Careers

The Fulfillment by Amazon (FBA) Science team is looking for a passionate, curious, and creative Senior Research Scientist with deep expertise in statistical modeling, machine learning, and large language models (LLMs), and a proven record of solving complex forecasting problems at scale. Our team sits at the intersection of supply chain science, seller behavior modeling, and policy analytics — building the forecasting backbone that powers FBA's shipment creation, inbound arrival planning, and inventory management. We develop science solutions that predict seller shipment creation patterns, model inbound arrival timing and quantity, and forecast inventory levels across Amazon's fulfillment network. A key challenge we tackle is understanding how seller behavior changes — driven by market dynamics, FBA policy updates, and incentive structures — and how these behavioral shifts propagate into forecasting signals. We aim to build forecasting systems that are not only accurate but also explainable and actionable for both internal stakeholders and sellers. To do so, we build and innovate science solutions at the intersection of statistical learning, machine learning, econometrics, operations research, and generative AI. As a Senior Research Scientist, you will propose and deploy solutions drawing from a range of scientific areas including time-series forecasting, causal inference, Bayesian methods, LLMs, and deep learning. This role has high visibility to senior Amazon business leaders and involves close collaboration with scientists, engineers, and product teams to integrate scientific work into production systems. Key job responsibilities - As a senior member of the FBA Science forecasting team, play an integral role in building and advancing Amazon's FBA shipment creation, inbound arrival, and inventory forecasting systems. - Research and develop statistical models, ML models, and LLM-based solutions to forecast seller shipment creation behavior, inbound arrival patterns, and downstream inventory levels across the FBA network. - Model and quantify the impact of seller behavior changes and FBA policy updates (e.g., capacity limits, fee structures, inbound placement policies) on forecasting accuracy, and develop robust forecasting approaches that adapt to these dynamics. - Build explainability frameworks for forecasting models — enabling science teams, product managers, and business stakeholders to understand model drivers, diagnose forecast errors, and trust model outputs. - Define a long-term science vision and roadmap for the forecasting team, driven fundamentally by customer and seller needs, translating those directions into specific plans for research and applied scientists, as well as engineering and product teams. - Drive and execute forecasting science projects end-to-end: from ideation, analysis, and prototyping through to development, deployment, metrics definition, and monitoring. - Review and audit modeling processes and results for other scientists, both junior and senior. - Advocate the right science solutions to business stakeholders, engineering teams, and executive-level decision makers. A day in the life In this role, you will be a technical leader in forecasting science with significant scope, impact, and high visibility. Your solutions will directly influence billions of dollars in inventory decisions, inbound logistics planning, and seller experience across Amazon's global fulfillment network. As a senior scientist on the team, you will be involved in every aspect of the process — from idea generation, business analysis, and scientific research, through to development and deployment of advanced forecasting models — giving you a real sense of ownership. From day one, you will work with experienced scientists, engineers, and product designers who are passionate about what they do. You are expected to make decisions about modeling methodology, technology choices, and explainability approaches. You will strive for simplicity and demonstrate judgment backed by mathematical rigor. You will also collaborate with the broader decision and research science community at Amazon to broaden the horizon of your work, and mentor engineers and scientists. We are seeking someone who wants to lead projects requiring innovative thinking and deep technical problem-solving skills to create production-ready forecasting solutions. The candidate will need to be entrepreneurial, wear many hats, and work in a fast-paced, high-energy, highly collaborative environment. About the team Fulfillment by Amazon (FBA) is a service that allows sellers to outsource order fulfillment to Amazon, enabling them to leverage Amazon's world-class fulfillment infrastructure to deliver on the Prime promise. FBA ships more than half of all products offered on Amazon, and our science team is at the heart of making that possible. The FBA Science forecasting team focuses on predicting seller shipment creation, inbound arrival, and inventory dynamics — providing the signals that drive capacity planning, inbound logistics, and inventory positioning across the network. We work full-stack, from foundational forecasting models to seller-facing explainability tools. Our culture is centered on rapid prototyping, rigorous experimentation, and data-driven decision-making.

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses. Amazon's advertising portfolio helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day! The ADSP Forecasting team's vision is to build the best in class forecasting products offered by any DSP to allow advertisers to forecast campaign outcomes across the full market funnel. Our goal is to empower advertisers using Amazon demand side platform to make informed decisions by providing predictions and recommendations of supply and ad-performance. Our forecasting models and analytical solutions will also help internal teams (sales, PSC, supply desk etc) to gain insights into forecasted supply, demand and ad performance to make the best business decisions. The team comprises scientists and engineers who own end-to-end projects - data collection, analysis, ideation, and prototyping, to development, metrics and monitoring. The models and services are integrated directly with Amazon's Ads eco system and the forecasts are used to drive key business decisions at the VP/SVP level. We are a team of Applied Scientists and Engineers, who are passionate about solving technical problems in the Ad Forecasting space with models using Machine Learning, Bayesian Statistics, etc. You will join a group of highly talented PhDs with diverse background to design, prototype, and implement models to deliver impact directly to customers. You will have the opportunity to present your work in science communities and to leadership As a Applied Scientist on this team, you will: - Be the technical leader in Machine Learning; lead efforts within this team and across other teams. - Perform hands-on analysis and modeling of enormous data sets to develop insights that increase traffic monetization and merchandise sales, without compromising the shopper experience. - Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity. - Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models. - Run A/B experiments, gather data, and perform statistical analysis. - Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving. - Research new and innovative machine learning approaches. Why you will love this opportunity: Amazon is investing heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate. Impact and Career Growth: You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. Team video https://youtu.be/zD_6Lzw8raE

Amazon's advertising business has grown exponentially over the past years, helping connect sellers and vendors to shoppers who may be interested in their products. Our ad products are strategically important to our Retail and Marketplace businesses driving long term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products that leverage state of the art AI technologies. The Sponsored Products and Brands team is seeking a Principal Applied Scientist to lead the development and implementation of generative AI solutions for ad allocation and ranking on Amazon search pages. This role will be instrumental in revolutionizing how we match ads with customer intent and shopping behavior. Key job responsibilities * Design and develop novel generative AI architectures for real-time ad allocation, focusing on both efficiency and effectiveness at massive scale * Lead research initiatives in applying large language models and multimodal AI to understand deep semantic relationships between ads, queries, and user behavior * Create innovative approaches to leverage GenAI for dynamic ad placement optimization while maintaining strict latency requirements * Collaborate with cross-functional teams to integrate GenAI solutions into existing advertising systems * Author research papers and technical documentation, contributing to the broader scientific community

The People eXperience and Technology Central Science (PXTCS) team uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, well-being, and the value of work to Amazonians. The Benefits Science team is looking for a senior economist to transform complex business challenges into actionable scientific insights. In this role, you will partner directly with business leaders to design and evaluate pilots, build models using large-scale data, and scale successful prototypes into company-wide policies and programs. We're looking for someone who can combine rigorous scientific thinking with practical business acumen and is passionate about using economics to improve employee experiences at scale. The ideal candidate will thrive in interdisciplinary environments, working alongside engineers, data scientists, and business leaders from diverse backgrounds. Key job responsibilities * Design and evaluate innovative research pilots that address critical business challenges * Develop sophisticated economic models using large-scale organizational data * Collaborate with engineers, data scientists, and business leaders to transform research insights into actionable strategies * Write and present comprehensive research findings to senior leadership * Scale successful prototypes into company-wide policies and programs A day in the life Work with teammates to apply economic methods to business problems. This might include identifying the appropriate research questions, writing code to implement a DID analysis or estimate a structural model, or writing and presenting a document with findings to business leaders. Our economists also collaborate with partner teams throughout the process, from understanding their challenges, to developing a research agenda that will address those challenges, to help them implement solutions. About the team Our Benefits Science team is a dynamic group of economists, data scientists, and business strategists committed to understanding human capital at scale. We use interdisciplinary approaches to solve complex workforce challenges, combining economics, behavioral science, and advanced analytics to create meaningful workplace improvements.

Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the limits. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. As an Applied Scientist on our team, you will focus on building state-of-the-art ML models for biology. Our team rewards curiosity while maintaining a laser-focus in bringing products to market. Competitive candidates are responsive, flexible, and able to succeed within an open, collaborative, entrepreneurial, startup-like environment. At the forefront of both academic and applied research in this product area, you have the opportunity to work together with a diverse and talented team of scientists, engineers, and product managers and collaborate with other teams. Key job responsibilities - Build, adapt and evaluate ML models for life sciences applications - Collaborate with a cross-functional team of ML scientists, biologists, software engineers and product managers

The Mission Build AI safety systems that protect millions of Alexa customers every day. As conversational AI evolves, you'll solve challenging problems in Responsible AI by ensuring LLMs provide safe, trustworthy responses, building AI systems that understand nuanced human values across cultures, and maintaining customer trust at scale. What You'll Build You'll pioneer breakthrough solutions in Responsible AI at Amazon's scale. Imagine training models that set new safety standards, designing automated testing systems that hunt for vulnerabilities before they surface, and certifying the systems that power millions of daily conversations. You'll create intelligent evaluation systems that judge responses with human-level insight, build models that truly understand what makes interactions safe and delightful, and craft feedback mechanisms that help Alexa+ grasp the nuances of complex customer conversations. Here's where it gets even more exciting: you'll build AI agents that act as your team's safety net—automatically detecting and fixing production issues in real-time, often before anyone notices there was a problem. Your innovations won't just improve Alexa+; they'll fundamentally shape how it learns, evolves, and earns customer trust. As Alexa+ continues to delight customers, your work ensures it becomes more trustworthy, safer, and deeply aligned with customer needs and expectations. Your work directly protects customer trust at Amazon's scale. Every innovation you create—from novel safety mechanisms to sophisticated evaluation techniques—shapes how millions of people interact with AI confidently. You're not just building products; you're defining industry standards for responsible AI. This is frontier research with immediate real-world impact. You'll tackle problems that require innovative solutions: training models that remain truthful and grounded across diverse contexts, building reward models that capture the nuanced spectrum of human values across cultures and languages, and creating automated systems that continuously discover and address potential issues before customers encounter them. You'll collaborate with world-class scientists, product managers, and engineers to transform state-of-the-art ideas into production systems serving millions. What We're Looking For * Deep expertise in state-of-the-art NLP and Large Language Models * Track record of building scalable ML systems * Passion for impactful research—where frontier science meets real-world responsibility at scale * Excitement about solving problems that will shape the future of AI Ready to work on AI safety challenges that define the industry? Join us. Key job responsibilities This is where you'll make your mark. You'll architect breakthrough Responsible AI solutions that become industry benchmarks, pioneering algorithms that eliminate false information, designing frameworks that hunt down vulnerabilities before bad actors find them, and developing models that understand human values across every culture we serve. Working with world-class engineers and scientists, you'll push the boundaries of model training—transforming bold research into production systems that protect millions of customers daily while withstanding attacks and delivering exceptional experiences. But here's what makes this role truly special: you'll shape the future. You'll lead certification processes, advance optimization techniques, build evaluation systems that reason like humans, and mentor the next generation of AI safety experts. Every innovation you drive will set new standards for trustworthy AI at the world's largest scale. A day in the life As a Responsible AI Scientist, you're at the frontier of AI safety—experimenting with breakthrough techniques that push the boundaries of what's possible. You partner with engineering to transform research into production-ready solutions, tackling complex optimization challenges. You brainstorm with Product teams, translating ambitious visions into concrete objectives that drive real impact. Your expertise shapes critical deployment decisions as you review impactful work and guide go/no-go calls. You mentor the next generation of AI safety leaders, watching ideas spark and capabilities grow. This is where science meets impact—building AI that's not just intelligent, but trustworthy and aligned with human values. About the team Our team pioneers Responsible AI for conversational assistants. We ensure Alexa delivers safe, trustworthy experiences across all devices, modalities, and languages worldwide. We work on frontier AI safety challenges—and we're looking for scientists who want to help shape the future of trustworthy AI.

AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we’re looking for talented people who want to help. You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion. Do you love problem solving? Are you looking for real world Supply Chain challenges? Do you have a desire to make a major contribution to the future, in the rapid growth environment of Cloud Computing? Amazon Web Services is looking for a highly motivated, Data Scientist to help build scalable, predictive and prescriptive business analytics solutions that supports AWS Supply Chain and Procurement organization. You will be part of the Supply Chain Analytics team working with Global Stakeholders, Data Engineers, Business Intelligence Engineers and Business Analysts to achieve our goals. We are seeking an innovative and technically strong data scientist with a background in optimization, machine learning, and statistical modeling/analysis. This role requires a team member to have strong quantitative modeling skills and the ability to apply optimization/statistical/machine learning methods to complex decision-making problems, with data coming from various data sources. The candidate should have strong communication skills, be able to work closely with stakeholders and translate data-driven findings into actionable insights. The successful candidate will be a self-starter, comfortable with ambiguity, with strong attention to detail and ability to work in a fast-paced and ever-changing environment. Key job responsibilities - Demonstrate thorough technical knowledge on feature engineering of massive datasets, effective exploratory data analysis, and model building using industry standard time Series Forecasting techniques like ARIMA, ARIMAX, Holt Winter and formulate ensemble model. - Design and deploy AI agents for supply chain optimization. Build evaluation frameworks with guardrails and benchmarks ensuring reliability. Own the full development lifecycle adhering to responsible AI principles. Drive the AI roadmap leveraging emerging agentic AI trends. - Proficiency in both Supervised(Linear/Logistic Regression) and UnSupervised algorithms(k means clustering, Principle Component Analysis, Market Basket analysis). - Experience in solving optimization problems like inventory and network optimization . Should have hands on experience in Linear Programming. - Work closely with internal stakeholders like the business teams, engineering teams and partner teams and align them with respect to your focus area - Detail-oriented and must have an aptitude for solving unstructured problems. You should work in a self-directed environment, own tasks and drive them to completion. - Excellent business and communication skills to be able to work with business owners to develop and define key business questions and to build data sets that answer those questions - Work with distributed machine learning and statistical algorithms to harness enormous volumes of data at scale to serve our customers About the team Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve. Inclusive Team Culture AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do. Mentorship and Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Amazon's Compliance and Safety Services (CoSS) Team is looking for a smart and creative Applied Scientist to apply and extend state-of-the-art research in NLP, multi-modal modeling, domain adaptation, continuous learning and large language model to join the Applied Science team. At Amazon, we are working to be the most customer-centric company on earth. Millions of customers trust us to ensure a safe shopping experience. This is an exciting and challenging position to drive research that will shape new ML solutions for product compliance and safety around the globe in order to achieve best-in-class, company-wide standards around product assurance. You will research on large amounts of tabular, textual, and product image data from product detail pages, selling partner details and customer feedback, evaluate state-of-the-art algorithms and frameworks, and develop new algorithms to improve safety and compliance mechanisms. You will partner with engineers, technical program managers and product managers to design new ML solutions implemented across the entire Amazon product catalog. Key job responsibilities As an Applied Scientist on our team, you will: - Research and Evaluate state-of-the-art algorithms in NLP, multi-modal modeling, domain adaptation, continuous learning and large language model. - Design new algorithms that improve on the state-of-the-art to drive business impact, such as synthetic data generation, active learning, grounding LLMs for business use cases - Design and plan collection of new labels and audit mechanisms to develop better approaches that will further improve product assurance and customer trust. - Analyze and convey results to stakeholders and contribute to the research and product roadmap. - Collaborate with other scientists, engineers, product managers, and business teams to creatively solve problems, measure and estimate risks, and constructively critique peer research - Consult with engineering teams to design data and modeling pipelines which successfully interface with new and existing software - Publish research publications at internal and external venues. About the team The science team delivers custom state-of-the-art algorithms for image and document understanding. The team specializes in developing machine learning solutions to advance compliance capabilities. Their research contributions span multiple domains including multi-modal modeling, unstructured data matching, text extraction from visual documents, and anomaly detection, with findings regularly published in academic venues.

Amazon Science gives you insight into the company’s approach to customer focused scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work. Please visit https://www.amazon.science for more information. Are you an expert in Computer Vision (CV), Natural Langugage Procesing (NLP) or Multi-Modality Large Language Models (MLLM)? Are you interested in building Generative AI solutions on complex business problems that have significant global benefit. The Brand Protection Science team designs and builds highly performing and scalable AI models using machine learning, deep learning, LLM/Gen AI to identify and prevent infringement abuse and counterfeit on behalf of buyer, seller and brand owners worldwide. As an Applied Science Manager, you will be lead a group of highly talented scientists, and partner with Tech, Business and Operations, to build the strategic vision for brand protection, drive execution and launch scalable AI solutions operating on billions of Amazon product listings WW for Brand Protection. Key job responsibilities You will lead a team of Applied Scientist to work backwards from customer needs and solve complex scientific problems that have a high business and customer impact. As a manager, You will be the thought leader for inventing novel science solutions using SOTA ML techniques including LLM and GenAI. You partner with your stakeholders and leadership to define the science vision and strategies for your team. You have excellent communication skills to explain complex scientific approaches to a variety of stakeholders and customers, and bridge the gap between science, tech, and business,. You are accountable for the science vision and strategic direction of your team, the artifacts they provide, and any technologies owned. You will establish structures that enable your team to consistently deliver. You will also lead your team to leverage the broader Amazon scientific community, and build a team culture that focuses on bringing research to production, removing road blockers, and delivering more results for Amazon customers. You are strategic about the team members' growth and provide those interested with opportunities to demonstrate higher level role scope, impact, complexity and leadership.

Global Optimization is a strategic initiative aimed at improving Amazon advertisers experience at global scale. We are looking for a passionate Applied Scientist to help pioneer the next generation of agentic AI applications for Amazon advertisers. In this role, you will design agentic architectures, develop tools and datasets, and contribute to building systems that can reason, plan, and act autonomously across complex advertiser workflows at global scale. You will work at the forefront of applied AI, developing methods for fine-tuning, reinforcement learning, and preference optimization, while helping create evaluation frameworks that ensure safety, reliability, and trust at scale. You will work backwards from the needs of advertisers—delivering customer-facing products that directly help them create, optimize, and grow their campaigns. Beyond building models, you will advance the agent ecosystem by experimenting with and applying core primitives such as tool orchestration, multi-step reasoning, and adaptive preference-driven behavior. This role requires working independently on ambiguous technical problems, collaborating closely with scientists, engineers, and product managers to bring innovative solutions into production. Key job responsibilities - Design and build agents that improve advertisers experiences globally - Design and implement advanced model and agent optimization techniques, including supervised fine-tuning, instruction tuning and preference optimization (e.g., DPO/IPO). - Design and implement optimization models that work at global scale taking into account nuances of multiple countries - Innovate new science models to help advertisers scale their campaigns globally - Curate datasets and tools for MCP. - Build evaluation pipelines for agent workflows, including automated benchmarks, multi-step reasoning tests, and safety guardrails. - Develop agentic architectures (e.g., CoT, ToT, ReAct) that integrate planning, tool use, and long-horizon reasoning. - Prototype and iterate on multi-agent orchestration frameworks and workflows. - Collaborate with peers across engineering and product to bring scientific innovations into production. - Stay current with the latest research in LLMs, RL, and agent-based AI, optimization and translate findings into practical applications. About the team The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through the latest 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. The Global Optimization team within Sponsored Products and Brands is focused on guiding and supporting 1.6MM advertisers to meet their advertising needs of creating and managing ad campaigns at global scale. At this scale, the complexity of diverse advertiser goals, campaign types, and market dynamics creates both a massive technical challenge and a transformative opportunity: even small improvements in guidance systems can have outsized impact on advertiser success and Amazon’s retail ecosystem. Our work is grounded in state-of-the-art agent architectures, tool integration, reasoning frameworks, and model customization approaches (including tuning, MCP, and preference optimization), ensuring our systems are both scalable and adaptive.