needs, and have the skills and capacity to address customer outcomes. Possessing the ability to translate technical concepts into business value for customers and then talk in technical depth with teams, you will cultivate strong customer, Amazon Global Sales (AGS), and ProServe team relationships which enables exceptional business performance. DPMs success is primarily measured by consistently delivering customer engagements by supporting sales through scoping technical requirements for an engagement, delivering engagements on time, within budget, and exceeding customer expectations. They will hold the Practice total utilization goal and be responsible for optimizing team performance. The AWS Professional Services organization is a global team of experts that help customers realize their desired business outcomes when using the AWS Cloud. We work together with customer teams and the AWS Partner Network (APN) to execute enterprise cloud computing initiatives. Our team provides assistance through a collection of offerings which help customers achieve specific outcomes related to enterprise cloud adoption. We also deliver focused guidance through our global specialty practices, which cover a variety of solutions, technologies, and industries. Key job responsibilities • Building and managing a high-performing team of Delivery Consultants • Collaborating with Delivery Consultants, Engagement Managers, Account Executives, and Cloud Architects to deploy solutions and provide input on new features • Developing and overseeing the implementation of innovative, forward-looking IT strategies for customers • Managing practice P&L, ensuring on-time and within-budget delivery of customer engagements • Driving business development initiatives and exceed customer satisfaction targets

Amazon Advertising is one of Amazon's fastest growing businesses. Amazon's advertising portfolio helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day! The Creative X team within Amazon Advertising time aims to democratize access to high-quality creatives (audio, images, videos, text) by building AI-driven solutions for advertisers. To accomplish this, we are investing in understanding how best users can leverage Generative AI methods such as latent-diffusion models, large language models (LLM), generative audio (music and speech synthesis), computer vision (CV), reinforced learning (RL) and related. As an Applied Scientist you will be part of a close-knit team of other applied scientists and product managers, UX and engineers who are highly collaborative and at the top of their respective fields. We are looking for talented Applied Scientists who are adept at a variety of skills, especially at the development and use of multi-modal Generative AI and can use state-of-the-art generative music and audio, computer vision, latent diffusion or related foundational models that will accelerate our plans to generate high-quality creatives on behalf of advertisers. Every member of the team is expected to build customer (advertiser) facing features, contribute to the collaborative spirit within the team, publish, patent, and bring SOTA research to raise the bar within the team. As an Applied Scientist on this team, you will: - Drive the invention and development of novel multi-modal agentic architectures and models for the use of Generative AI methods in advertising. - Work closely and integrate end-to-end proof-of-concept Machine Learning projects that have a high degree of ambiguity, scale and complexity. - Build interface-oriented systems that use Machine Learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models. - Curate relevant multi-modal datasets. - Perform hands-on analysis and modeling of experiments with human-in-the-loop that eg increase traffic monetization and merchandise sales, without compromising the shopper experience. - Run A/B experiments, gather data, and perform statistical analysis. - Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving. - Mentor and help recruit Applied Scientists to the team. - Present results and explain methods to senior leadership. - Willingness to publish research at internal and external top scientific venues. - Write and pursue IP submissions. Key job responsibilities This role is focused on developing new multi-modal Generative AI methods to augment generative imagery and videos. You will develop new multi-modal paradigms, models, datasets and agentic architectures that will be at the core of advertising-facing tools that we are launching. You may also work on development of ML and GenAI models suitable for advertising. You will conduct literature reviews to stay on the SOTA of the field. You will regularly engage with product managers, UX designers and engineers who will partner with you to productize your work. For reference see our products: Enhanced Video Generator, Creative Agent and Creative Studio. A day in the life On a day-to-day basis, you will be doing your independent research and work to develop models, you will participate in sprint planning, collaborative sessions with your peers, and demo new models and share results with peers, other partner teams and leadership. About the team The team is a dynamic team of applied scientists, UX researchers, engineers and product leaders. We reside in the Creative X organization, which focuses on creating products for advertisers that will improve the quality of the creatives within Amazon Ads. We are open to hiring candidates to work out of one of the following locations: UK (London), USA (Seattle).

Lead ML teams building large-scale forecasting and optimization systems that power Amazon’s global transportation network and directly impact customer experience and cost. As an Sr Applied Scientist, you will set scientific direction, mentor applied scientists, and partner with engineering and product leaders to deliver production-grade ML solutions at massive scale. Key job responsibilities 1. Lead and grow a high-performing team of Applied Scientists, providing technical guidance, mentorship, and career development. 2. Define and own the scientific vision and roadmap for ML solutions powering large-scale transportation planning and execution. 3. Guide model and system design across a range of techniques, including tree-based models, deep learning (LSTMs, transformers), LLMs, and reinforcement learning. 4. Ensure models are production-ready, scalable, and robust through close partnership with stakeholders. Partner with Product, Operations, and Engineering leaders to enable proactive decision-making and corrective actions. 5. Own end-to-end business metrics, directly influencing customer experience, cost optimization, and network reliability. 6. Help contribute to the broader ML community through publications, conference submissions, and internal knowledge sharing. A day in the life Your day includes reviewing model performance and business metrics, guiding technical design and experimentation, mentoring scientists, and driving roadmap execution. You’ll balance near-term delivery with long-term innovation while ensuring solutions are robust, interpretable, and scalable. Ultimately, your work helps improve delivery reliability, reduce costs, and enhance the customer experience at massive scale.

At Amazon, we strive every day to be Earth’s most customer-centric company. Selling Partner Support Engagement (SPSE) Science delivers on this by building AI-enhanced experiences that provide world class support to our global network of selling partners. We are building applications at the forefront of GenAI applications, tackling the challenges caused by the volume, diversity, and complexity of our selling partner's needs. Do you want to join a team of scientists with critical problem solving skills who are innovating on behalf of our customers using natural language processing and generative AI? Are you interested in helping us redefine what world class support can be in an age of automation and AI, while prizing human empathy and ingenuity? Are you excited by the prospect of your solutions resulting in large-scale impact while getting a chance to research at the forefront of AI innovation? The SPSE Science Team is looking for a Senior Applied Scientist to build machine learning and GenAI solutions (agentic frameworks) that help us understand and solve our sellers' most challenging problems. We need to better understand our Sellers and the problems they face, to augment our human workforce with smarter tools and to automatically diagnose and resolve issues. In this role, you will have ownership of the end-to-end development of solutions to complex problems and you will play an integral role in strategic decision-making. You will also work closely with engineers, operations teams and product owners to build ML pipelines, platforms and solutions that solve problems of defect detection, automation, and workforce optimization. Key job responsibilities Use state-of-the-art Machine Learning and Generative AI techniques to create the next generation of tools that empower Amazon's Selling Partners and Support Associates to succeed. Design, develop and deploy models that either interact with end users or automate entire workflows. Work closely with teams of scientists and software engineers to drive online model implementations with impactful features through A/B testing. Establish scalable, efficient, automated processes for large scale data analyses, model benchmarking, model validation and model implementation. Research and implement novel machine learning approaches. Participate in strategic initiatives to employ the most recent advances in ML in a fast-paced, experimental environment. Raise the bar for ML design and execution for the scientists on the team. Assist in hiring the best talent on the team. About the team Selling Partner Support Engagement Science (Titans Science) is a growing team of scientists engaged in the research and development of the next generation of ML-driven technology to empower Amazon's Selling Partners to succeed. We strive to radically simplify the seller experience, making it easy to accomplish critical tasks such as launching new products, understanding and complying with Amazon’s policies and taking actions to grow their business. Scientists on the team get an opportunity to learn the state of the art end-to-end ML tooling and infrastructure offered through AWS and other open source technology stacks. The complexity of our work also give scientists an opportunity to successfully publish research in leading journals and conferences. We value 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. Additionally, the team fosters an inclusive and learning culture, inspiring us to embrace our uniqueness. We highly value individual growth; you will also find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.