Careers

Amazon.com’s Product Detail Page team is looking for talented, motivated and passionate applied scientist to be part of the design and development of a highly scalable multi-tiered shopping application to provide the best possible online shopping experience for Amazon customers world-wide. Our team is comprised of talented applied scientists, developers, testers, program managers, designers and product managers tasked with the singular goal to create THE world's best buying experience. Scientists on this team develop the next-generation technologies and experiences that change how millions interact and shop online. To provide the best possible online shopping at the scale of the web requires ideas from every area of computer science, including distributed computing, large-scale system design, machine learning, natural language processing, data compression and user interface design; the list goes on and is growing every day. We need our scientists to be versatile and always eager to tackle new problems as we continue to push technology forward. Our team leverages sophisticated econometric, machine learning, and big data technologies to help customers to discover the right products at the right prices from millions of trusted sellers billions of times a day. If you are looking for a career-defining opportunity on one of the most customer centric and business impacting teams within Amazon, we’d love to hear from you. We are looking for an Applied Scientist to help build the next generation of Detail Page optimization algorithms. These new set of algorithms will incorporate the continually changing preferences of our customers and continue to scale with numerous new programs that Amazon is introducing for our customers. You will work with multiple Amazon businesses and programs to identify big business opportunities and propose new business features and technical systems to improve customer experience on Amazon Detail Page, Search Page and many other widgets throughout the website. You will be responsible for the quality of algorithm design and will get the opportunity to present your ideas and share results of your deliverables with Amazon executives on a frequent basis. You will get an opportunity to work with senior scientists to define and enforce broad, company-wide technical standards in optimization techniques, statistical modeling and simulation techniques, and/or data analytics.

We're seeking a Senior Applied Scientist to pioneer sensor-based algorithms that power next-generation experiences across Amazon's device ecosystem, including Echo, Kindle, Fire TV, and Fire Tablets. Working with multidisciplinary teams of scientists and engineers, you'll develop innovative technologies at the intersection of signal processing and machine learning that transform how millions of customers interact with our products. The ideal candidate combines strong theoretical foundations in machine learning and signal processing with practical implementation skills. You'll develop state-of-the-art sensor algorithms from concept to production, translate complex research problems into practical consumer technologies, and create solutions optimized for diverse hardware platforms. We're looking for someone who thrives in fast-paced environments, solves complex problems efficiently, and iterates quickly based on real-world feedback. Your technical decisions will directly shape future product capabilities and deliver exceptional experiences to Amazon customers worldwide. Key job responsibilities - Develop and implement advanced algorithms and machine learning models to enhance Amazon's products and services. - Collaborate with cross-functional teams, including software engineers, scientists, and product managers to translate business needs into technical solutions. - Conduct thorough data analysis to identify trends, patterns, and insights that drive product innovation and improvement. - Optimize algorithms for performance, scalability, and efficiency across various Amazon platforms. - Present findings and recommendations to stakeholders, influencing product strategy and decision-making. - Stay abreast of the latest research and technological advancements in machine learning and related fields to continuously improve Amazon's offerings. - Mentor and guide junior scientists and engineers, fostering a culture of learning and innovation. - Ensure the ethical use of data and algorithms, adhering to Amazon's guidelines and best practices. - Contribute to the publication of research findings in conferences and journals, elevating Amazon's reputation in the scientific community. About the team At Amazon Lab126, we're a pioneering research and development hub dedicated to designing and engineering revolutionary consumer electronics. Established in 2004 as a subsidiary of Amazon.com, Inc., we've been at the forefront of innovation, starting with the creation of the best-selling Kindle family of products. Our portfolio has since expanded to include transformative devices such as Fire tablets, Fire TV, and Amazon Echo. Our Lab126 team is dedicated to developing advanced sensing technologies and algorithms, collaborating with program managers to design and implement transformative user features and experiences.

We are seeking Data Scientist II with strong science application skills to join our Device Economics team. This role will focus primarily on Amazon's innovative devices and services (e.g. Echo Family of Devices), working at the intersection of economic modeling, forecasting science, and business strategy. The ideal candidate will be responsible for pre-launch forecasts, annualized overall forecasts, identifying substitution patterns, and partnering closely with product managers and marketing managers to understand the evolution of the Devices portfolio. Key job responsibilities Forecasting & Modeling 1. Develop and maintain pre-launch forecasts and annualized overall forecasts for Amazon Devices 2. Identify and model substitution patterns across the device portfolio 3. Build economic and financial models to support demand planning and business decisions 4. Formulate relevant analytical frameworks to address key economic issues in device forecasting Science Communication & Collaboration 1. Explain complex science models and methodologies to non-technical stakeholders including product managers and marketing managers 2. Collaborate with economists, data scientists, and applied scientists across Decision Science 3. Present results of analyses to cross-functional teams and leadership 4. Build trust in science models and forecast outputs with product teams Innovation & Strategic Thinking 1. Think creatively about ways that leading-edge analytics and emerging data sources can address Devices' most pressing business challenges 2. Help internal teams leverage analytic tools to better manage innovation 3. Conduct empirical studies and perform quantitative and qualitative research 4. Identify opportunities to improve forecasting accuracy and business impact Cross-Functional Partnership 1. Work closely with product managers and marketing managers to understand portfolio evolution and business strategy 2. Support DSO leadership in quarterly business reviews and strategic planning A day in the life Your days will be split between refining and building models and working with business leaders to interpret them. You own science-based forecasts that can directly impact Amazon's bottom line on the order of multi-million dollar decisions. - You will perform model refreshes or updates to analyses as needed; and, - You will be expected to develop new techniques to process large data sets, address quantitative problems, and contribute to design of automated systems. About the team The Decision Science team within DSO (Device Supply Organization) is responsible for forecasting and demand planning initiatives across Amazon Devices. The DSO team of 300+ engineers, scientists, and PMs applies quantitative methods and data-driven approaches to replace judgment-based decisions with science-driven forecasts. Decision Science focuses on lifetime demand forecasting using econometric and machine learning models for rapid reforecasting, mix adjustments, and portfolio management for new product launches. We also inform to go/no-go investment decision for new product initiatives

Are you a passionate scientist in the computer vision area who is aspired to apply your skills to bring value to millions of customers? Here at Ring, we have a unique opportunity to innovate and see how the results of our work improve the lives of millions of people and make neighborhoods safer. As an Applied Scientist, you will work with talented peers pushing the frontier of computer vision and machine learning technology to deliver the best experience for our neighbors. This is a great opportunity for you to innovate in this space by developing highly optimized algorithms that will work at scale. This position requires experience with developing Multi-modal LLMs and/or Vision Language Models. You will collaborate with different Amazon teams to make informed decisions on the best practices in machine learning to build highly-optimized integrated hardware and software platforms. Key job responsibilities - Participate in the design, development, evaluation, deployment and updating of data-driven models for computer vision applications. - Research and implement the state-of-the-art computer vision and Vision Language models algorithms. - Collaborate with product managers and engineering teams to design and implement computer vision and machine learning based features for Ring devices - Influence system design and product vision by making informed decisions on the selection of technology, data sources, algorithms, and sensors.

RISC's vision is to make Amazon Earth’s most trusted shopping destination for safe and compliant products. We do this by protecting customers from products that are unsafe, illegal, illegally marketed, controversial or otherwise in violation of Amazon's policies while enabling our Selling Partners (SPs) to offer their broadest selection of safe and compliant products. We are seeking an exceptional Applied Scientist to join a team of experts in the field of agentic AI, GenAI, Machine Learning, Software Engineers, and work together to tackle challenging problems across diverse compliance domains. We leverage and train state-of-the-art large-language-models (LLMs), multi-modal model, mixed with elegant harness engineering and SKILL building to 1) detect illegal and unsafe products across the Amazon catalog; 2) automation safety and compliance content authoring; 3) reasoning over enforcement action to provide actionable insights to Amazon sellers. We work on machine learning problems for content generation, multi-modal classification, global product taxonomy, intent detection, information retrieval, anomaly and fraud detection, agentic AI, generative AI and multi-agent system. This is an exciting and challenging position to deliver scientific innovations into production systems at Amazon-scale to make immediate, meaningful customer impacts while also pursuing ambitious, long-term research. You will work in a highly collaborative environment where you can analyze and process large amounts of image, text, unstructured and tabular data. You will work on challenging science problems that have not been solved before, conduct rapid prototyping to validate your hypothesis, and deploy your algorithmic ideas at scale. There will be something new to learn every day as we work in an environment with rapidly evolving regulations and adversarial actors looking to outwit your best ideas. Key job responsibilities • Design and evaluate state-of-the-art algorithms and approaches in content generation, multi-modal classification, global product taxonomy, intent detection, information retrieval, anomaly and fraud detection, agentic AI, generative AI and multi-agent system. • Translate product and CX requirements into measurable science problems and metrics. • Collaborate with product and tech partners and customers to validate hypothesis, drive adoption, and increase business impact • Key author in writing high quality scientific papers in internal and external peer-reviewed conferences. A day in the life • Understanding customer problems, project timelines, and team/project mechanisms • Proposing science formulations and brainstorming ideas with team to solve business problems • Writing code, and running experiments with re-usable science libraries • Reviewing labels and audit results with investigators and operations associates • Sharing science results with science, product and tech partners and customers • Writing science papers for submission to peer-review venues, and reviewing science papers from other scientists in the team. • Contributing to team retrospectives for continuous improvements • Driving science research collaborations and attending study groups with scientists across Amazon

Have you ever ordered a product on Amazon and when that box with the smile arrived you wondered how it got to you so fast? Have you wondered where it came from and how much it cost Amazon to deliver it to you? We are looking for a Data Scientist who will be responsible to develop scientific solutions to optimize our fulfillment strategy across multiple regions of the world (EU, JP, IN and more), to maximize our Customer Experience and minimize our cost and carbon footprint. You will partner with the worldwide scientific community to help design the optimal fulfillment strategy for Amazon. You will also collaborate with technical teams to develop optimization tools for network flow planning and execution systems. Finally, you will also work with business and operational stakeholders to influence their strategy and gather inputs to solve problems. To be successful in the role, you will need deep analytical skills and a strong scientific background. The role also requires excellent communication skills, and an ability to influence across business functions at different levels. You will work in a fast-paced environment that requires you to be detail-oriented and comfortable in working with technical, business and technical teams. Key job responsibilities - Design and develop mathematical models to optimize inventory placement and product flows. - Design and develop statistical and optimization models for planning Supply Chain under uncertainty. - Manage several, high impact projects simultaneously. - Consult and collaborate with business and technical stakeholders across multiple teams to define new opportunities to optimize our Supply Chain. - Communicate data-driven insights and recommendations to diverse senior stakeholders through technical and/or business papers. - Leverage LLMs to improve explainability of our optimization solutions and drive engagement from supply chain planners across the world.

Amazon Industrial Robotics is seeking exceptional applied science talent to develop AI and machine learning systems that will enable the next generation of advanced manufacturing capabilities at unprecedented scale. We're building revolutionary software infrastructure that combines cutting-edge AI, large-scale optimization, and advanced manufacturing processes to create adaptive production control systems. As a Senior Applied Scientist, you will develop and improve machine learning systems that enable real-time manufacturing flow decisions. You will leverage state-of-the-art optimization and ML techniques, evaluate them against representative manufacturing scenarios, and adapt them to meet the robustness, reliability, and performance needs of production environments. You will invent new algorithms where gaps exist. You'll collaborate closely with software engineering, manufacturing engineering, robotics simulation, and operations teams, and your outputs will directly power the systems that determine what to build next, where to allocate resources, and how to maximize throughput. The ideal candidate brings deep expertise in optimization and machine learning, with a proven track record of delivering scientifically complex solutions into production. You are hands-on, writing significant portions of critical-path scientific code while driving your team's scientific agenda. If you're passionate about inventing the intelligent manufacturing systems of tomorrow rather than optimizing those of today, this role offers the chance to make a lasting impact on the future of automation. Key job responsibilities - Identify and devise new scientific approaches for constraint identification, dispatch optimization, WIP release control, and predictive flow intelligence when the problem is ill-defined and new methodologies need to be invented - Lead the design, implementation, and successful delivery of scientifically complex solutions for real-time manufacturing flow optimization in production - Design and build ML models and optimization algorithms including constraint prediction, starvation risk forecasting, and dispatch optimization - Write a significant portion of critical-path scientific code with solutions that are inventive, maintainable, scalable, and extensible - Execute rapid, rigorous experimentation with reproducible results, closing the gap between simulation and real manufacturing environments - Build evaluation benchmarks that measure model performance against manufacturing outcomes including constraint utilization and throughput rather than traditional ML metrics alone - Influence your team's science and business strategy through insightful contributions to roadmaps, goals, and priorities - Partner with manufacturing engineering, robotics simulation, and applied intelligence teams to ensure scientific approaches are grounded in operational reality - Drive your team's scientific agenda and role model publishing of research results at peer-reviewed venues when appropriate and not precluded by business considerations - Actively participate in hiring and mentor other scientists, improving their skills and ability to deliver - Write clear narratives and documentation describing scientific solutions and design choices

About Sponsored Products and Brands: The Sponsored Products and Brands (SPB) organization at Amazon Ads is re-imagining the advertising landscape through industry leading generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. About Our Team: The Brand Beacon team is responsible for inventing impressions offerings for brands to increase share of voice via premium experiences, helping brands get discovered, acquire new customers and sustainably grow customer lifetime value. We build end-to-end solutions that enable brands to drive discovery, visibility and share of voice. This includes building advertiser controls, shopper experiences, monetization strategies and optimization features. We succeed when (1) shoppers discover, engage and build affinity with brands and (2) brands can grow their business at scale with our advertising products. About This Role: As a Senior Scientist for the team, you will have the opportunity to apply your deep subject matter expertise in the area of ML, LLM and GenAI models. You will invent new product experiences that enable novel advertiser and shopper experiences. This role will liaise with internal Amazon partners and work on bringing state-of-the-art GenAI models to production, and stay abreast of the latest developments in the space of GenAI and identify opportunities to improve the efficiency and productivity of the team. Additionally, you will define a long-term science vision for our advertising business, driven by our customer’s needs, and translate it into actionable plans for our team of applied scientists and engineers. This role will play a critical role in elevating the team’s scientific and technical rigor, identifying and implementing best-in-class algorithms, methodologies, and infrastructure that enable rapid experimentation and scaling. You will communicate learnings to leadership and mentor and grow Applied AI talent across org. * Develop AI solutions for advertiser and shopper experiences. Build monetization and optimization systems that leverage generative models to value and improve campaign performance. * Define a long-term science vision and roadmap for our advertising business, driven from our customers' needs, translating that direction into specific plans for applied scientists and engineering teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. * Design and conduct A/B experiments to evaluate proposed solutions based on in-depth data analyses. * Effectively communicate technical and non-technical ideas with teammates and stakeholders. * Stay up-to-date with advancements and the latest modeling techniques in the field. * Think big about the arc of development of Gen AI over a multi-year horizon and identify new opportunities to apply these technologies to solve real-world problems. #GenAI

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.

Amazon's Stores-Ads Science team operates at the intersection of Amazon's Stores and advertising businesses. We develop causal measurement systems, optimization algorithms, and machine learning models that inform how advertising affects shopper engagement, driving selling partner growth and marketplace economics. Our science shapes decisions both at the strategic level and in production systems. We are a team of interdisciplinary scientists who combine causal inference, economic modeling, and machine learning to drive measurable business impact. We are looking for an Applied Science Manager to lead our Ads Impact initiative. This team owns the science of understanding and optimizing how advertising creates value for shoppers and selling partners. What makes this role distinctive is its position at the frontier of AI and Economics: as Amazon's shopping experience evolves from traditional search toward LLM-powered, agentic commerce, the fundamental mechanisms through which advertising creates value are changing. This role will partner with leading scientists and academic researchers to measure these effects through large-scale causal experimentation, and develop novel methods to encode causal and economic reasoning into AI systems that optimize the shopping experience. Key job responsibilities In this role, you will lead a team of scientists, setting the technical vision and science roadmap for ads impact measurement and optimization. You will design experiments that identify the causal mechanisms through which advertising drives shopper engagement, advertiser value, and marketplace outcomes. You will develop optimization algorithms that integrate these causal signals into production and business decision-making, in close partnership with engineering and product teams across the organization. You will lead the research and communicate findings and recommendations to senior leadership through written narratives that connect technical science to business strategy. This role requires deep expertise in causal inference and experimental design, combined with strong applied ML skills and the engineering judgment to translate research into production systems. You will hire and develop future science leaders, think strategically, set ambitious roadmaps in highly ambiguous problem spaces, and foster a culture that values both intellectual depth and production impact. You will work cross-functionally, influencing across organizational boundaries to drive alignment on complex, multi-sided tradeoffs.