Careers

Amazon is looking for a passionate, talented, and inventive Applied Scientist with a strong machine learning, systems, applied statistics and natural language technologies background to join our Learned Systems Group (LSG) in the Agentic AI organization, and help build industry-leading large scale applied ML, AI and GenAI systems. As part of our LSG 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 systems, machine learning, artificial intelligence and human language technology. The Learned Systems Group at AWS helps build the scientific foundations of our genAI and analytics systems, including Redshift, Athena and RDS. We constantly push the state of the art to deploy state of the art ML and AI techniques at scale and finding new ways to delight our customers. We are constantly faced with large scale systems and we apply rigorous research methods to improve them with efficient and scalable innovative solutions. A day in the life 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 (gender diversity) conferences, inspire us to never stop embracing our uniqueness. 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. 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.

The Amazon Postdoctoral Science Program offers recent PhD graduates an exciting opportunity to gain hands-on industry experience, apply their specialized knowledge, and collaborate with Amazon's leading scientists. This program is designed for researchers who have completed their PhD within the past two years and are eager to bridge academia and industry, driving innovation at scale. “This program provides an excellent and fun opportunity to work on cutting-edge customer-obsessed research and learn from and collaborate with some of the brightest researchers and leading experts at Amazon,” said Sareh Nabi, a postdoctoral scientist in Amazon Ads who is participating in a postdoc pilot program. “It also provides a great platform to take the skillset I learned and apply it to a wide range of real-world applications on a large scale.” “This is an opportunity for outstanding researchers to work with us on our hardest scientific challenges,” said Jeremy Wyatt, senior manager of Amazon Robotics AI. “Amazon postdoctoral scientists will pursue exploratory work on our hardest problems, gaining industry experience and publishing the results in the best scientific venues.” Postdoctoral scientists will contribute to high-impact research initiatives, advance cutting-edge scientific developments, and publish their work in top-tier scientific journals. Participants will benefit from mentorship, access to Amazon's world-class resources, and exposure to real-world challenges with immediate customer impact. **Focus Areas** We are seeking candidates with expertise in foundational and applied research, particularly in: - Large Language Models (LLMs): Experience developing, fine-tuning, and scaling LLMs for diverse applications. - Graph Databases: Strong understanding of graph theory, data modeling, and implementation of graph database technologies in complex systems. - Mathematical Optimization: Good understanding of mathematical optimization, including mixed-integer optimization, combinatorial optimization, and robust optimization. **Basic Qualifications** - PhD in a relevant field (e.g., Computer Science, Operations Research, Mathematics, Statistics) received within 2 years of program start date. - Proven publication record in areas such as LLM, NLP, Generative AI, Graph Database, or other relevant domains. - Hands-on experience with technologies related to large language models, graph databases, and mathematical optimization. Preferred qualifications Postdocs demonstrate the following preferred job qualifications: - Ability to independently deliver results in a fast-paced environment - Publications at top-tier, peer-reviewed conferences and/or journals such as NurIPS, ICML, ICLR, CIKM, ICDE - Exceptional verbal and written communication skills - Expert knowledge in modeling and performance, operationalization, and scalability of scientific techniques and establishing decision strategies Required application materials: - CV, which lists all peer-reviewed publications and conferences - Research statement that outlines your research achievements and future research interests, and - A journal article or book chapter that demonstrates your domain expertise

AI is the most transformational technology of our time, capable of tackling some of humanity’s most challenging problems. That is why Amazon is investing in generative AI (GenAI) and the responsible development and deployment of large language models (LLMs) across all of our businesses. Come build the future of human-technology interaction with us. We are looking for a Research Scientist with strong technical skills which includes coding and natural language processing experience in dataset construction, training and evaluating models, and automatic processing of large datasets. You will play a critical role in driving innovation and advancing the state-of-the-art in natural language processing and machine learning. You will work closely with cross-functional teams, including product managers, language engineers, and other scientists. Key job responsibilities Specifically, the Research Scientist will: • Ensure quality of speech/language/other data throughout all stages of acquisition and processing, including data sourcing/collection, ground truth generation, normalization, transformation, cross-lingual alignment/mapping, etc. • Clean, analyze and select speech/language/other data to achieve goals • Build and test models that elevate the customer experience • Collaborate with colleagues from science, engineering and business backgrounds • Present proposals and results in a clear manner backed by data and coupled with actionable conclusions • Work with engineers to develop efficient data querying infrastructure for both offline and online use cases

Our customers have immense faith in our ability to deliver packages timely and as expected. A well planned network seamlessly scales to handle millions of package movements a day. It has monitoring mechanisms that detect failures before they even happen (such as predicting network congestion, operations breakdown), and perform proactive corrective actions. When failures do happen, it has inbuilt redundancies to mitigate impact (such as determine other routes or service providers that can handle the extra load), and avoids relying on single points of failure (service provider, node, or arc). Finally, it is cost optimal, so that customers can be passed the benefit from an efficiently set up network. 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 is looking for a passionate, talented, and inventive Scientist with a strong machine learning background to help build industry-leading Speech and Language technology. Our mission is to push the envelope in Automatic Speech Recognition (ASR), Natural Language Understanding (NLU), and Audio Signal Processing, in order to provide the best-possible experience for our customers. As a Speech and Language Scientist, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art in spoken language understanding. Your work will directly impact our customers in the form of products and services that make use of speech and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in spoken language understanding. We are hiring in the area of speech recognition (ASR) and associated technologies.

At Amazon, we believe that scientific innovation is essential to being the most customer-centric company in the world. Our scientists' ability to have an impact at scale allows us to attract some of the brightest minds in machine learning, artificial intelligence and related fields. Amazon scientists employ the company's working backwards method to identify problems to solve on behalf of customers in research areas ranging from machine learning to operations, GenAI, robotics, quantum computing, computer vision, economics, search, sustainability and more. Learn more about Amazon Science here: https://www.amazon.science/ We are hiring across multiple businesses and in many locations across the US. Apply here to learn more about open roles that could be a compelling fit for your background. Key job responsibilities You will be responsible for defining key research directions, adopting or inventing new machine learning techniques, conducting rigorous experiments, publishing results, and ensuring that research is translated into practice. You will develop long-term strategies, persuade teams to adopt those strategies, propose goals and deliver on them. You will also participate in organizational planning, hiring, mentorship and leadership development. You will be technically fearless and with a passion for building scalable science and engineering solutions. You will serve as a key scientific resource in full-cycle development (conception, design, implementation, testing to documentation, delivery, and maintenance).

Are you inspired by invention? Is problem solving through teamwork in your DNA? Do you like the idea of seeing how your work impacts the bigger picture? Answer yes to any of these and you’ll fit right in here at Amazon Robotics. We are a smart team of doers who work passionately to apply cutting edge advances in robotics and software to solve real-world challenges that will transform our customers’ experiences. We invent new improvements every day. We are Amazon Robotics and we will give you the tools and support you need to invent with us in ways that are rewarding, fulfilling, and fun. Amazon Robotics empowers a smarter, faster, more consistent customer experience through automation. Amazon Robotics automates fulfillment center operations using various methods of robotic technology including autonomous mobile robots, sophisticated control software, language perception, power management, computer vision, depth sensing, machine learning, object recognition, and semantic understanding of commands. Amazon Robotics has a dedicated focus on research and development to continuously explore new opportunities to extend its product lines into new areas. Key job responsibilities We are seeking an enthusiastic Data Scientist to: - Design and implement state-of-the-art solutions for never-before-solved problems. - Collaborate closely with other research and robotics experts to design and run experiments, research new algorithms, and find new ways to improve Amazon Robotics analytics to optimize the Customer experience. - Partner with technology and product leaders to solve business problems using scientific approaches. - Build new tools and invent business insights that surprise and delight our customers. - Work to quantify system performance at scale, and to expand the breadth and depth of our analysis to increase the ability of software components and warehouse processes. - Work to evolve our library of key performance indicators and construct experiments that efficiently root cause emergent behaviors. - Engage with software development teams and warehouse design engineers to drive the evolution of the Amazon Robotics system, as well as the simulation engine that supports our work. A day in the life As a member of the Software Research and Data Science (SWRDS) team, there are multiple different paths you can take. For example, you may conduct deep dive analysis of both structured and unstructured robotics field analyses. Some of our team members focus on modeling, pipelines and tooling work, while others focus more on analytic work. We also have team members working on early-concept solution analysis (leveraging simulations, ML-based models, experimenting with new solutions). About the team The Amazon Robotics Software Research and Data Science (SWRDS) team builds and runs simulation experiments and delivers analyses that are central to understanding the performance of the entire Amazon Robotics system. This includes operational and software scaling characteristics, bottlenecks, and robustness to “chaos monkey” stresses -- we inform critical engineering and business decisions about Amazon’s approach to robotic fulfillment.

Our team drives innovation for the onsite retail shopping site publisher. We collaborate and influence the advertising science community at Amazon across the entire Ads stack— sourcing and ranking ads, bidding into and pricing in the ads auction, experimentation design to measure causal impact of showing ads on shoppers and Amazon vendors, creative development with GenAI, and more. If you’re interested in joining a unique, highly respected advertising group with a relentless focus on the customer, you’ve come to the right place. As we continue building to out our team, we are looking for a Principal Applied Scientist, to lead research, design, experiment and implementation of cutting edge algorithms for complex Stores Display publisher use cases. You will collaborate with Amazon demand programs and front-end teams to influence how the entire advertising stack works end-to-end. You will work with business and finance teams to design experiments that inform tradeoffs across advertiser and shopper goals. You will work collaboratively with software engineers, data engineers, and other scientists on the team to deploy production algorithms that support the billions of ad auctions run daily and set a high bar for science and engineering excellence. This is a rare opportunity to be a foundational member with huge potential for impact and innovating new user experiences at Amazon. Why you will love this opportunity: Despite being part of a large business, we embrace a start-up mentality. This is an opportunity for massive impact and affords a lot of autonomy. Impact and Career Growth: You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. Key job responsibilities As a Principal Applied Scientist on this team, you will: - Be the technical science leader on the org; leading efforts within the team and across other teams. - Perform hands-on analysis and modeling of enormous data sets to develop insights that increase traffic monetization and retail merchandise sales, without compromising the shopper experience. - Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity. - Build 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. - 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. - Research new and innovative machine learning approaches. - Recruit Applied Scientists to the team and provide mentorship. About the team Amazon Advertising operates at the intersection of eCommerce and advertising, offering a rich array of digital advertising solutions with the goal of helping our customers find and discover anything they want to buy. We help advertisers reach Amazon customers on some of the most valued advertising real estate on the internet on the Amazon.com store. We start with the customer and work backwards in everything we do, including advertising.

Do you want to join an innovative team of scientists who invent and apply the most advanced machine learning and NLP techniques to create the best customer engagement experience on the earth? Do you want to revolutionize the way how customers solve their issues and get their questions answered? At Customer Engagement Technology (CET), we develop peculiar products that help customers solve problems. We innovate on behalf of customers, developing Bot, self-service, and associate-facing products that delight customers and support our world class customer service workforce. We are looking for talented Postdoctoral Scientists to join our CET Machine Learning team in Seattle, WA for a one-year, full-time research position to work on research and development of task oriented dialogue agents for the customer support domain. We utilize Large Language Models (LLMs) to address challenges within TOD systems, such as Natural Language Generation for generating system responses based, state tracking, decision making etc. We publish our research in top tier NLP and AI venues (EMNLP, ACL, AAAI, etc), and deploy ML powered chatbots primarily in the customer returns domain. Key job responsibilities In this role you will: • Work closely with a senior science advisor, collaborate with other scientists and engineers, and be part of Amazon’s vibrant and diverse global science community. • Publish your innovation in top-tier academic venues and hone your presentation skills. • Be inspired by challenges and opportunities to invent cutting-edge techniques in your area(s) of expertise.

As part of the AWS Applied AI Solutions organization, we're advancing the frontier of visual reasoning and agentic AI technologies. Our vision is to develop sophisticated AI systems that can understand, interpret, and reason about visual information at human-like levels, enabling breakthrough applications across multiple industries. Key job responsibilities - Spearhead research in Agentic AI for complex visual AI challenges - Innovate novel approaches to efficient visual processing mechanisms for large-scale, real-world applications - Pioneer advancements in autonomous decision-making and visual reasoning systems, pushing the boundaries of computational and data efficiency - Define and pursue long-term, high-impact research directions that shape the future of visual AI technologies - Provide scientific mentorship to junior researchers, fostering a culture of innovation and rigorous research methodology - Collaborate with cross-functional teams to bridge research with practical applications, influencing the broader scientific community A day in the life As a Principal Research Scientist, you'll drive research in visual reasoning and generative AI, defining novel research directions while ensuring impact through practical applications. Your day-to-day work will involve developing theoretical frameworks, conducting deep technical investigations, and validating complex hypotheses through rigorous experimentation. You'll mentor junior scientists in research methodology and experimental design while collaborating with cross-functional teams to translate research insights into scalable solutions. Your expertise and guidance will be instrumental in shaping both the technical direction of our visual AI initiatives and the development of junior research talent on the team. About the team Our research team is tackling fundamental challenges in visual reasoning that combine generative AI and agentic frameworks. We're investigating novel approaches to how AI systems understand spatial relationships, reason about object interactions, and maintain contextual awareness across time. Working at the intersection of computer vision and large language models, we're developing theoretical frameworks and practical techniques that advance the state-of-the-art in visual AI.