Careers

The Amazon Search team creates customer-focused search solutions and technologies. Whenever a customer visits an Amazon site worldwide and types in a query or browses through product categories, Amazon Product Search services go to work. We design, develop, and deploy high performance, fault-tolerant distributed search systems used by millions of Amazon customers every day. Our Search Relevance team works to maximize the quality and effectiveness of the search experience for visitors to Amazon websites worldwide. The Search Relevance team focuses on several technical areas for improving search quality. In this role, you will invent universally applicable signals and algorithms for training machine-learned ranking models. The relevance improvements you make will help millions of customers discover the products they want from a catalog containing millions of products. You will work on problems such as predicting the popularity of new products, developing new ranking features and algorithms that capture unique characteristics, and analyzing the differences in behavior of different categories of customers. The work will span the whole development pipeline, including data analysis, prototyping, A/B testing, and creating production-level components. Joining this team, you’ll experience the benefits of working in a dynamic, entrepreneurial environment, while leveraging the resources of Amazon.com (AMZN), one of the world’s leading Internet companies. We provide a highly customer-centric, team-oriented environment in our offices located in Palo Alto, California. Please visit https://www.amazon.science for more information Key job responsibilities Your responsibilities include but not limited to: * Analyze the data and metrics resulting from traffic into Amazon's product search service. * Design, build, and deploy effective and innovative ML solutions to improve search ranking. * Evaluate the proposed solutions via offline benchmark tests as well as online A/B tests in production. * Publish and present your work at internal and external scientific venues in the fields of ML/NLP/IR.

Our team is at the forefront of machine learning research. Led by scientists including Dean Foster, the team is dedicated to developing innovative RL algorithms and applying them to complex, real-world challenges in Amazon's global inventory and supply chain network. Our focus is not just on advancing theoretical knowledge but also on implementing these insights to optimize operations and enhance customer satisfaction. We foster a collaborative environment where exploration of new ideas and tackling complex problems is encouraged. The supply chain spans a wide range of operations,managing decisions that impact billions of dollars worth of inventory. For scientists passionate about impactful research in machine learning and AI, our team offers a dynamic and fulfilling environment to make a tangible difference in the field and Amazon's operations. Key job responsibilities - Design, implement, and evaluate innovative models, agents, and software prototypes. - Collaborate with a team of experienced scientists to drive technological advancements. - Develop innovative solutions to complex business problems in collaboration with partner teams. - Contribute to Amazon's global science community through collaboration and publication of ground-breaking research. - Engage in research projects that contribute to the wider scientific community, sharing findings through publications in top-tier journals and conferences. A day in the life A day in the life As a part of our team, you will be working alongside thought leaders like Dean Foster, contributing to academic research and complex, real-world applications. Your work will directly influence Amazon's global inventory planning systems, shaping decisions that affect billions of dollars worth of inventory and a wide array of product lines. You will tackle complex inventory planning challenges using Reinforcement Learning, contributing both to the theoretical aspect of the field and its practical applications. We value innovative thinking and the ability to approach problems from new perspectives. 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: - Medical, Dental, and Vision Coverage - Maternity and Parental Leave Options - Paid Time Off (PTO) - 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!

Are you ready to build something extraordinary from the ground up? We're looking for a seasoned Applied Science Manager to establish and lead a brand-new team in Bangalore, India, within Alexa Edge AI. This is a rare greenfield opportunity to shape the future of ambient intelligence by pioneering breakthroughs in computer vision, acoustic modeling, and multimodal semantic understanding that will power hundreds of millions of Alexa-enabled devices worldwide. As an Applied Science Manager, you will architect and scale a world-class applied science team that pushes the boundaries of what's possible at the intersection of edge and cloud AI. From enabling seamless Visual ID that recognizes who's in the room, to crafting ultra-low-latency wake word detection that works flawlessly in noisy environments, to building multimodal models that build deep semantic understanding — your work will directly define how Alexa perceives, understands, and interacts with the physical world. You'll operate at the frontier of on-device ML, tackling hard constraints in compute, memory, and power while delivering experiences that feel magical to customers. If you thrive on ambiguity, love building high-performing teams from scratch, and want to ship science that touches millions of lives daily — this is your moment. Key job responsibilities Establish and grow a high-caliber applied science team from the ground up at our new Bangalore site, defining the team's charter, culture, hiring bar, and technical roadmap Recruit, mentor, and develop top-tier scientists and engineers across computer vision, speech/acoustics, and multimodal ML disciplines Foster a culture of scientific rigor, rapid experimentation, customer obsession, and operational excellence Drive R&D of privacy preserving edge solutions like Visual recognition and Acoustic Modeling (Wake Word & Audio Intelligence) optimized for edge deployment on resource-constrained hardware (custom silicon, DSPs, NPUs). Define and execute strategies for optimizing latency, privacy, accuracy, and cost while collaborating with hardware and silicon teams to co-design next-generation AI accelerators and model architectures Own the end-to-end lifecycle from research ideation through experimentation, prototyping, and production deployment at scale Establish robust benchmarking, A/B testing, and metrics frameworks to measure real-world impact Partner closely with engineering, product, and UX teams to translate scientific breakthroughs into delightful customer experiences Shape the long-term science and technology roadmap for Alexa's perceptual AI capabilities Represent the team in org-wide science reviews, patent filings, and publications at top-tier venues (NeurIPS, ICML, CVPR, ICASSP, etc.) Build strong cross-site collaboration with teams in Sunnyvale, Boston and other global locations A day in the life As an Applied Science Manager in Alexa Edge AI, you'll split your time between deep technical engagement and people leadership — reviewing experiment results, debating model architectures with your scientists, guiding on trade-offs, and connecting with cross-site partners to align on roadmap priorities and influence org-wide direction. Initially, a significant portion of your energy goes toward building the team itself: interviewing exceptional candidates, calibrating the hiring bar, coaching scientists on career growth, and shaping the culture of a brand-new site. You stay hands-on with the research landscape, refine your science roadmap, and ensure your team has clear priorities — all while context-switching fluidly between being a technical thought leader, a strategic voice in leadership forums, and a mentor to your growing team. No two days are the same — but every day, you're building a team, pushing science forward, and shipping intelligence to the edge. About the team The Alexa Edge AI team has a mission to deliver best in class, resource efficient multimodal AI models in support of various perception (vision, audio and speech) based applications for Echo Family of Devices within Amazon.

Are you passionate about solving complex classification challenges at massive scale? We are seeking a Data Science Manager to join our ASIN Classification team within WAVE (World Wide AI Enablement). In this high-impact role, you will lead a team of scientists and engineers to architect, deploy, and operationalize advanced machine learning models that drive ASIN classification across a range of compliance programs. From supervised and unsupervised ML approaches to Large Language Models and Small Language Models, you will guide your team in harnessing state-of-the-art techniques to deliver accurate, scalable classification solutions for millions of ASINs. Key job responsibilities • Lead and manage a team of Applied Scientists, Data Scientists, and Engineers, fostering a culture of innovation, scientific rigor, and operational excellence • Define the team's science roadmap and prioritize classification initiatives across compliance programs • Own end-to-end delivery of classification solutions from problem framing and data strategy through model deployment and production monitoring • Drive architecture decisions including model selection, feature engineering from product catalogs, and evaluation metric frameworks • Translate ambiguous, large-scale compliance challenges into well-scoped data science and ML workstreams • Collaborate with business teams to convert business requirements into scalable ML solutions • Establish and monitor classification metrics, model performance KPIs, and production health dashboards to ensure continuous improvement • Partner cross-functionally with Science, Engineering, Product, and Operations teams to align science investments with business priorities • Build scalable data environments and ML pipelines to support model training, evaluation, shadow testing, and production inference at scale • Mentor and develop team members through career coaching, technical guidance, and structured growth plans • Communicate complex technical concepts effectively to non-technical stakeholders and senior leadership • Drive operational rigor ensuring zero-disruption deployments, data quality standards, and robust experimentation practices • Stay current with latest research, publications, and application of techniques to production systems

The Camera and Sensors team is looking for a passionate, talented, and inventive Applied Scientist with a strong deep learning background, to help build industry-leading technology with computer vision and multimodal perception models for various Amazon devices. Key job responsibilities As an Applied Scientist with the Camera and Sensors team, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art with multimodal models with an emphasis on computer vision. Your work will directly impact our customers in the form of products and services that make use of Computer Vision technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances for Amazon devices. A day in the life An Applied Scientist with the Camera and Sensors team you will support the science solution design, run experiments, research new algorithms, and find new ways of optimizing the customer experience; while setting examples for the team on good science practice and standards. Besides theoretical analysis and innovation, an Applied Scientist will also work closely with talented engineers and scientists to put algorithms and models into practice. About the team You will work with a team of applied scientists and software engineers locally in Cambridge, along with a broader team of principle scientists, applied scientists and software engineers across multiple global teams in the devices group.

The Alexa For Shopping (formerly Rufus) Analytics team is seeking a customer-obsessed Sr Data Scientist to own and drive analytics strategy for GenAI-powered Shopping experiences. This role will partner closely with senior leaders to deliver high-quality insights that inform executive decision-making for the AI shopping assistant, Alexa for shopping. Successful candidate will demonstrate strong attention to detail, excellent written and verbal communication, and the ability to influence across organizations. In this role, you will mentor and set the bar for data science, economics, and engineering partners by establishing best practices for understanding customer behavior in AI-driven shopping experiences. You will invent and scale metrics that measure customer adoption and habituation, and build agentic, automated analytical workflows that enable fast, repeatable deep dives. This position will play a critical role in shaping product roadmap and investment decisions in a rapidly evolving GenAI space. The ideal candidate will operate effectively in ambiguous environments, exercise strong business judgment on high-impact, one-way door decisions, and continuously raise the bar for analytical rigor and operational excellence. You will work cross-functionally with product, engineering, and economics partners to deliver results for customers Key job responsibilities - Own the development of customer and shopping-mission cohorts to understand behavior with and without Alexa for shopping engagement across the end-to-end shopping journey. - Identify which query shapes and interaction patterns drive the most customer value for specific customer cohorts and shopping missions. - Build predictive models to estimate customer re-engagement and long-term adoption of Rufus based on interaction quality and downstream shopping outcomes. - Invent, operationalize, and publish scalable metrics and dashboards that surface actionable insights, enabling data-driven product growth and executive decision-making. - Partner closely with Product, Engineering, and Economics teams to translate analytical insights into roadmap priorities and customer-focused improvements. About the team The Alexa for shopping Analytics team focuses on understanding how GenAI-powered shopping tools are transforming customer behavior across the shopping lifecycle - from inspiration and problem-solving, to product research, selection, purchase, and post-purchase support. We build the foundational measurement frameworks that enable teams to evaluate performance, identify what AI experiences resonate most with customers, and uncover opportunities for improvement. Our work directly influences customer-centric product roadmap decisions and helps scale impactful, high-quality AI shopping experiences

Amazon is looking for a passionate, talented, and inventive Applied Scientists with machine learning background to help build industry-leading Speech and Language technology. Our mission is to provide a delightful experience to Amazon’s customers by pushing the envelope in Automatic Speech Recognition (ASR), Natural Language Understanding (NLU), Machine Learning (ML) and Computer Vision (CV). Key job responsibilities Amazon is looking for a passionate, talented, and inventive Applied Scientists with machine learning background to help build industry-leading Speech and Language technology. Our mission is to provide a delightful experience to Amazon’s customers by pushing the envelope in Automatic Speech Recognition (ASR), Natural Language Understanding (NLU), Machine Learning (ML) and Computer Vision (CV). As part of our AI 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 human language technology. Your work will directly impact millions of our customers in the form of products and services that make use of speech and language technology. You will gain hands on experience with Amazon’s heterogeneous speech, text, and structured data sources, and large-scale computing resources to accelerate advances in spoken language understanding. We are hiring in all areas of human language technology: ASR, MT, NLU, text-to-speech (TTS), and Dialog Management, in addition to Computer Vision. We are also looking for talents with experiences/expertise in building large-scale, high-performing systems. A day in the life 0

Join Amazon's Last Mile Technology Revolution! Are you ready to reshape the future of logistics? Join us in transforming how millions of packages reach their final destination through state-of-the-art technology and innovation! The Last Mile Technology organization is pioneering advanced solutions that are revolutionizing Amazon Logistics (AMZL). Our mission is to create intelligent, efficient, and scalable systems that will transform the delivery experience. We're building the future of last-mile logistics while maintaining Amazon's highest standards for safety and reliability. The Last Mile challenge is a fascinating blend of real-world complexity and technological innovation. We're tackling multidimensional problems that involve enabling AI agents to perceive and navigate complex delivery environments, understanding dynamic scenes through visual data, and adapting to everything from unexpected obstacles to varying weather and lighting conditions – all while ensuring every package arrives safely as per our promise. As an Applied Scientist on our Last Mile Technology team, you'll be at the forefront of developing computer vision and perception systems that enable us to understand and interact with the physical world. You'll design and implement deep learning models for visual perception, build algorithms that enable decision-making, and create robust systems that allow AI agents to operate safely across diverse geographical areas. Your research must excel in environments ranging from dense urban centers to suburban neighborhoods, each presenting unique visual and navigational challenges that require innovative solutions in perception and control. What Makes This Role Exciting: Real-World Impact: Your computer vision models and control algorithms will power AI agents that deliver millions of packages to customers, making their lives better every day Scale That Matters: Develop perception systems that operate across thousands of delivery agents in different cities, weather conditions, lighting scenarios, and dynamic environments Innovation at Scale: Publish novel research and create entirely new approaches to visual perception, scene understanding, and control systems End-to-End Science: Work on complete solutions from object detection and tracking to path planning and control, from sim-to-real transfer to real-world deployment and continuous learning from agent experiences

The Alexa For Shopping (formerly Rufus) Analytics team is seeking a customer-obsessed Sr Data Scientist to own and drive analytics strategy for GenAI-powered Shopping experiences. This role will partner closely with senior leaders to deliver high-quality insights that inform executive decision-making for the AI shopping assistant, Alexa for shopping. Successful candidate will demonstrate strong attention to detail, excellent written and verbal communication, and the ability to influence across organizations. In this role, you will mentor and set the bar for data science, economics, and engineering partners by establishing best practices for understanding customer behavior in AI-driven shopping experiences. You will invent and scale metrics that measure customer adoption and habituation, and build agentic, automated analytical workflows that enable fast, repeatable deep dives. This position will play a critical role in shaping product roadmap and investment decisions in a rapidly evolving GenAI space. The ideal candidate will operate effectively in ambiguous environments, exercise strong business judgment on high-impact, one-way door decisions, and continuously raise the bar for analytical rigor and operational excellence. You will work cross-functionally with product, engineering, and economics partners to deliver results for customers Key job responsibilities Own the development of customer and shopping-mission cohorts to understand behavior with and without Alexa for shopping engagement across the end-to-end shopping journey. Identify which query shapes and interaction patterns drive the most customer value for specific customer cohorts and shopping missions. Build predictive models to estimate customer re-engagement and long-term adoption of Rufus based on interaction quality and downstream shopping outcomes. Invent, operationalize, and publish scalable metrics and dashboards that surface actionable insights, enabling data-driven product growth and executive decision-making. Partner closely with Product, Engineering, and Economics teams to translate analytical insights into roadmap priorities and customer-focused improvements. About the team The Alexa for shopping Analytics team focuses on understanding how GenAI-powered shopping tools are transforming customer behavior across the shopping lifecycle - from inspiration and problem-solving, to product research, selection, purchase, and post-purchase support. We build the foundational measurement frameworks that enable teams to evaluate performance, identify what AI experiences resonate most with customers, and uncover opportunities for improvement. Our work directly influences customer-centric product roadmap decisions and helps scale impactful, high-quality AI shopping experiences

Amazon's Selling Partner Support handles tens of millions of contacts annually worldwide. The Titans Science team is transforming this experience by building AI agents that autonomously resolve seller issues, learn from every interaction, and continuously improve with minimal human intervention. These agents reason, remember, and adapt — from understanding the seller's context and selecting the right solution, to routing contacts optimally, automating resolution end-to-end, and augmenting associates with AI when human judgment is needed. We do this in deep partnership with multiple engineering and product partners. We are looking for a Senior Applied Scientist who wants to work at the intersection of reinforcement learning, agentic architectures, and large-scale production systems. You will be directly connected to the problems sellers face every day, translating real customer pain into science solutions that operate at massive scale. You will frame ambiguous business challenges as tractable ML problems to shipping systems that measurably improve millions of seller interactions. Key job responsibilities - Own end-to-end research and development of RL-based agent improvement systems — from problem formulation through production deployment and impact measurement. - Design novel approaches to preference learning, reward modeling, and policy optimization in the context of conversational agents operating over real-world tools and APIs. - Build and maintain evaluation frameworks that measure agent quality across multiple dimensions: helpfulness, correctness, safety, and alignment with operational standards. - Collaborate with a team of scientists that work on forefront of Natural Language Understanding, Optimization, Machine Learning and Statistics - Partner with 10+ engineering teams to deploy models into production systems serving sellers worldwide. - Publish research at top venues (NeurIPS, ICML, EMNLP, AMLC) — the complexity of our problems produces publishable work, and we actively support it. - Raise the scientific bar through rigorous peer review, mentorship of junior scientists, and contribution to hiring. A day in the life You read the latest research papers and implement novel techniques by building rapid prototypes using AI-assisted coding tools, then taking what works from prototype to production. You collaborate closely with product managers and engineering teams to translate seller pain points into deployed science solutions. You influence leadership by bringing the state of the art to strategic decisions about where the organization invests, and you drive the science roadmap for your domain — identifying new research directions, proposing experiments, and making the case for what to build next. You mentor other scientists on the team, raising the bar on rigor and execution and get mentored by Principals across the org. Finally, you attend meetings with other Amazonians to stay connected to the seller experience by understanding the real problems sellers face so your models solve what actually matters. About the team Titans Science is a growing team of scientists building the AI that powers Amazon's seller support experience. We operate in across capabilities such as Agentic Systems, Knowledge Retrieval & Query Understanding, and Content Intelligence & Automation, each owning distinct problem spaces but sharing evaluation infrastructure and research insights. We work backwards from business problems, deeply understanding the problem space and domain, defining gold-standard datasets, success metrics, and guardrails. This lets us run parallel experiments, compare approaches rigorously, and ship the best Science models to production. We publish at internal conferences and external venues, and we actively invest in research that compounds over multiple product cycles. The team sits in Seattle and operates with high autonomy. Scientists own their domains end-to-end, from problem framing through production deployment. We value speed over perfection, scientific rigor over polish, and experimentation over debate. We value diverse experiences. Even if you do not meet all of the preferred qualifications listed above, we encourage you to apply. The team fosters an inclusive learning culture where individual growth is a priority — you will find mentorship, knowledge-sharing, and career-advancing resources here.