Careers

Do you want to leverage your expertise in translating innovative science into impactful products to improve the lives and work of over a million people worldwide? If so, People eXperience Technology Central Science (PXTCS) would love to discuss how you can make that a reality. PXTCS is an interdisciplinary team that uses economics, behavioral science, statistics, and machine learning to identify products, mechanisms, and process improvements that enhance Amazonians' well-being and their ability to deliver value for Amazon's customers. We collaborate with HR teams across Amazon to make Amazon PXT the most scientific human resources organization in the world. In this role, you will spearhead science design and technical implementation innovations across our predictive modeling and forecasting work-streams. You'll enhance existing models and create new ones, empowering leaders throughout Amazon to make data-driven business decisions. You'll collaborate with scientists and engineers to deliver solutions while working closely with business stakeholders to address their specific needs. Your work will span various business domains (corporate, operations, safety) and analysis levels (individual, group, organizational), utilizing a range of modeling approaches (linear, tree-based, deep neural networks, and LLM-based). You'll develop end-to-end ML solutions from problem formulation to deployment, maintaining high scientific standards and technical excellence throughout the process. As a Sr. Applied Scientist, you'll also contribute to the team's science strategy, keeping pace with emerging AI/ML trends. You'll mentor junior scientists, fostering their growth by identifying high-impact opportunities. Your guidance will span different analysis levels and modeling approaches, enabling stakeholders to make informed, strategic decisions. If you excel at building advanced scientific solutions and are passionate about developing technologies that drive organizational change in the AI era, join us as we work hard, have fun, and make history.

The Perfect Order Experience (POE) AI team combines artificial intelligence, machine learning, and economic insights to ensure exceptional customer experiences and seller success on Amazon. We develop advanced scientific solutions that protect product authenticity, maintain quality standards, and safeguard intellectual property across Amazon's vast catalog. Our work spans from building detection systems using state-of-the-art Large Language Models to creating automated investigation processes and risk treatment mechanisms. Our solutions directly impact billions of customer interactions and enable millions of sellers to thrive while maintaining the highest standards of trust and quality. We are seeking an exceptional Senior Applied Science Manager to lead key AI initiatives to ensure a perfect order experience for Amazon customers. In this role, you will spearhead the development of a domain specific large language model designed to comprehend complex seller behaviors and relationships. You will lead the research and implementation on LLM pre-training, fine-tuning and reinforcement learning for LLM reasoning. You will implement and influence ranker models that intelligently adjust product visibility based on risk signals and trust metrics. Key job responsibilities - Drive AI strategy and lead a team of applied scientists in developing ML solutions. - Lead the end-to-end development of a domain specific LLM. - Drive the development of large-scale pre-training and post-training strategies for the LLM using domain-specific datasets. - Architect automated risk detection and treatment systems that combine multi-modal signals to identify product quality issues and implement optimization-based mitigation strategies. - Collaborate with other science teams to develop/ influence ranker models that optimize product visibility.

The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Senior Applied Scientist with a strong deep learning background, to build Generative Artificial Intelligence (GenAI) technology with Large Language Models (LLMs) and multimodal systems. Key job responsibilities As a Senior Applied Scientist with the AGI team, you will work with talented peers to lead the development of GenAI algorithms and modeling techniques, to advance the state of the art with LLMs. Your work will directly impact our customers in the form of products and services that make use of speech and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in GenAI. About the team The AGI team has a mission to push the envelope with GenAI in LLMs and multimodal systems, in order to provide the best-possible experience for our customers.

The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive 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. Key job responsibilities Join us to work as an integral part of a team that has 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 - Learning objectives and reinforcement learning methods - Distributed training methods and solutions - AI-assisted research About the team The AGI team has a mission to push the envelope in GenAI with Large Language Models (LLMs) and multimodal systems, in order to provide the best-possible experience for our customers.

The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Applied Scientist with a strong deep learning background, to build industry-leading Generative Artificial Intelligence (GenAI) technology with Large Language Models (LLMs) and multimodal systems. Key job responsibilities As an Applied Scientist with the AGI team, you will work with talented peers to lead the development of algorithms and modeling techniques, to advance the state of the art with LLMs. Your work will directly impact our customers in the form of products and services that make use of GenAI technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in LLMs. About the team The AGI team has a mission to push the envelope in GenAI with LLMs and multimodal systems, in order to provide the best-possible experience for our customers.

Project Kuiper is Amazon’s low Earth orbit satellite broadband network. Its mission is to deliver fast, reliable internet to customers and communities around the world, and we’ve designed the system with the capacity, flexibility, and performance to serve a wide range of customers, from individual households to schools, hospitals, businesses, government agencies, and other organizations operating in locations without reliable connectivity. 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. We are looking for an experienced Data Scientist to help architect state-of-the-art test infrastructure and lead the development of data models and analysis tools to represent the ground truth about satellite test results in order to facilitate important business decisions. Our team is responsible for core infrastructure and tools that will serve as the backbone of automated satellite testing operations to enable rapid scaling of manufacturing processes. Key job responsibilities - Work with engineering, software and manufacturing teams to understand drivers, impacts, and key influences on satellite performance - Lead the design, build and implementation of production models and make decisions in real time for satellite test results - Drive actions at scale to optimize test methodology and drive increases to satellite reliability - Analysis and modeling of satellite telemetry from test results in lab and on-orbit - Develop models and data pipelines for satellite telemetry - Create and manage datasets for continued pre-training and supervised fine-tuning of LLMs - Develop scalable visualizations for analysis of satellite performance A day in the life As a Project Kuiper Data Scientist you will own the architecture definition and development of data analysis tools to to aid engineering and production teams in deciding flight-worthiness of each Kuiper satellite and historical traceability tools to enable simplified discovery and interpretation of past test data. You will work with multiple engineering, software and manufacturing teams across ground and space systems, to specify requirements, define data collection, interpretation strategies, data pipelines and implement data analysis and reporting tools for Integrated Vehicle tests. Your focus will be in optimizing the analysis of test results to enable Project Kuiper production plans. About the team The Automated Vehicle Testing Team is responsible for core infrastructure and tools that will serve as the backbone of automated satellite testing operations to enable rapid scaling of manufacturing processes.

Amazon Stores is looking for exceptional Applied Scientists to join our efforts in developing generative AI solutions in marketing. In this role, you will be part of a team that designs, implements, and evaluates state-of-the-art agentic AI solutions to enhance customer experiences through intelligent, personalized interactions. Key job responsibilities * Research, develop, and deploy novel approaches using large language models (LLMs) and multi-agent AI systems * Design and implement scalable solutions for personalized recommendations and customer insights * Create innovative evaluation frameworks for complex AI systems * Collaborate with cross-functional teams to integrate AI solutions into production environments * Conduct rigorous experimentation and data analysis to improve model performance * PhD in Computer Science, Machine Learning, AI, or related field; OR Master's degree with 2+ years of relevant industry experience * Strong programming skills in Python and experience with ML frameworks (PyTorch, TensorFlow, etc.) * Experience building and deploying machine learning models in production environments * Proficiency in natural language processing techniques and applications * Strong publication record or demonstrated practical experience in machine learning * Experience working with large language models (LLMs) and prompt engineering * Knowledge of multi-agent systems and their applications * Background in recommendation systems or personalization technologies * Experience with uncertainty quantification in AI systems * Ability to design and implement automated testing frameworks for ML systems * Previous experience in AI labs or AI-focused startups * Strong communication skills and ability to translate complex technical concepts to diverse audiences * Experience with model evaluation and validation methodologies * Track record of innovation in applied machine learning

The Amazon Web Services (AWS) Center for Quantum Computing (CQC) is a multi-disciplinary team of scientists, engineers, and technicians on a mission to develop a fault-tolerant quantum computer. You will be joining a team located in Pasadena, CA that conducts materials research to improve the performance of superconducting quantum processors. We seek a Quantum Research Scientist to investigate how material defects affect qubit performance. In this role, you will combine expertise in numerical simulations and materials characterization to study materials loss mechanisms such as two-level systems, quasiparticles, vortices, etc. Key job responsibilities Provide subject matter expertise on integrated experimental and computational studies of materials defects Develop and use computational tools for large-scale simulations of disordered structures Develop and implement multi-technique materials characterization workflows for thin films and devices, with a focus on the surfaces and interfaces Identify material properties that can be a reliable proxy for the performance of superconducting resonators and qubits Communicate findings to teammates, the broader CQC team and, when appropriate, publish findings in scientific journals A day in the life At the AWS CQC, we understand that developing quantum computing technology is a marathon, not a sprint. The work/life integration within our team encourages a culture where employees work hard and also have ownership over their downtime. We are committed to the growth and development of every employee at the AWS CQC, and that includes our research scientists. You will receive management and mentorship from within the team that is geared toward career growth, and also have the opportunity to participate in Amazon's mentorship programs for scientists and engineers. Working closely with other quantum research scientists in other disciplines – like design, measurement and cryogenic hardware – will provide opportunities to dive deep into an education on quantum computing. About the team Our team contributes to the fabrication of processors and other hardware that enable quantum computing technologies. Doing that necessitates the development of materials with tailored properties for superconducting circuits. Research Scientists and Engineers on the Materials team operate deposition and characterization systems in order to develop and optimize thin film processes for use in these devices. They work alongside other Research Scientists and Engineers to help deliver the fabricated devices for quantum computing experiments.

The WW Operations IPAT team is revolutionizing Amazon's financial forecasting through TrendCast, an innovative, automated, science based top-down forecast modeling that's transforming how we predict Worldwide Operations costs. This cutting-edge approach leverages key performance indicators to generate automated, transparent forecasts with unprecedented frequency. By moving beyond traditional bottom-up planning, TrendCast empowers leadership with real-time insights, enabling swift identification of both risks and opportunities. This game-changing model not only delivers more agile and precise financial projections but also significantly reduces the workload on finance teams. By providing more frequent forecasts, this model will facilitate leadership's decision-making process, allowing for more timely and informed strategic choices. Key job responsibilities As our operational scope rapidly expands, we're seeking a Senior Data Scientist to spearhead the development of advanced analytical solutions. In this role, you will: • Drive model development and improvement through machine learning and statistical techniques, creating scalable solutions for complex business problems • Design, develop, and evaluate novel forecasting models, with a focus on large-scale operational challenges • Lead projects through the entire data science lifecycle, from problem formulation to production deployment, working with both technical and non-technical stakeholders • Implement advanced ML models, including supervised and unsupervised learning approaches, and optimization algorithms for supply chain and operational systems • Develop a deep understanding of key business metrics and KPIs, connecting them to actionable levers that inform strategic decisions • Collaborate closely with finance, product, and BIEs teams to build and deploy robust models and algorithms • Architect scalable data pipelines and work with distributed computing frameworks to handle petabyte-scale datasets The ideal candidate will have expertise in ML model development, optimization techniques, statistical analysis, and database design. Proficiency in working with large, complex datasets and visualization tools is essential. Experience with cloud computing, MLOps, and production model deployment is highly valued. Join our team as we tackle unprecedented challenges in global operations, driving data-driven decision making at scale.

The Customer Behavior Analytics team designs innovative machine learning solutions to enhance customer experiences and strengthen their relationship with Amazon. This interdisciplinary team of scientists and engineers incubates and develops disruptive solutions using state-of-the-art technology to tackle some of the most challenging scientific problems in customer behavior analysis at Amazon. To achieve this, the team utilizes methods from deep learning, large language models (LLMs), natural language models, recommendation systems, affinity models, reinforcement learning, and econometrics to drive personalized experiences throughout the customer journey. As a Customer Behavior Analytics Scientist, you will have the opportunity to make a significant business impact, delve into large-scale problems, drive measurable actions, and collaborate closely with other scientists and engineers. You will be responsible for designing and developing state-of-the-art models and working with business, marketing, and engineering teams to address key challenges in customer behavior analytics. Key responsibilities include: - Creating of innovative deep learning and generative models for recommender systems to provide personalized experiences, including fine-tuning, efficient contextualization, adapters, evaluations. - Developing innovative statistical methods to calibrate our predictions and corroborate them with data sources and behavioral signals. - Designing and implementing models that improve the overall relationship between customers and Amazon, focusing on long-term customer value and satisfaction. - Applying reinforcement learning methods in production to continuously improve and adapt customer behavior models. - Developing and deploying sophisticated incentive recommendation models to optimize customer engagement and loyalty. - Leveraging state-of-the-art AI/ML techniques to extract insights from vast amounts of customer data. In this role, you will be an analytical problem solver who enjoys exploring data, participating in problem-solving efforts, developing new frameworks, and engaging in investigations and algorithm development. You should be capable of effectively collaborating with technical teams and business stakeholders, pushing the boundaries of what is scientifically possible, and maintaining a sharp focus on measurable customer satisfaction and business impact. Your work will be crucial in shaping the future of customer behavior analytics at Amazon, driving innovation that directly impacts millions of customers worldwide. This position offers a high-visibility opportunity to contribute to solutions that are vital to improving customer satisfaction and loyalty, serving as a model for customer-centric solutions across the company.