Careers

We are seeking an Applied Scientist to join our AI Security team, which builds security tooling and paved path solutions to ensure Generative AI (GenAI) based experiences developed by Amazon uphold our high security standards, and uses AI to develop foundational services that make security mechanisms more effective and efficient. As an Applied Scientist, you’ll be responsible for designing and implementing state-of-the-art solutions, to build an AI-based foundational service for securing products and services at Amazon scale. You will collaborate with applied scientists and software engineers to develop innovative technologies to solve some of our hardest security problems, and AI-based security solutions that support builder teams across Amazon throughout their software development journey, enabling Amazon businesses to strengthen their security posture more efficiently and effectively. Key job responsibilities • design and implement accurate and scalable methods to solve our hardest AI security problems • Lead and partner with applied scientists and software development engineers to drive technical design and implementation for a foundational GenAI-based security service About the team The mission of the AI Security organization is to ensure Generative AI experiences delivered by Amazon to our customers uphold our high security standards and to harness AI to strengthen Amazon’s security posture more efficiently and effectively. A day in the life A day in the life involves meeting Vulnerability Management and Incident Responder teams to review data flows, prediction use cases, and automation gaps. From here you will research data sets, working with security/software engineers to retrieve data needed for your analysis and explorations. Once you have framed the problems, you will conduct experiments, regressions, and various analysis activities to find insights. You will develop and train models that will then be placed into a production environment with the help of software engineers. You will then work with your security team partners to understand the effectiveness of the models created. About the team The Defensive Security team is small, tight-knit, and located in Austin, Texas. It is primarily software engineers, but will be developed into a hybrid team of software engineers and security engineers. This team will have tenured Amazonian leadership, with a track record of mentoring, coaching, and career progression support. About Amazon Security Diverse Experiences — Amazon Security 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 Amazon Security? — At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon’s products and services. We offer talented security professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores. Inclusive Team Culture — In Amazon Security, it’s in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices. Training & 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, training, 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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.

We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to work with large and complicated data sets. Some knowledge of econometrics, as well as basic familiarity with Python is necessary, and experience with SQL and UNIX would be a plus. These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis. You will learn how to build data sets and perform applied econometric analysis at Internet speed collaborating with economists, scientists, and product managers. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with placement. Roughly 85% of previous cohorts have converted to full time economist employment at Amazon. If you are interested, please send your CV to our mailing list at: econ-internship@amazon.com.

The Amazon Fulfillment Technologies (AFT) Science team is looking for an Applied Scientist with strong Deep Learning and Large Language Models background, to develop critical algorithms for generating reasoning and explainability for some key algorithms driving warehouse management processes on Amazon’s Fulfillment Network. We’re working to improve operations management within 4-walls of Amazon Fulfillment Center by using the conversational capabilities of large language models on existing algorithms, and developing online learning mechanisms. We are searching for pioneers who are passionate about technology, innovation, and customer experience, and are ready to make a lasting impact on the industry. Key job responsibilities Develop novel algorithms and modeling techniques to advance the state of the art with LLMs Analyze, understand, and model the operator (user/customer) behavior and the customer experience based on large scale data Build novel online & offline evaluation metrics and methodologies. Develop an understanding and domain knowledge of operational processes, system architecture and functions, and business requirements. Drive scalable and hands-off-the-wheel solutions. Create, enhance, and maintain technical documentation, and present to other scientists, engineers and business leaders. Partner with engineers to integrate prototypes into production systems. -Quickly experiment and setup experimentation framework for agile model and data analysis or A/B testing. Set high standards of coding and integrate successful models and algorithms in production systems. Use the best practices in science: data integrity, design, test, and implementation and documentation. Contribute to Amazon's Intellectual Property through patents and internal and external publications. Drive best practices on the team; mentor and guide junior members to achieve their career growth potential. A day in the life Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply! About the team Amazon Fulfillment Technology (AFT) designs, develops and operates the end-to-end fulfillment technology solutions for all Amazon Fulfillment Centers (FC). We harmonize the physical and virtual world so Amazon customers can get what they want, when they want it. The AFT Science team has expertise in computer vision, deep learning, operations research, optimization, scheduling, planning, simulation, and machine learning. We also have domain expertise in the operational processes within the FCs and their defects. We prioritize advancements that support AFT tech teams and focus areas rather than specific fields of research or individual business partners. We influence each stage of innovation from inception to deployment which includes both developing novel solutions or improving existing approaches. Resulting production systems rely on a diverse set of technologies, our teams therefore invest in multiple specialties as the needs of each focus area evolves.

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 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

Conversational AI ModEling and Learning (CAMEL) team is part of Amazon Artificial General Intelligence (AGI) 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 a passionate, talented, and resourceful Applied Scientist 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 strong machine learning background and a desire to push the envelope in one or more of the above areas. The ideal candidate would also have hands-on experiences in developing LLM solution, enjoy operating in dynamic environments, be self-motivated to take on challenging problems to deliver big customer impact, moving fast to ship solutions and then iterating on user feedback and interactions. Key job responsibilities As an Applied Scientist, you will leverage your technical expertise and experience to collaborate with other talented applied scientists and engineers to research and develop novel algorithms and modeling techniques to reduce friction and enable natural and contextual conversations. You will analyze, understand and improve user experiences by leveraging Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in artificial intelligence. You will work on core LLM technologies, including developing best-in-class modeling, prompt optimization algorithms to enable Conversation AI use cases. Your work will directly impact our customers in the form of novel products and services .

Amazon benefits is expanding our health actuarial team to support Amazon’s global benefit programs. We innovate and build world-class offerings and programs supporting over 1.5 million employees and their families across more than 60 countries. This role will work closely with our benefit managers, financial team, and clinical experts to build models, develop cost projections, evaluate program offerings and inform key benefit decisions in the US and internationally. We are looking for a motivated self-starter that can work independently in a fast paced, ambiguous environment. You’ll help us analyze large amounts of data, discover and solve real world problems and build metrics and models around benefit programs. Key job responsibilities - Support modeling and cost projections for US and International benefits. - Serve as a subject-matter expert on insurance renewals, healthcare trends, claims analysis, and industry benchmarks. - Implement metrics and processes to track and measure healthcare quality. - Design reports and dashboards to support tracking experience, outliers, and surfacing insights across healthcare cost, quality, and utilization. - Detect, research, and propose strategies to address gaps and anomalies. - Translate technical and financial results for a non-technical audience. - Design and implement program evaluations for vendor solutions and benefit programs. - Develop models and pricing analysis for medical outlier claims. - Review and recommend plan designs, plan offering strategies, and pricing for benefits. A day in the life Our primary focus is to ensure our stakeholders are enabled to effectively manage our benefit programs around the world. We provide actuarial and financial modeling support for medical, pharmacy, dental, vision, and behavioral health programs. We partner closely with finance, our economist team, benefit managers, business leaders, and clinical specialists to uncover actuarial insights. On any given day, we could be working on the following: - Collaborating with benefit managers to identify cost drivers and recommend changes. - Helping business leaders compare strategic benefit decisions. - Working with clinical specialists to evaluate the impact of new programs. - Establishing data pipelines for new and existing data. - Periodic travel required. - Some early mornings or late evenings to sync with international teams. About the team The Health and Wellness Team within Amazon Global Benefits ensures that our employees and their families have access to high quality, affordable, and frustration-free care by offering world class healthcare programs and services. We are striving to be Earth’s Best Employer, and are hiring for several new roles to help us build innovative solutions to meet the needs of our large and diverse employee population. This role contributes to these efforts, and collaborates with many internal and external leaders and teams.

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 ML 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 team for India Consumer Businesses. Machine Learning, Big Data and related quantitative sciences have been strategic to Amazon from the early years. Amazon has been a pioneer in areas such as recommendation engines, ecommerce fraud detection and large-scale optimization of fulfillment center operations. As Amazon has rapidly grown and diversified, the opportunity for applying machine learning has exploded. We have a very broad collection of practical problems where machine learning systems can dramatically improve the customer experience, reduce cost, and drive speed and automation. These include product bundle recommendations for millions of products, safeguarding financial transactions across by building the risk models, improving catalog quality via extracting product attribute values from structured/unstructured data for millions of products, enhancing address quality by powering customer suggestions We are developing state-of-the-art machine learning solutions to accelerate the Amazon India growth story. Amazon India is an exciting place to be at for a machine learning practitioner. We have the eagerness of a fresh startup to absorb machine learning solutions, and the scale of a mature firm to help support their development at the same time. As part of the India Machine Learning team, you will get to work alongside brilliant minds motivated to solve real-world machine learning problems that make a difference to millions of our customers. We encourage thought leadership and blue ocean thinking in ML. Key job 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, develop, evaluate and deploy, innovative and highly scalable ML models Work closely with software engineering teams to drive real-time model implementations Work closely with business partners to identify problems and propose machine learning solutions Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model maintenance Work proactively with engineering teams and product managers to evangelize new algorithms and drive the implementation of large-scale complex ML models in production Leading projects and mentoring other scientists, engineers in the use of ML techniques About the team International Machine Learning Team is responsible for building novel ML solutions that attack India first (and other Emerging Markets across MENA and LatAm) problems and impact the bottom-line and top-line of India business. Learn more about our team from https://www.amazon.science/working-at-amazon/how-rajeev-rastogis-machine-learning-team-in-india-develops-innovations-for-customers-worldwide

Have you ever wondered how Amazon delivers timely and reliably hundreds of millions of packages to customer’s doorsteps? Are you passionate about data and mathematics, and hope to impact the experience of millions of customers? Are you obsessed with designing simple algorithmic solutions to very challenging problems? If so, we look forward to hearing from you! Amazon Transportation Services is seeking a Applied Scientist to be based in the EU Headquarters in Luxembourg. As a key member of the Research Science Team of ATS operations, this person will be responsible for designing algorithmic solutions based on data and mathematics for optimizing the middle-mile Amazon Transportation Network. The successful applicant will ensure that our end-to-end strategies in terms of customer demand fulfillment, routing, consolidation locations, linehaul/airhaul/sea options and last-mile transportation are streamlined and optimized. Key job responsibilities This critical role requires an aptitude for independent initiative and decision-making, the ability to drive innovation in Transportation modelling and optimization across Amazon’s expanding European network and linking into global initiatives and expansion strategies. - Design and prototype algorithmic solutions for standardized processes. - Lead complex time-bound, long-term as well as ad-hoc transportation modelling analyses to help management in decision making. - Communicate to leadership results from business analysis, strategies and tactics (for senior candidates). - Drive large-scale projects to scale and enhance Amazon’s EU transportation network (for senior candidates). - Partner with the planning, linehaul/airhaul and sort center operations teams, while working closely with last-mile, supply chain, and global delivery departments for modeling and optimizing the transportation network of EU. About the team We are a global science and tech team for developing cutting-edge optimization models for Amazon's middle mile network. We are owning the entire lifecycle of tech products from idea to production-use and deploy our tools on a worldwide basis. Our team is composed of a wide variety of tech roles including scientists, data engineers and business intelligence engineers.

Customer Experience and Business Trends (CXBT) is looking for an Applied Scientist to join their team. CXBT's 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 leverage advanced architectures, cross-modal learning, interpretability, and responsible AI techniques to provide coherent, context-aware responses augmented by real-time knowledge retrieval. Ideal candidate will have expertise in Large Language Models (LLMs), speech, audio, Natural Language processing (NLP) or multimodal learning to pioneer innovations in data simulation, representation, generation, reasoning, retrieval, and evaluation. Key job responsibilities - Build scalable solutions for real-time conversational experiences, including: Multilingual support, Customizable personalities, Conversational turn-taking. - Develop data simulation approaches that mimic real-world speech interactions. - Research and implement novel algorithms and modeling techniques. - Acquire and curate diverse datasets while ensuring user privacy. - Create robust evaluation metrics and test sets to assess language model performance. - Integrate human feedback to improve data selection and model performance. - Innovate in data representation and model training techniques. - Apply responsible AI practices throughout the development process. A day in the life Our team is dedicated to improving Amazon’s products and services through evaluation of the end-to-end customer experience using both internal and external processes and technology. Our mission is to deeply understand our customer’s experience, challenge the status quo, and provide insights that drive innovation to improve that experience. Through our analysis and our insights, we inform business decisions that directly impact customer experience as customers of new GenAI and LLM technologies. About the team Customer Experience and Business Trends (CXBT) is an organization made up of a diverse suite of functions dedicated to deeply understand and improve customer experience, globally. We are a team of builders that develop products, services, ideas, and various ways of leveraging data to influence product and service offerings - for almost every business at Amazon - for every customer (e.g., consumers, developers, sellers/brands, employees, investors, streamers, gamers). Our approach is based on determining the customer need, along with problem solving, and we work backwards from there. We use technical and non-technical approaches and stay aware of industry and business trends. We are a global team made up of diverse set of profiles, skills, and backgrounds - including: Product Managers, Software Developers, Computer Vision experts, Solutions Architects, Data Scientists, Business Intelligence Engineers, Business Analysts, Risk Managers, and more.

Amazon Music is an immersive audio entertainment service that deepens connections between fans, artists, and creators. From personalized music playlists to exclusive podcasts, concert livestreams to artist merch, Amazon Music is innovating at some of the most exciting intersections of music and culture. We offer experiences that serve all listeners with our different tiers of service: Prime members get access to all the music in shuffle mode, and top ad-free podcasts, included with their membership; customers can upgrade to Amazon Music Unlimited for unlimited, on-demand access to 100 million songs, including millions in HD, Ultra HD, and spatial audio; and anyone can listen for free by downloading the Amazon Music app or via Alexa-enabled devices. Join us for the opportunity to influence how Amazon Music engages fans, artists, and creators on a global scale. Imagine shaping how millions of customers discover and engage with digital music and audio, leveraging the resources of a Fortune-500 company within the atmosphere of a start-up. Love collaborating with a wide range of internal and external partners to drive successful partnerships? If so, come and build the future of music and audio with us. Transform how people enjoy music, audiobooks & podcasts with personalized recommendations as our Applied Scientist in Berlin. Lead the design, development & deployment of data-driven models that recommend the right content at the right time based on customer context & behavior. Leverage audio data, metadata & listening patterns to create innovative features that personalize the Amazon Music experience. Collaborate with engineers and business teams to ensure coherent personalization across Amazon Music, from conception to productionization. You will make listening magical again through the power of personalization! Please note, PhD, or a Master's degree and experience in CS, CE, ML or related field, or equivalent work experience, is required for the role Key job responsibilities * Create Innovative ML Solutions for Customized Musical Joy You will architect novel machine learning solutions that delight customers with personalized music experiences tailored just for them. Through A/B testing and online experiments done hand-in-hand with engineering teams, you'll implement and validate your ideas and solutions. * Chart the Course to Musical Discovery As a leader in Amazon Music's personalization mission, you'll set the strategy for your team's personalization science and recommender systems. You'll scout out new directions to guide Amazon Music's quest to match each customer with their perfect playlists. * Publish Pioneering Research You'll produce innovative research on recommender systems that shapes the field and meets the high standards of peer-reviewed publications. You'll cement your team's reputation as thought leaders pioneering new recommenders. A day in the life Lead innovation in ML to shape Amazon Music experiences for millions. Collaborate with talented engineers and scientists to guide research and build scalable models across our audio portfolio - music, podcasts, live streaming, and more. Drive experiments and rapid prototyping, leveraging Amazon's data at scale. Innovate daily alongside world-class teams to delight customers worldwide through personalization. About the team Bring music to life through machine learning! Our Berlin teams breathe passion into Amazon Music, optimizing each recommendation for our customers' unique tastes. Scale your work across our music apps, web player and Alexa devices, fine-tuning the algorithms behind our popular recommendation and personalization features. Collaborate with leading ML experts in Seattle and San Francisco to create the future of musical engagement, one stream at a time. Help us surprise and delight tens of millions of Amazon Music fans with an ever-better listening experience. Join our mission to personalize music through forefront machine learning!