Careers

The Artificial General Intelligence (AGI) team is looking for a highly skilled and experienced Senior Applied Scientist, to lead the development and implementation of cutting-edge algorithms and models to automate workflows, processes for browser automation, developers and operations teams. As part of this, we are developing services and inference engine for these automation agents; and techniques for reasoning, planning, and modeling workflows. As a Senior Applied Scientist, you will play a critical role in driving the development of Generative AI (GenAI) technologies that can handle Amazon-scale use cases and have a significant impact on our customers' experiences. Key job responsibilities - Develop cutting edge multimodal Large Language Models (LLMs) to observe, model and derive insights from manual workflows for automation - Work in a joint scrum with engineers for rapid invention, develop cutting edge automation agent systems, and take them to launch for millions of customers - Collaborate with cross-functional teams of engineers, product managers, and scientists to identify and solve complex problems in GenAI - Design and execute experiments to evaluate the performance of different algorithms and models, and iterate quickly to improve results - Think big about the arc of development of GenAI over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems - Communicate results and insights to both technical and non-technical audiences, including through presentations and written reports - Mentor and guide junior scientists and engineers, and contribute to the overall growth and development of the team

Amazon.com’s Buyer Risk Prevention's (BRP) mission is to make Amazon the safest and most trusted place worldwide to transact online. BRP safeguards every financial transaction across all Amazon sites. As such, BRP designs and builds the software systems, risk models, and operational processes that minimize risk and maximize trust in Amazon.com. The BRP organization is looking for an Applied Scientist for the Buyer Abuse team, whose mission is to combine advanced analytics with investigator insight to create mechanisms to proactively and reactively reduce the impact of abuse across Amazon. Key job responsibilities As an Applied Scientist, you will be responsible for modeling complex problems, discovering insights, and building cutting edge risk algorithms that identify opportunities through statistical models, machine learning, and visualization techniques to improve operational efficiency and reduce monetary losses and improve customer trust. You will need to collaborate effectively with business and product leaders within BRP and cross-functional teams to build scalable solutions against high organizational standards. The candidate should be able to apply a breadth of tools, data sources, and ML techniques to answer a wide range of high-impact business questions and proactively present new insights in concise and effective manner. The candidate should be an effective communicator capable of independently driving issues to resolution and communicating insights to non-technical audiences. This is a high impact role with goals that directly impacts the bottom line of the business. Responsibilities: - Invent, implement, and deploy state of the art machine learning algorithms and systems - Build prototypes and explore conceptually new solutions - Define and conduct experiments to validate/reject hypotheses, and communicate insights and recommendations to Product and Tech teams - Take ownership of how ML solutions impact Amazon resources and Customer experience - Develop efficient data querying infrastructure for both offline and online use cases - Collaborate with cross-functional teams from multidisciplinary science, engineering and business backgrounds to enhance current automation processes - Learn and understand a broad range of Amazon’s data resources and know when, how, and which to use and which not to use. - Research and implement novel machine learning and statistical approaches - Maintain technical document and communicate results to diverse audiences with effective writing, visualizations, and presentations Please visit https://www.amazon.science for more information

Do you want to join an innovative team of scientists who use deep learning, natural language processing, large language models to help Amazon provide the best seller experience across the entire Seller life cycle, including recruitment, growth, support and provide the best customer and seller experience by automatically mitigating risk? Do you want to build advanced algorithmic systems that help manage the trust and safety of millions of customer interactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data and creating state-of-the-art algorithms to solve real world problems? Are you excited by the opportunity to leverage GenAI and innovate on top of the state-of-the-art large language models to improve customer and seller experience? Do you like to build end-to-end business solutions and directly impact the profitability of the company? Do you like to innovate and simplify processes? If yes, then you may be a great fit to join the Machine Learning Accelerator team in the Amazon Selling Partner Services (SPS) group. Key job responsibilities The scope of an Applied Scientist III in the Selling Partner Services (SPS) Machine Learning Accelerator (MLA) team is to research and prototype Machine Learning applications that solve strategic business problems across SPS domains. Additionally, the scientist collaborates with engineers and business partners to design and implement solutions at scale when they are determined to be of broad benefit to SPS organizations. They develop large-scale solutions for high impact projects, introduce tools and other techniques that can be used to solve problems from various perspectives, and show depth and competence in more than one area. They influence the team’s technical strategy by making insightful contributions to the team’s priorities, approach and planning. They develop and introduce tools and practices that streamline the work of the team, and they mentor junior team members and participate in hiring.

Amazon is committed to exceeding customer expectations. In the Returns and Recommerce organization, we seek to improve customer satisfaction with the items they buy on Amazon, provide new value for our customers, and reduce costs to drive the holistic business flywheel. We are looking for a dynamic, resourceful, and organized Economist to join the Returns and Recommerce organization to develop new, data-driven solutions to support the most critical components of this rapidly scaling team. The Amazon R&R team has an opening for applied micro, empirical IO, and time series and forecasting with demonstrated industry, policy, or academic experience. You will apply economic theory to build econometric models, and prototype and put into production scalable implementations in partnership with technical teams, using Amazon’s world class data systems. You will be expected to be a thought leader as we chart new courses with our customer delivery support technologies. Successful candidates will have a deep knowledge of quantitative modelling in at least one area (ML, forecasting/time series, optimization, causal modeling), the ability to build and refine models that can be implemented in production, the communication skills necessary to explain complex technical approaches to a variety of stakeholders and customers, and the excitement to take iterative approaches to tackle big, long-term problems. Economists at Amazon will be expected to develop new techniques to process large data sets, address quantitative problems, and contribute to design of automated systems around the company. The economics community at Amazon has grown tremendously in the past few years – economists in Amazon R&R partner with economists company-wide to tackle some of the hardest problems at Amazon. As part of the R&R organization, you’ll partner closely with Science, Product, Tech, and Program teams to design innovative solutions to organizational and business problems, communicating highly complex findings to multiple audiences. The ability to understand and measure policy effects and then integrate them into downstream optimization systems is a highly valuable asset. You may come from any one of a variety of econometric backgrounds, but you must be comfortable with multiple modeling techniques, be able to acquire new techniques with practice, and be willing to show flexibility in finding the right technique to match the research problem. Our economists will be comfortable with both ambiguity and autonomy, and excel at investigative analyses. Key job responsibilities Key Responsibilities: - Conceptualize and lead global research initiatives in the Returns and Recommerce space - Guide the technical approach for the design and implementation of successful models and algorithms in support of expert cross-functional teams delivering on demanding projects - Conduct, direct, and coordinate all phases of research projects, demonstrating skill in all stages of the analysis process, including defining key research questions, recommending measures, working with multiple data sources, evaluating methodology and design, executing analysis plans, interpreting and communicating results - Functionally decompose complex problems into simple, straight-forward solutions

Amazon Devices is revolutionizing smart home devices and services, and we're seeking a visionary Senior Economist to lead the charge. In this high-impact role, you'll flex your advanced Empirical IO and Structural Demand modeling expertise to tackle complex pricing challenges for a diverse portfolio of world-class products and services. Imagine being the driving force behind the pricing and demand strategies that power game-changing innovations for brands like Alexa, Ring, Blink, and Kids+. Your insights will directly influence critical business decisions, like optimizing, bundled offerings, and feature roadmaps for subscriptions. Get ready to dive deep, uncover valuable insights, and transform them into real-world impact. Whether you're supporting products pre-launch or fine-tuning mature business lines, your work will have a multi-million-dollar influence. As a Senior Economist on the Subscription Science team, you'll collaborate cross-functionally to shape product roadmaps. Sound like the kind of challenge you thrive on? Bring your passion for problem-solving, your knack for translating data into action, and your entrepreneurial spirit – and join us on the frontlines of the connected home revolution. This is your opportunity to make a lasting mark and create experiences that delight customers worldwide. Key job responsibilities - Develop advanced structural demand and econometric frameworks for products and services in Amazon Devices. - Create and drive the scientific roadmap for the team, and influence partner science teams - Drive cross-functional collaboration with scientists, engineers, and business leaders to integrate economic insights into strategic decision-making processes and shape future initiatives. - Communicate insights in writing and verbally, to senior leaders on Product and Finance teams within the company. - Actively mentor junior scientists on advanced econometric techniques. About the team This role is in the Subscription Science team, a cross-functional team in Amazon Devices that focuses on developing science models to inform major one-way door decisions that lead to customer facing changes for our products and services, and using these insights to help product teams focus efforts on improving products for their customers. We do this by building world-class demand models which provide pricing recommendations, for these organizations and help inform critical business investment decisions, frequently presenting results to the highest levels of leadership in the organization. In addition to the primary job location we are open to considering locations near major Amazon hubs including but not limited to Arlington VA (HQ2 near DC).

Amazon is looking for an outstanding Senior Research Scientist to help build next generation selection/assortment systems. On the Specialized Selection team within the Supply Chain Optimization Technologies (SCOT) organization, we own the selection to determine which products Amazon offers in our fastest delivery programs. We build tools and systems that enable our partners and business owners to scale themselves by leveraging our problem domain expertise, focusing instead on introspecting our outputs and iteratively helping us improve our ML models rather than hand-managing their assortment. We partner closely with our business stakeholders as we work to develop state-of-the-art, scalable, automated selection. As an Senior Research Scientist, you will work with software engineers, product managers, and business teams to understand the business problems and requirements, distill that understanding to crisply define the problem, and design and develop innovative solutions to address them. Our team is highly cross-functional and employs a wide array of scientific tools and techniques to solve key challenges, including supervised and unsupervised machine learning, non-convex optimization, causal inference, natural language processing, linear programming, reinforcement learning, and other forecast algorithms. Some critical research areas in our space include modeling substitutability between similar products, incorporating basket awareness and complementarity-aware logic, measuring speed sensitivity of products, modeling network capacity constraints, and supply and demand forecasting. Key job responsibilities You will be an end-to-end owner for the projects you support. Responsibilities include: - Understanding business requirements and existing challenges and map them to the right scientific solution; - Designing effective, scalable, and achievable solutions to key business problems; - Developing the right set of metrics to evaluate efficacy of your models and solutions; - Prototyping and analyzing new models and business logic; - Synthesize learnings from past policy changes into critical insight to help the business develop new strategies and make science-based decisions; - Designing experiments to measure pilot programs and support scaling-up effort; - Communicating, both written and verbally, with both technical and business audiences throughout each project; - Publishing findings in internal and/or external conferences and interfacing with the scientific community; - Mentoring and developing the scientist community across the organization

We’re working to improve shopping on Amazon using the conversational capabilities of large language models, and are searching for pioneers who are passionate about technology, innovation, and customer experience, and are ready to make a lasting impact on the industry. You'll be working with talented scientists, engineers, and technical program managers (TPM) to innovate on behalf of our customers. 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 We seek strong Applied Scientists with domain expertise in machine learning and deep learning, transformers, generative models, large language models, computer vision and multimodal models. You will devise innovative solutions at scale, pushing the technological and science boundaries. You will guide the design, modeling, and architectural choices of state-of-the-art large language models and multimodal models. You will devise and implement new algorithms and new learning strategies and paradigms. You will be technically hands-on and drive the execution from ideation to productionization. You will work in collaborative environment with other technical and business leaders, to innovate on behalf of the customer.

Amazon is investing heavily in building a world class advertising business and developing a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses for 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. We are seeking a technical leader for our Supply Science team. This team is within the Sponsored Product team, and works on complex engineering, optimization, econometric, and user-experience problems in order to deliver relevant product ads on Amazon search and detail pages world-wide. The team operates with the dual objective of enhancing the experience of Amazon shoppers and enabling the monetization of our online and mobile page properties. Our work spans ML and Data science across predictive modeling, reinforcement learning (Bandits), adaptive experimentation, causal inference, data engineering. Key job responsibilities Search Supply and Experiences, within Sponsored Products, is seeking a Senior Applied Scientist to join a fast growing team with the mandate of creating new ads experience that elevates the shopping experience for our hundreds of millions customers worldwide. We are looking for a top analytical mind capable of understanding our complex ecosystem of advertisers participating in a pay-per-click model– and leveraging this knowledge to help turn the flywheel of the business. As a Senior Applied Scientist on this team you will: --Act as the technical leader in Machine Learning and drive full life-cycle Machine Learning projects. --Lead technical efforts within this team and across other teams. --Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production. --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. --Work closely with software engineers to assist in productionizing your ML models. --Research new machine learning approaches. --Recruit Applied Scientists to the team and act as a mentor to other scientists on the team. A day in the life The successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail, and with an ability to work in a fast-paced, high-energy and ever-changing environment. The drive and capability to shape the direction is a must. About the team We are a customer-obsessed team of engineers, technologists, product leaders, and scientists. We are focused on continuous exploration of contexts and creatives where advertising delivers value to customers and advertisers. We specifically work on new ads experiences globally with the goal of helping shoppers make the most informed purchase decision. We obsess about our customers and we are continuously innovating on their behalf to enrich their shopping experience on Amazon

By applying to this position, your application will be considered for all locations we hire for in the United States. Are you interested in machine learning, deep learning, automated reasoning, speech, robotics, computer vision, optimization, or quantum computing? We are looking for applied scientists capable of using a variety of domain expertise to invent, design, evangelize, and implement state-of-the-art solutions for never-before-solved problems. Our full-time opportunities are available in, but are not limited to the following domains: • Machine Learning: You will put Machine Learning theory into practice through experimentation and invention, leveraging machine learning techniques (such as random forest, Bayesian networks, ensemble learning, clustering, etc.), and implement learning systems to work on massive datasets in an effort to tackle never-before-solved problems. • Automated Reasoning: AWS Automated Reasoning teams deliver tools that are called billions of times daily. Amazon development teams are integrating automated-reasoning tools such as Dafny, P, and SAW into their development processes, raising the bar on the security, durability, availability, and quality of our products. Areas of work include: Distributed proof search, SAT and SMT solvers, Reasoning about distributed systems, Automating regulatory compliance, Program analysis and synthesis, Security and privacy, Cryptography, Static analysis, Property-based testing, Model-checking, Deductive verification, compilation into mainstream programming languages, Automatic test generation, and Static and dynamic methods for concurrent systems. • Natural Language Processing and Speech Technologies: You will tackle some of the most interesting research problems on the leading edge of natural language processing. We are hiring in all areas of spoken language understanding: NLP, NLU, ASR, text-to-speech (TTS), and more! • Computer Vision and Robotics: You will help build solutions where visual input helps the customers shop, anticipate technological advances, work with leading edge technology, focus on highly targeted customer use-cases, and launch products that solve problems for our customers. • Quantum: Quantum computing is rapidly emerging and our customers can the see the potential it has to address their challenges. One of our missions at AWS is to give customers access to the most innovative technology available and help them continuously reinvent their business. Quantum computing is a technology that holds promise to be transformational in many industries. We are adding quantum computing resources to the toolkits of every researcher and developer. If this sounds exciting to you - come build the future with us! Key job responsibilities You will have access to large datasets with billions of images and video to build large-scale systems Analyze and model terabytes of text, images, and other types of data to solve real-world problems and translate business and functional requirements into quick prototypes or proofs of concept Own the design and development of end-to-end systems Write technical white papers, create technical roadmaps, and drive production level projects that will support Amazon Web Services Work closely with AWS scientists to develop solutions and deploy them into production Work with diverse groups of people and cross-functional teams to solve complex business problems

Our mission is to create best-in-class AI agents that seamlessly integrate multimodal inputs like speech, images, and video, enabling natural, empathetic, and adaptive interactions. We develop cutting-edge Large Language Models (LLMs) that leverage advanced architectures, cross-modal learning, interpretability, and responsible AI techniques to provide coherent, context-aware responses augmented by real-time knowledge retrieval. We seek a talented Applied Scientist with expertise in LLMs, speech, audio, NLP, or multimodal learning to pioneer innovations in data simulation, representation, model pre-training/fine-tuning, generation, reasoning, retrieval, and evaluation. The ideal candidate will build scalable solutions for a variety of applications, such as streaming real-time conversational experiences, including multilingual support, talking avatar interactions, customizable personalities, and conversational turn-taking. With a passion for pushing boundaries and rapid experimentation, you'll deliver high-impact solutions from research to customer-facing products and services. Key job responsibilities As an Applied Scientist, you'll leverage your expertise to research novel algorithms and modeling techniques to develop data simulation approaches mimicking real-world interactions with a focus on the speech modality. You'll acquire and curate large, diverse datasets while ensuring privacy, creating robust evaluation metrics and test sets to comprehensively assess LLM performance. Integrating human-in-the-loop feedback, you'll iterate on data selection, sampling, and enhancement techniques to improve the core model performance. Your innovations in data representation, model pre-training/fine-tuning on simulated and real-world datasets, and responsible AI practices will directly impact customers through new AI products and services.