Careers

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. We are seeking a highly skilled and analytical Data Scientist. You will play an integral part in the measurement and optimization of Amazon Music marketing activities. You will have the opportunity to work with a rich marketing dataset together with the marketing managers. This role will focus on developing and implementing models that aids in audience segmentation, AI-enablement in data/reporting, and assessing randomized controlled trials to rate marketing effectiveness. This role is suitable for candidates with strong background in cohort analysis, causal inference, statistical analysis, and data-driven problem-solving, with the ability to translate complex data into actionable insights. As a key member of our team, you will work closely with cross-functional partners to optimize marketing strategies and drive business growth. Key job responsibilities Develop Causal & Predictive Models Build and validate causal and predictive models that quantify how marketing and lifecycle programs affect customer retention, engagement, and subscriber growth for Amazon Music. Own the team's models end to end. Statistical Analysis at Scale Analyze large customer datasets using SQL and Python or R to interpret results and uncover meaningful patterns, grounding your work in trusted, well-governed data. Enable Data-Driven Decisions Partner with marketing and finance stakeholders to deliver recommendations that improve retention and return on investment. Prioritize the work with the greatest impact on customer growth, and present findings clearly to both technical and executive audiences. Bring AI into Self-Service Tools Partner with product managers and engineers to incorporate AI and machine learning into the team's self-service analytics tools, so stakeholders can answer their own questions faster and at greater scale. Cross-Functional Problem Solving Work across marketing, product, and engineering teams to frame key business questions and build credible analytical solutions. Innovate & Document Track emerging methods and apply them to improve measurement; maintain reproducible documentation and clear reporting for non-technical audiences.

We are seeking a Sr. Applied Scientist to focus on Robot Navigation. In this role, you'll research and develop advanced navigation systems that enable robots to move reliably and safely through complex, dynamic environments. You'll work across a broad spectrum of navigation approaches—from classical methods to learning-based techniques and foundation models—to build robust solutions for autonomous robot navigation. Key job responsibilities - Develop and implement robust navigation systems that enable reliable autonomous operation in complex, dynamic indoor environments with static and dynamic obstacles - Build simulation-based and on-device evaluation frameworks with comprehensive benchmarks and metrics for systematic comparison of navigation methods - Conduct sim-to-real transfer experiments, analyzing performance gaps and developing techniques to ensure reliable real-world navigation performance - Collaborate with world model, manipulation, and other teams to ensure seamless integration of navigation capabilities into the full robot system - Stay current with the latest advances in robot navigation, spatial reasoning, and related fields, and apply relevant findings to improve system performance - Mentor fellow scientists and engineers while maintaining strong individual technical contributions About the team Fauna Robotics, an Amazon company, is building capable, safe, and genuinely delightful robots for everyday life. Our goal is simple: make robots people actually want to live and interact with in everyday human spaces. We believe that future won’t arrive until building for robotics becomes far more accessible. Today, too much effort is spent reinventing the fundamentals. We’re changing that by developing tightly integrated hardware and software systems that make it faster, safer, and more intuitive to create real-world robotic products. Our work spans the full stack: mechanical design, control systems, dynamic modeling, and intelligent software. The focus is not just functionality, but experience. We’re building robots that feel responsive, expressive, and genuinely useful. At Fauna, you’ll work at the frontier of this space, helping define how robots move, manipulate, and interact with people in natural environments. It’s an opportunity to solve hard problems across hardware and software with a team focused on making robotics accessible and joyful to build. If you care about making robotics real for everyone and building systems that are as delightful as they are capable, we’re interested in hearing from you.

Amazon's Price Perception and Evaluation team is seeking a driven Applied Scientist to harness planet scale multi-modal datasets, and navigate a continuously evolving competitor landscape, in order to build and scale an advanced self-learning scientific price estimation and product understanding system, regularly generating fresh customer-relevant prices on billions of Amazon and Third Party Seller products worldwide. The Applied Scientist will work closely with other research scientists, machine learning experts, and economists to design and run experiments, research new algorithms, and find new ways to improve Seller Pricing to optimize the Customer experience. The Scientist will partner with technology and product leaders to solve business and technology problems using scientific approaches to build new services that surprise and delight our customers. Key job responsibilities - Research and use of statistical techniques to create scalable solutions for business problems. - Design, build, and deploy effective and innovative ML solutions to provide low prices and increased selection for customers using scientifically-based methods and decision making. - Evaluate the proposed solutions via offline benchmark tests as well as online A/B tests in production. - Establish scalable, efficient, automated processes for large scale data analyses, model development, validation and implementation. - Publish and present your work at internal and external scientific venues.

As an Applied Scientist on the Science SW team, you will be a versatile generalist who collaborates closely with other scientists and engineers teams to bring research to production across a broad portfolio of problems: from computer-vision perception platforms to building-wide optimization and orchestration. This role combines the scientific application of ML and applied mathematics with a strong product focus. It will be your job to frame ambiguous business problems as tractable scientific problems, and to implement novel ML systems, first-principles models, embedded systems prototypes, and performance optimizations in both prototype and production environments. Key job responsibilities • Own the research and development of scientific and ML solutions across a broad range of problems spanning classical machine learning, statistical modeling, computer vision, optimization, and physics-informed / first-principles modeling in a production environment. • Rapidly ramp on unfamiliar problem domains, frame ambiguous or open-ended business problems as tractable scientific problems, and prototype solutions end to end. • Prototype and evaluate sensing hardware and lightweight, edge-deployable models that run on commodity compute under real-world constraints. • Collaborate across multiple science and engineering teams to integrate your solutions into our deployment architecture. About the team Amazon is building next generation software, hardware, and processes that will run our global network of fulfillment centers that move millions of units of inventory, and ensure customers get what they want when promised. The Science Software team in the One MHS organization unlocks Material Handling Equipment (MHE) innovation through a multiplicity of disciplines within Artificial Intelligence (AI) and applied science, including Computer Vision (CV), Physics-Informed Neural Networks (PINNs), Optimization, Reinforcement Learning, classical Machine Learning, statistical modeling, and sensing-hardware prototyping. Rooted in first principles aligned experimentation, the team is dedicated to building self-optimizing fulfillment centers, developing the models that drive real-time, building-wide orchestration of MHE. We conduct experiments, develop models, and apply machine learning (ML) at scale to optimize throughput, flow, merge, and congestion control, and to improve operational performance across the fulfillment network.

Are you passionate about solving unique customer-facing problems in the Amazon scale? Are you excited about utilizing statistical analysis, machine learning, data mining and leverage tons of Amazon data to learn and infer customer shopping patterns? Do you enjoy working with a diversity of engineers, machine learning scientists, product managers and user-experience designers? If so, you have found the right match! Fashion is extremely fast-moving, visual, subjective, and it presents numerous unique problem domains such as product recommendations, product discovery and evaluation. The vision for Amazon Fashion is to make Amazon the number one online shopping destination for Fashion customers by providing large selections, inspiring and accurate recommendations and customer experience. The NAS Shop and Keep (SHAKE) organization empowers customers to make confident, lasting purchase decisions by minimizing purchase anxiety and reducing returns. The NAS SHAKE science team advances this mission by innovating and developing scalable ML solutions tailored to these unique challenges. The team is hiring a Data Scientist who has a solid background in Statistical Analysis, Machine Learning, GenAI applications and Data Mining and a proven record of effectively analyzing large complex heterogeneous datasets, and is motivated to grow professionally as a Data Scientist. Key job responsibilities - You will work on our Science team and partner closely with applied scientists, data engineers as well as product managers, UX designers, and business partners to answer complex problems via data analysis. Outputs from your analysis will directly help improve the performance of the ML based recommendation systems thereby enhancing the customer experience as well as inform the roadmap for science and the product. - You can effectively analyze complex and disparate datasets collected from diverse sources to derive key insights, build segmentation models and improve customer experience by reducing retail returns. - You have excellent communication skills to be able to work with cross-functional team members to understand key questions and earn the trust of senior leaders. - You are able to multi-task between different tasks such as gap analysis of algorithm results, integrating multiple disparate datasets, doing business intelligence, analyzing engagement metrics or presenting to stakeholders. - You thrive in an agile and fast-paced environment on highly visible projects and initiatives.

Alexa International is looking for a passionate, talented, and inventive Applied Scientist to help build industry-leading technology with Large Language Models (LLMs), ASR, TTS, and Speech to Speech models, requiring strong deep learning and generative models knowledge. You will contribute to developing novel solutions and deliver high-quality results that impact Alexa's international products and services. Key job responsibilities As an Applied Scientist with the Alexa International team, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art with Large Language Models (LLMs), ASR, TTS, and Speech to Speech model. Your work will directly impact our international customers in the form of products and services that make use of digital assistant technology. You will leverage Amazon's heterogeneous data sources, unique and diverse international customer nuances and large-scale computing resources to accelerate advances in text, voice, and vision domains in a multimodal setup. The ideal candidate possesses a solid understanding of machine learning, natural language understanding, modern LLM architectures, LLM evaluation & tooling, and a passion for pushing boundaries in this vast and quickly evolving field. They thrive in fast-paced environments to tackle complex challenges, excel at swiftly delivering impactful solutions while iterating based on user feedback, and collaborate effectively with cross-functional teams. A day in the life * Analyze, understand, and model customer behavior and the customer experience based on large-scale data. * Build novel online & offline evaluation metrics and methodologies for multimodal personal digital assistants. * Drive research in ASR, TTS, and Speech-to-Speech (S2S) model training and fine-tuning * Advance multilingual speech recognition and synthesis using LLM-based architectures * Fine-tune/post-train LLMs using techniques like SFT, DPO, RLHF, and RLAIF. * Collaborate with partner teams on evaluation frameworks and post-training methodologies. * Communicate solutions clearly to partners and stakeholders. * Contribute to the scientific community through publications and community engagement.

Alexa International is looking for a passionate, talented, and inventive Applied Scientist to help build industry-leading technology with Large Language Models (LLMs), ASR, TTS, and Speech to Speech models, requiring strong deep learning and generative models knowledge. You will contribute to developing novel solutions and deliver high-quality results that impact Alexa's international products and services. Key job responsibilities As an Applied Scientist with the Alexa International team, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art with Large Language Models (LLMs), ASR, TTS, and Speech to Speech model. Your work will directly impact our international customers in the form of products and services that make use of digital assistant technology. You will leverage Amazon's heterogeneous data sources, unique and diverse international customer nuances and large-scale computing resources to accelerate advances in text, voice, and vision domains in a multimodal setup. The ideal candidate possesses a solid understanding of machine learning, natural language understanding, modern LLM architectures, LLM evaluation & tooling, and a passion for pushing boundaries in this vast and quickly evolving field. They thrive in fast-paced environments to tackle complex challenges, excel at swiftly delivering impactful solutions while iterating based on user feedback, and collaborate effectively with cross-functional teams. A day in the life * Analyze, understand, and model customer behavior and the customer experience based on large-scale data. * Build novel online & offline evaluation metrics and methodologies for multimodal personal digital assistants. * Drive research in ASR, TTS, and Speech-to-Speech (S2S) model training and fine-tuning * Advance multilingual speech recognition and synthesis using LLM-based architectures * Fine-tune/post-train LLMs using techniques like SFT, DPO, RLHF, and RLAIF. * Collaborate with partner teams on evaluation frameworks and post-training methodologies. * Communicate solutions clearly to partners and stakeholders. * Contribute to the scientific community through publications and community engagement.

Alexa International is looking for a passionate, talented, and inventive Applied Scientist to help build industry-leading technology with Large Language Models (LLMs), ASR, TTS, and Speech to Speech models, requiring strong deep learning and generative models knowledge. You will contribute to developing novel solutions and deliver high-quality results that impact Alexa's international products and services. Key job responsibilities As an Applied Scientist with the Alexa International team, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art with Large Language Models (LLMs), ASR, TTS, and Speech to Speech model. Your work will directly impact our international customers in the form of products and services that make use of digital assistant technology. You will leverage Amazon's heterogeneous data sources, unique and diverse international customer nuances and large-scale computing resources to accelerate advances in text, voice, and vision domains in a multimodal setup. The ideal candidate possesses a solid understanding of machine learning, natural language understanding, modern LLM architectures, LLM evaluation & tooling, and a passion for pushing boundaries in this vast and quickly evolving field. They thrive in fast-paced environments to tackle complex challenges, excel at swiftly delivering impactful solutions while iterating based on user feedback, and collaborate effectively with cross-functional teams. A day in the life * Analyze, understand, and model customer behavior and the customer experience based on large-scale data. * Build novel online & offline evaluation metrics and methodologies for multimodal personal digital assistants. * Drive research in ASR, TTS, and Speech-to-Speech (S2S) model training and fine-tuning * Advance multilingual speech recognition and synthesis using LLM-based architectures * Fine-tune/post-train LLMs using techniques like SFT, DPO, RLHF, and RLAIF. * Collaborate with partner teams on evaluation frameworks and post-training methodologies. * Communicate solutions clearly to partners and stakeholders. * Contribute to the scientific community through publications and community engagement.

Do you thrive in generating actionable insights at scale from complex datasets? Can you use data to look around the corners of a business and guide leaders on impactful business decisions? The Shop and Keep Data and Science team builds internet-scale shopping intelligence that helps Amazon customers find what they want with ease and give them the right information to make confident and lasting purchases. Our work powers customer experiences across Amazon.com surfaces, including Search, Product Detail Pages, Recommendations and Ads. We are looking for an experienced Senior Data Scientist to lead high visibility science initiatives that guide the business and ensure quality of our shopping intelligence signals. This role will focus on Data Science and Analytics related to signal quality evaluation, impact measurement, and delivering business insights. The role requires deep technical skills, strong business acumen and a deep analytical background to provide actionable data-driven insights and decision support. As a member of this team, the role will dive deep into our data and leverage their strong skills in measurement science, LLMs, predictive and prescriptive models, data ETLs, dashboards and visualization to support business strategy and deliver goals with executive visibility. You must have the ability to communicate effectively across multiple technical and non-technical business units, as well as across other geographies. Successful members of this team collaborate effectively to solve data problems, are highly organized and detail-oriented, implement new solutions for complex problems, and deliver successfully against highest standards. The ideal candidate will be a highly motivated individual that seeks to “tell the story” of the data with little direction or supervision. Key job responsibilities • Leverage state-of-the-art measurement science approaches, including LLMs, to develop evaluation frameworks for a variety of signals and customer experiences. • Support the development of continuously-evolving business analytics and data models, own the quantitative analysis of the performance of our features. • Continually develop new ways of using data to look around the corners and guide the development of shopping intelligence signals. • Use LLMs, machine learning, data mining, and statistical techniques to design/run experiments that solve complex business problems. • Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation. • Develop a deep understanding of e-commerce metrics, reporting tools, and data structures in order to identify and drive resolution of issues, provide actionable intelligence with existing metrics or identify, develop, and propose new metrics, dashboards, scorecards or new tools. • Develop relationships and processes with partner teams, PMs/TPMs, engineers, and other functional teams to identify and address reporting issues. • Manage and develop advanced analytical tools that align, and simplify, monthly business reviews, annual planning, operations and forecasting processes, based on the needs of the business and stakeholders. About the team The Shop and Keep Data and Science team's mission is to build shopping intelligence that helps Amazon customers find what they want with ease and give them the right information to make confident and lasting purchases. Through our personalized discovery and product evaluation signals, we assist customers in their shopping missions as they navigate Amazon.com's surfaces. We also share a selection of signals with partner teams and sellers to establish closed loop mechanisms and drive improvements in our signals, customer outcomes and Amazon’s product selection.

We are seeking a Data Scientist to join our analytics team. This person will own the design and implementation of scalable and reliable approaches to support or automate decision making throughout the business. You will do this by analyzing data with a variety of statistical techniques and then building, validating, and implementing models based your analysis. You will not be able to do this alone but by building partnerships across data, engineering, and business teams. Key job responsibilities Apply a range of data science techniques and tools combined with subject matter expertise to solve difficult customer or business problems and cases in which the solution approach is unclear. Proactively seek to identify business opportunities and insights and provide solutions to automate and optimize key internal and external products based on a broad and deep knowledge of Amazon data, industry best-practices, and work done by other teams. Dive deep into the data and other models across the business to identify defects or inefficiencies which materially impact the customer or business, but can be mitigated through corrective actions for the AB Ops use case Acquire this data by accessing data sources and building the necessary SQL/ETL queries or scripts. Analyze data for trends and input validity by inspecting univariate distributions, exploring bivariate relationships, constructing appropriate transformations, and tracking down the source and meaning of anomalies. Build models and automated tools using statistical modeling, mathematical modeling, econometric modeling, network modeling, social network modeling, natural language processing, machine learning algorithms, genetic algorithms, and neural networks. Validate these models against alternative approaches, expected and observed outcome, and other business defined key performance indicators. Implement these models in a manner which complies with evaluations of the computational demands, accuracy, and reliability of the relevant ETL processes at various stages of production. Enable product engineering teams to consume your models through services which can directly power customer-facing experiences. Inspect the key business metrics/KPIs (even if you did not create them) when your analytics work points to potential gaps or opportunities; providing clear, compelling analyses by leveraging your knowledge across the AWS suite of products to support the broader business. About the team Amazon Business (AB) launched in the United States in April 2015 with the vision of delivering a comprehensive procurement solution for business customers of all sizes. In the US, AB now serves Fortune 500 companies, hospital systems, local governments, and education organizations. To support AB's mission, the AB Operations team owns end to end customer experience for AB customers right from checkout to final mile delivery and sits under the broader Global Transportation Services (GTS). We are the Single Threaded WW Ops team driving B2B operations, developing products and programs unique to business customers, and enhancing the core Amazon delivery capabilities for commercial addresses. While Amazon has built its core operations over the last two decades mostly catered towards the end-consumer, we recognize that the business customers have unique needs and require a different set of features and services from their e-Commerce provider.