Careers

The Artificial General Intelligence (AGI) team is seeking a dedicated, skilled, and innovative Applied Scientist with a robust background in machine learning, statistics, quality assurance, auditing methodologies, and automated evaluation systems to ensure the highest standards of data quality, to build industry-leading technology with Large Language Models (LLMs) and multimodal systems. Key job responsibilities As part of the AGI team, an Applied Scientist will collaborate closely with core scientist team developing Amazon Nova models. They will lead the development of comprehensive quality strategies and auditing frameworks that safeguard the integrity of data collection workflows. This includes designing auditing strategies with detailed SOPs, quality metrics, and sampling methodologies that help Nova improve performances on benchmarks. The Applied Scientist will perform expert-level manual audits, conduct meta-audits to evaluate auditor performance, and provide targeted coaching to uplift overall quality capabilities. A critical aspect of this role involves developing and maintaining LLM-as-a-Judge systems, including designing judge architectures, creating evaluation rubrics, and building machine learning models for automated quality assessment. The Applied Scientist will also set up the configuration of data collection workflows and communicate quality feedback to stakeholders. An Applied Scientist will also have a direct impact on enhancing customer experiences through high-quality training and evaluation data that powers state-of-the-art LLM products and services. A day in the life An Applied Scientist with the AGI team will support quality solution design, conduct root cause analysis on data quality issues, research new auditing methodologies, and find innovative ways of optimizing data quality while setting examples for the team on quality assurance best practices and standards. Besides theoretical analysis and quality framework development, an Applied Scientist will also work closely with talented engineers, domain experts, and vendor teams to put quality strategies and automated judging systems into practice.

As a STRUC Economist Intern, you'll specialize in structural econometric analysis to estimate fundamental preferences and strategic effects in complex business environments. Your responsibilities include: Analyze large-scale datasets using structural econometric techniques to solve complex business challenges Applying discrete choice models and methods, including logistic regression family models (such as BLP, nested logit) and models with alternative distributional assumptions Utilizing advanced structural methods including dynamic models of customer or firm decisions over time, applied game theory (entry and exit of firms), auction models, and labor market models Building datasets and performing data analysis at scale Collaborating with economists, scientists, and business leaders to develop data-driven insights and strategic recommendations Tackling diverse challenges including pricing analysis, competition modeling, strategic behavior estimation, contract design, and marketing strategy optimization Helping business partners formalize and estimate business objectives to drive optimal decision-making and customer value Build and refine comprehensive datasets for in-depth structural economic analysis Present complex analytical findings to business leaders and stakeholders

Do you want to join an innovative team of scientists who use machine learning and statistical techniques to help Amazon provide the best customer experience by preventing eCommerce fraud? 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? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you enjoy collaborating in a diverse team environment? If yes, then you may be a great fit to join the Amazon Selling Partner Trust & Store Integrity Science Team. We are looking for a talented scientist who is passionate to build advanced machine learning systems that help manage the safety of millions of transactions every day and scale up our operation with automation. Key job responsibilities Innovate with the latest GenAI/LLM/VLM technology to build highly automated solutions for efficient risk evaluation and automated operations Design, develop and deploy end-to-end machine learning solutions in the Amazon production environment to create impactful business value Learn, explore and experiment with the latest machine learning advancements to create the best customer experience A day in the life You will be working within a dynamic, diverse, and supportive group of scientists who share your passion for innovation and excellence. You'll be working closely with business partners and engineering teams to create end-to-end scalable machine learning solutions that address real-world problems. You will build scalable, efficient, and automated processes for large-scale data analyses, model development, model validation, and model implementation. You will also be providing clear and compelling reports for your solutions and contributing to the ongoing innovation and knowledge-sharing that are central to the team's success.

Alexa+ is Amazon’s next-generation, AI-powered assistant. Building on the original Alexa, it uses generative AI to deliver a more conversational, personalized, and effective experience. The Trust CX Innovations team is looking for an Applied Scientist with strong background in Generative AI space to build solutions that help in upholding customer trust for Alexa+. A Senior Applied Scientist in Trust CX innovations, you will be at the forefront of developing innovative solutions to critical challenges in AI trust and privacy. You'll lead research in trust-preserving machine learning techniques. We are working on revolutionizing the way Amazonians work and collaborate. You will help us achieve new heights of productivity through the power of advanced generative AI technologies. We are looking for a leader with strong technical experiences a passion for building scientific driven solutions in a fast-paced environment. You should have good understanding of Artificial Intelligence (AI), Natural Language Understanding (NLU), Machine Learning (ML), Dialog Management, Automatic Speech Recognition (ASR), and Audio Signal Processing where to apply them in different business cases. You will be joining a select group of people making history producing one of the most highly rated products in Amazon's history, so if you are looking for a challenging and innovative role where you can solve important problems while growing as a leader, this may be the place for you. Key job responsibilities • Lead research initiatives in generative AI, focusing on LLMs, multimodal models, and frontier AI capabilities • Develop innovative approaches for model optimization, including prompt engineering, few-shot learning, and efficient fine-tuning • Pioneer new methods for AI safety, alignment, and responsible AI development • Design and execute sophisticated experiments to evaluate model performance and behavior • Lead the development of production-ready AI solutions that scale efficiently • Collaborate with product teams to translate research innovations into practical applications • Guide engineering teams in implementing AI models and systems at scale • Author technical papers for top-tier conferences • File patents for novel AI technologies and applications A day in the life You will be working with a group of talented scientists on researching algorithm and running experiments to test scientific proposal/solutions to improve our trust-preserving experiences. This will involve collaboration with partner teams including engineering, PMs, data annotators, and other scientists to discuss data quality, policy, and model development. You work closely with partner teams across Alexa to deliver platform features that require cross-team leadership. About the team Who We Are: Trust CX Innovations is a strategic innovation team within Amazon Devices & Services that focuses on advancing AI technology while prioritizing customer trust and experience. Our team operates at the intersection of artificial intelligence, privacy engineering and customer-centric design.

Passionate about books? The Amazon Books team is looking for a talented Applied Scientist II to help invent, design, and deliver science solutions to make it easier for millions of customers to find the next book they will love. In this role, you will - Be a part of a growing team of scientists, economists, engineers, analysts, and business partners. - Use Amazon’s large-scale computing and data resources to generate deep understandings of our customers and products. - Build highly accurate models (and/or agentic systems) to enhance the book reading & discovery experiences. - Design, implement, and deliver novel solutions to some of Amazon’s oldest problems. Key job responsibilities - Inspect science initiatives across Amazon to identify opportunities for application and scaling within book reading and discovery experiences. - Participate in team design, scoping, and prioritization discussions while mapping business goals to scientific problems and aligning business metrics with technical metrics. - Spearhead the design and implementation of new features through thorough research and collaboration with cross-functional teams. - Initiate the design, development, execution, and implementation of project components with input and guidance from team members. - Work with Software Development Engineers (SDEs) to deliver production-ready solutions that benefit customers and business operations. - Invent, refine, and develop solutions to ensure they meet customer needs and team objectives. - Demonstrate ability to use reasonable assumptions, data analysis, and customer requirements to solve complex problems. - Write secure, stable, testable, and maintainable code with minimal defects while taking full responsibility for your components. - Possess strong understanding of data structures, algorithms, model evaluation techniques, performance optimization, and trade-off analysis. - Follow engineering and scientific method best practices, including design reviews, model validation, and comprehensive testing. - Maintain current knowledge of research trends in your field and apply rigorous scrutiny to results and methodologies. A day in the life In this role, you will address complex Books customer challenges by developing innovative solutions that leverage the advancements in science. Working alongside a talented team of scientists, you will conduct research and execute experiments designed to enhance the Books reading and shopping experience. Your responsibilities will encompass close collaboration with cross-functional partner teams, including engineering, product management, and fellow scientists, to ensure optimal data quality, robust model development, and successful productionization of scientific solutions. Additionally, you will provide mentorship to other scientists, conduct reviews of their work, and contribute to the development of team roadmaps. About the team The team consists of a collaborative group of scientists, product leaders, and dedicated engineering teams. We work with multiple partner teams to leverage our systems to drive a diverse array of customer experiences, owned both by ourselves and others, that enable shoppers to easily find their perfect next read and enable delightful reading experiences that would make Kindle the best place to read.

Application deadline: Mar 28, 2026 Applied Scientists in AWS Science of Security are dedicated to making AWS the best computing service in the world for customers who require advanced and rigorous solutions for security, privacy, and sovereignty. Key job responsibilities The successful candidate will: * Solve large or significantly complex problems that require deep knowledge and understanding of your domain and scientific innovation. * Own strategic problem solving, and take the lead on the design, implementation, and delivery for solutions that have a long-term quantifiable impact. *Provide cross-organizational technical influence, increasing productivity and effectiveness by sharing your deep knowledge and experience. * Develop strategic plans to identify fundamentally new solutions for business problems. * Assist in the career development of others, actively mentoring individuals and the community on advanced technical issues. A day in the life This is a unique and rare opportunity to get in early on a fast-growing segment of AWS and help shape the technology, product and the business. You will have a chance to utilize your deep technical experience within a fast moving, start-up environment and make a large business and customer impact. About the team 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.

At Amazon Selection and Catalog Systems (ASCS), our mission is to power the online buying experience for customers worldwide so they can find, discover, and buy any product they want. We innovate on behalf of our customers to ensure uniqueness and consistency of product identity and to infer relationships between products in Amazon Catalog to drive the selection gateway for the search and browse experiences on the website. We're solving a fundamental AI challenge: establishing product identity and relationships at unprecedented scale. Using Generative AI, Visual Language Models (VLMs), and multimodal reasoning, we determine what makes each product unique and how products relate to one another across Amazon's catalog. The scale is staggering: billions of products, petabytes of multimodal data, millions of sellers, dozens of languages, and infinite product diversity—from electronics to groceries to digital content. The research challenges are immense. GenAI and VLMs hold transformative promise for catalog understanding, but we operate where traditional methods fail: ambiguous problem spaces, incomplete and noisy data, inherent uncertainty, reasoning across both images and textual data, and explaining decisions at scale. Establishing product identities and groupings requires sophisticated models that reason across text, images, and structured data—while maintaining accuracy and trust for high-stakes business decisions affecting millions of customers daily. Amazon's Item and Relationship Platform group is looking for an innovative and customer-focused applied scientist to help us make the world's best product catalog even better. In this role, you will partner with technology and business leaders to build new state-of-the-art algorithms, models, and services to infer product-to-product relationships that matter to our customers. You will pioneer advanced GenAI solutions that power next-generation agentic shopping experiences, working in a collaborative environment where you can experiment with massive data from the world's largest product catalog, tackle problems at the frontier of AI research, rapidly implement and deploy your algorithmic ideas at scale, across millions of customers. Key job responsibilities Key job responsibilities include: * Formulate open research problems at the intersection of GenAI, multimodal reasoning, and large-scale information retrieval—defining the scientific questions that transform ambiguous, real-world catalog challenges into publishable, high-impact research * Push the boundaries of VLMs, foundation models, and agentic architectures by designing novel approaches to product identity, relationship inference, and catalog understanding—where the problem complexity (billions of products, multimodal signals, inherent ambiguity) demands methods that don't yet exist * Advance the science of efficient model deployment—developing distillation, compression, and LLM/VLM serving optimization strategies that preserve frontier-level multimodal reasoning in compact, production-grade architectures while dramatically reducing latency, cost, and infrastructure footprint at billion-product scale * Make frontier models reliable—advancing uncertainty calibration, confidence estimation, and interpretability methods so that frontier-scale GenAI systems can be trusted for autonomous catalog decisions impacting millions of customers daily * Own the full research lifecycle from problem formulation through production deployment—designing rigorous experiments over petabytes of multimodal data, iterating on ideas rapidly, and seeing your research directly improve the shopping experience for hundreds of millions of customers * Shape the team's research vision by defining technical roadmaps that balance foundational scientific inquiry with measurable product impact * Mentor scientists and engineers on advanced ML techniques, experimental design, and scientific rigor—building deep organizational capability in GenAI and multimodal AI * Represent the team in the broader science community—publishing findings, delivering tech talks, and staying at the forefront of GenAI, VLM, and agentic system research

At Amazon Selection and Catalog Systems (ASCS), our mission is to power the online buying experience for customers worldwide so they can find, discover, and buy any product they want. We innovate on behalf of our customers to ensure uniqueness and consistency of product identity and to infer relationships between products in Amazon Catalog to drive the selection gateway for the search and browse experiences on the website. We're solving a fundamental AI challenge: establishing product identity and relationships at unprecedented scale. Using Generative AI, Visual Language Models (VLMs), and multimodal reasoning, we determine what makes each product unique and how products relate to one another across Amazon's catalog. The scale is staggering: billions of products, petabytes of multimodal data, millions of sellers, dozens of languages, and infinite product diversity—from electronics to groceries to digital content. The research challenges are immense. GenAI and VLMs hold transformative promise for catalog understanding, but we operate where traditional methods fail: ambiguous problem spaces, incomplete and noisy data, inherent uncertainty, reasoning across both images and textual data, and explaining decisions at scale. Establishing product identities and groupings requires sophisticated models that reason across text, images, and structured data—while maintaining accuracy and trust for high-stakes business decisions affecting millions of customers daily. Amazon's Item and Relationship Platform group is looking for an innovative and customer-focused applied scientist to help us make the world's best product catalog even better. In this role, you will partner with technology and business leaders to build new state-of-the-art algorithms, models, and services to infer product-to-product relationships that matter to our customers. You will pioneer advanced GenAI solutions that power next-generation agentic shopping experiences, working in a collaborative environment where you can experiment with massive data from the world's largest product catalog, tackle problems at the frontier of AI research, rapidly implement and deploy your algorithmic ideas at scale, across millions of customers. Key job responsibilities Key job responsibilities include: * Formulate novel research problems at the intersection of GenAI, multimodal learning, and large-scale information retrieval—translating ambiguous business challenges into tractable scientific frameworks * Design and implement leading models leveraging VLMs, foundation models, and agentic architectures to solve product identity, relationship inference, and catalog understanding at billion-product scale * Pioneer explainable AI methodologies that balance model performance with scalability requirements for production systems impacting millions of daily customer decisions * Design and execute model distillation strategies—distilling large frontier LLMs and VLMs into compact, production-grade models—that preserve multimodal reasoning capability while dramatically reducing serving latency, cost, and infrastructure footprint at billion-product catalog scale * Own end-to-end ML pipelines from research ideation to production deployment—processing petabytes of multimodal data with rigorous evaluation frameworks * Define research roadmaps aligned with business priorities, balancing foundational research with incremental product improvements * Mentor peer scientists and engineers on advanced ML techniques, experimental design, and scientific rigor—building organizational capability in GenAI and multimodal AI * Represent the team in the broader science community—publishing findings, delivering tech talks, and staying at the forefront of GenAI, VLM, and agentic system research

We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to apply their causal inference and/or structural econometrics skillsets to solve real world problems. The intern will work in the area of Economics Intelligence in Amazon Returns and Recommerce Technology and Innovation and develop new, data-driven solutions to support the most critical components of this rapidly scaling team. Our PhD Economist Internship Program offers hands-on experience in applied economics, supported by mentorship, structured feedback, and professional development. Interns work on real business and research problems, building skills that prepare them for full-time economist roles at Amazon and beyond. You will learn how to build data sets and perform applied econometric analysis 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. These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis. About the team The WWRR Economics Intelligence (RREI) team brings together Economists, Data Scientists, and Business Intelligence Engineers experts to delivers economic solutions focused on forecasting, causality, attribution, customer behavior for returns, recommerce, and sustainability domains.

Amazon Leo is an initiative to launch a constellation of Low Earth Orbit satellites that will provide low-latency, high-speed broadband connectivity to unserved and underserved communities around the world. As a Systems Engineer, this role is primarily responsible for the design, development and integration of Ka band and S/C band communication payload and ground terminal systems. The Role: Be part of the team defining the overall communication system and architecture of Amazon’s broadband wireless network. This is a unique opportunity to innovate and define groundbreaking wireless technology with few legacy constraints. The team develops and designs the communication system of Amazon Leo and analyzes its overall system level performance such as for overall throughput, latency, system availability, packet loss etc. This role in particular will be responsible for leading the effort in designing and developing advanced technology and solutions for communication system. This role will also be responsible developing advanced L1/L2 proof of concept HW/SW systems to improve the performance and reliability of the Amazon Leo network. In particular this role will be responsible for using concepts from digital signal processing, information theory, wireless communications to develop novel solutions for achieving ultra-high performance LEO network. This role will also be part of a team and develop simulation tools with particular emphasis on modeling the physical layer aspects such as advanced receiver modeling and abstraction, interference cancellation techniques, FEC abstraction models etc. This role will also play a critical role in the design, integration and verification of various HW and SW sub-systems as a part of system integration and link bring-up and verification. Export Control Requirement: Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum. Key job responsibilities • Design advanced L1/L2 algorithms and solutions for the Amazon Leo communication system, particularly Multi-User MIMO techniques. • Develop proof-of-concepts for critical communication payload components using SDR platforms consisting of FPGAs and general-purpose processors. • Work with ASIC development teams to build power/area efficient L1/L2 HW accelerators to be integrated into Amazon Leo SoCs. • Provide specifications and work with implementation teams on the development of embedded L1/L2 HW/SW architectures. • Work with multi-disciplinary teams to develop advanced solutions for time, frequency and spatial acquisition/tracking in LEO systems, particularly under large uncertainties. • Develop link-level and system-level simulators and work closely with implementation teams to evaluate expected performance and provide quick feedback on potential improvements. • Develop testbeds consisting of digital, IF and RF components while accounting for link-budgets and RF/IF line-ups. Previous experiences with VSAs/VSGs, channel emulators, antennas (particularly phased-arrays) and anechoic chamber instrumentation are a plus. • Work with development teams on system integration and debugging from PHY to network layer, including interfacing with flight computer and SDN control subsystems. • Willing to work in fast-paced environment and take ownership that goes from algorithm specification, to HW/SW architecture definition, to proof-of-concept development, to testbed bring-up, to integration into the Amazon Leo system. • Be a team player and provide support when requested while being able to unblock themselves by reaching out to RF, ASIC, SW, Comsys and Testbed supporting teams to move forward in development, testing and integration activities. • Ability to adapt design and test activities based on current HW/SW capabilities delivered by the development teams.