Careers

The Private Brands Discovery team designs innovative machine learning solutions to enhance customer awareness of Amazon’s own brands and help customers find products they love. This interdisciplinary team of scientists and engineers incubates and develops disruptive solutions using cutting-edge technology to tackle some of the most challenging scientific problems at Amazon. To achieve this, the team utilizes methods from Natural Language Processing, deep learning, large language models (LLMs), multi-armed bandits, reinforcement learning, Bayesian optimization, causal and statistical inference, and econometrics to drive discovery throughout the customer journey. Our solutions are crucial to the success of Amazon’s private brands and serve as a model for discovery solutions across the company. This role presents a high-visibility opportunity for someone eager to make a business impact, delve into large-scale problems, drive measurable actions, and collaborate closely with scientists and engineers. As a team lead, you will be responsible for developing and coaching talent, guiding the team in designing and developing cutting-edge models, and working with business, marketing, and software teams to address key challenges. These challenges include building and improving models for sourcing, relevance, and CTR/CVR estimation, deploying reinforcement learning methods in production etc. In this role, you will be a technical leader in applied science research with substantial scope, impact, and visibility. A successful team lead will be an analytical problem solver who enjoys exploring data, leading problem-solving efforts, guiding the development of new frameworks, and engaging in investigations and algorithm development. You should be capable of effectively interfacing between technical teams and business stakeholders, pushing the boundaries of what is scientifically possible, and maintaining a sharp focus on measurable customer and business impact. Additionally, you will mentor and guide scientists to enhance the team's talent and expand the impact of your work.

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!

Are you passionate about automation, optimization, knowledge extraction, and artificial intelligence through the use of Machine Learning, Computer Vision, Optimization, Natural Language Processing, and Recommender systems? We have a team of experienced scientists with a critical business mission making revolutionary leaps forward in these spaces. On this team you will work with large multimodal datasets to build generative and discriminative models for optimizing large-scale manufacturing and fulfillment processes, analyze and model customer reading behavior to measure engagement and detect risks, and build AI-based systems for helping indie authors make their businesses successful. This will involve combining methods from several science domains with domain knowledge across multiple businesses into sophisticated ML workflows. Our team has mature areas and green-field opportunities. We offer scientific autonomy, value end-to-end ownership, and have a strong customer-focused culture. As an Applied Scientist at Amazon, you will connect with world leaders in your field working on similar problems. You will be working with large distributed systems of data and providing technical leadership to the product managers, teams, and organizations building machine learning solutions. You will be tackling Machine Learning challenges in Supervised, Unsupervised, and Semi-supervised Learning; utilizing modern methods such as deep learning and classical methods from statistical learning theory, detection, estimation. Senior Applied Scientists are specialists with the deep expertise to drive the scientific vision for our products. They are externally aware of the state-of-the-art in their respective field of expertise and are constantly focused on advancing that state-of-the-art for improving Amazon’s products and services. Come join us as we revolutionize the book industry and deliver an amazing experience to our Kindle authors and readers. Kindle Direct Publishing (KDP) and Print On Demand (POD) have empowered a new wave of self-motivated creators, tearing down barriers that once blocked writers from reaching readers. Our team builds rich applications and systems that empower anyone to realize their dream of becoming a published author. We strive to provide an experience that is powerful, yet simple to use and accessible to all. We focus on building tools that enable authors to design high quality digital and print books, reaching readers all around the world. This role will help ensure we maintain the trust of both our Authors and Readers by ensuring all books published to Amazon meet our standards. Great candidates for this position will be experts in the areas of data science, machine learning, computer vision, optimization, NLP, or statistics. You will have hands-on experience with multiple science initiatives as well as be able to balance technical leadership with strong business judgment to make the right decisions about technology, models and methodological choices. You will strive for simplicity, and demonstrate significant creativity and high judgment. Come join us as we continue to revolutionize the book industry!

AI for Domains (AIDO) team is part of Alexa Conversational Assistant Services organization where our mission is to create a best-in-class Conversational AI that is intuitive, intelligent, and responsive, by developing superior Large Language Models (LLM) solutions and services which increase the capabilities built into the model and which enable utilizing thousands of APIs and external knowledge sources to provide the best experience for each request across millions of customers and endpoints. We are looking for talented and experienced science leader in the field of LLM, Artificial Intelligence (AI), Natural Language Processing (NLP) and/or Information Retrieval, to invent and build scalable solutions for a state-of-the-art context-aware conversational AI. A successful candidate will have solid technical background and extensive experience in leading projects and technical teams. The ideal candidate would also have experiences in developing natural language processing systems (particularly LLM based systems) for industry applications, enjoy operating in highly dynamic and ambiguous environments, be self-motivated to take on challenging problems to deliver customer impact. Key job responsibilities As a Senior Applied Scientist, you will: * Build a strong and coherent team with particular focus on sciences and innovations in LLM technologies for conversation AI applications * Serve as a technical lead on demanding and cross-team projects, and effectively collaborating with multiple cross-organizational teams * Apply technical influence on partner teams, increasing their productivity by sharing your deep knowledge

Amazon is looking for world class senior applied scientist to join its AWS Fundamental Research Team working within a variety of machine learning disciplines. This group is entrusted with developing core machine learning solutions for AWS services. At the AWS Fundamental Research Team you will invent, implement, and deploy state of the art machine learning algorithms and systems. You will build prototypes and explore conceptually large scale ML solutions across different domains and computation platforms. You will interact closely with our customers and with the academic community. You will be at the heart of a growing and exciting focus area for AWS and work with other acclaimed engineers and world famous scientists. This team is part of AWS Utility Computing: Utility Computing (UC) AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services. About the team Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

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).

Would you like to work on developing ML models for one of the largest transactional distributed systems in the world? How about working with customers and peers from the entire range of Amazon's business and Science on complex real world problems, backed with high volume data ? Whether you're passionate about building highly scalable and reliable systems or a scientist who likes to solve business problems, Amazon Tax Platform Services is the place for you. We are responsible for the tax calculation platform, providing the core services that calculate taxes (sales tax and VAT) for all Amazon sales, physical and digital, globally. We seek to provide the correct tax amounts to the customer when placing their Amazon order, and ensure all records are stored safely to meet tax law requirements around the globe. Our challenges include staying on top of the complex and ever-changing global tax legislations as well as computing calculations correctly and quickly, thousands of times a second, and each one needs to be accurate. As an Applied scientist, you will provide machine learning leadership to the team that helps increase the accuracy of Tax classification based product information in Amazon catalogue making it the biggest and most challenging tax classification using Machine learning models globally. You will work with large language models, to build various machine learning models to predict accuracy of human's on specific tasks, reason with large volumes of systems changes to identify causal determinants, apply generative AI to model outcomes from sparse data. You will help us innovate different ways to enhance tax classification experience for our global customers. You will need to be entrepreneurial, work in a highly collaborative environment with SDEs, Product managers and businesses. We like to move fast, experiment, iterate and then scale quickly, thoughtfully balancing speed and quality.

Are you a MS or PhD student interested in a 2025 Internship in the field of machine learning, deep learning, speech, robotics, computer vision, optimization, quantum computing, automated reasoning, or formal methods? If so, we want to hear from you! We are looking for students interested in using a variety of domain expertise to invent, design and implement state-of-the-art solutions for never-before-solved problems. You can find more information about the Amazon Science community as well as our interview process via the links below; https://www.amazon.science/ https://amazon.jobs/content/en/career-programs/university/science https://amazon.jobs/content/en/how-we-hire/university-roles/applied-science Key job responsibilities As an Applied Science Intern, you will own the design and development of end-to-end systems. You’ll have the opportunity to write technical white papers, create roadmaps and drive production level projects that will support Amazon Science. You will work closely with Amazon scientists, and other science interns to develop solutions and deploy them into production. You will have the opportunity to design new algorithms, models, or other technical solutions whilst experiencing Amazon’s customer focused culture. The ideal intern must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. A day in the life At Amazon, you will grow into the high impact, visionary person you know you’re ready to be. Every day will be filled with developing new skills and achieving personal growth. How often can you say that your work changes the world? At Amazon, you’ll say it often. Join us and define tomorrow. Some more benefits of an Amazon Science internship include; • All of our internships offer a competitive stipend/salary • Interns are paired with an experienced manager and mentor(s) • Interns receive invitations to different events such as intern program initiatives or site events • Interns can build their professional and personal network with other Amazon Scientists • Interns can potentially publish work at top tier conferences each year About the team Applicants will be reviewed on a rolling basis and are assigned to teams aligned with their research interests and experience prior to interviews. Start dates are available throughout the year and durations can vary in length from 3-6 months for full time internships. This role may available across multiple locations in the EMEA region (Austria, Estonia, France, Germany, Ireland, Israel, Italy, Luxembourg, Netherlands, Poland, Romania, Spain, UAE, and UK). Please note these are not remote internships.

The Artificial General Intelligence (AGI) team is looking for a Senior Applied Scientist to work on pre-training methodologies for Generative Artificial Intelligence (GenAI) models. You will interact closely with our customers and with the academic and research communities. You will be at the heart of a growing and exciting focus area for Amazon, working with other acclaimed engineers and world-famous scientists. Key job responsibilities Join us to work as an integral part of a team that has diverse experience with GenAI models in this space. We work on these areas: - Scaling laws - Hardware-informed efficient model architecture, low-precision training - Optimization methods, learning objectives, curriculum design - Deep learning theories on efficient hyperparameter search and self-supervised learning - Reasoning, self-reflection, interactive learning, data synthesis - Distributed training methods and solutions About the team The AGI team has a mission to push the envelope in LLMs and multimodal systems, in order to provide the best-possible experience for our customers.