Careers

Amazon has the world's most complex supply chain: we fulfill global demand for hundreds of millions of products at lightning fast delivery speeds. We need your skills to optimize our supply chain, with the end goal of delighting our customers. A core part of the supply chain operations is Demand Forecasting: We forecast the demand of tens of millions of products. These forecasts are used to make many decisions, such as automatically order hundreds of millions worth of inventory, decide where to place that inventory, and establish labor plans for hundreds of warehouses. The Product Data Science team within Forecasting & Labs (part of Supply Chain Optimization Technologies) is looking for an analytical and technically skilled Data Scientist to join our team. Our team is responsible for bias correction model development and A/B testing for forecast improvements, GenAI/LLM research for forecast explainability, and deep analytics for Labs and Foundation Models. We work horizontally across the forecasting product portfolio—including National, Regional, Grocery, SSD, Inbound, and CIV forecasting—to embed advanced analytics and machine learning solutions where they create the most value. This position will be responsible for developing and supporting data science methodologies and building models to address ambiguous forecasting questions. The Data Scientist will design and analyze experiments (A/B tests) to measure the impact of forecast model changes, develop bias correction models to improve forecast accuracy, and contribute to GenAI/LLM-based approaches for forecast explainability and interpretability. The role also involves supporting the Labs experimentation platform, which designs and executes inference and experimentation systems that measure the impact of initiatives across SCOT. The Data Scientist needs to be familiar with deriving causal inferences using observational and experimental data and able to model variations related to demand prediction, out of stock, seasonality, and different lead times and spans. This role requires an individual with excellent analytical abilities as well as business acumen. The successful candidate will be a self-starter comfortable with ambiguity, with attention to detail, vocally self-critical, and an ability to work in a fast-paced and ever-changing environment. They recognize that the true measure of the success of the work product is based on the business impact the findings have had. The Demand Forecasting Team is looking for an analytical and technically skilled Data Scientist to join our team. This position will be responsible for developing and supporting best-in-class data science methodologies and building models to address ambiguous forecasting questions. The Data Scientist needs to be familiar with deriving causal inferences using observational data and able to model variations related with demand prediction, out of stock, seasonality, and different lead times and spans. Upon completion of statistical analysis, the Data Scientist needs to communicate measurement results to stakeholders by translating technical framework to business-oriented insights. This role requires an individual with excellent analytical abilities as well as business acumen. The successful candidate will be a self-starter comfortable with ambiguity, with attention to detail, vocally self-critical, an ability to work in a fast-paced and ever-changing environment. They recognize that the true measure of the success of the work product is based on the business impact the findings have had. Key job responsibilities - Design and analyze experiments (A/B tests) to measure the impact of forecast model changes and SCOT initiatives, drawing causal inferences from both experimental and observational data - Develop bias correction models to improve forecast accuracy across Amazon's demand forecasting systems, including National, Regional, Grocery, SSD, Inbound, and CIV forecasts - Contribute to GenAI/LLM-based research for forecast explainability and interpretability, helping stakeholders understand what drives forecast signals - Support and enhance the Labs experimentation platform by building scalable inference and measurement solutions that quantify the impact of forecasting improvements - Work horizontally across the forecasting product portfolio and collaborate with product managers, applied scientists, and engineering teams to embed analytics and ML solutions where they create the most value - Use large datasets to build models addressing ambiguous forecasting questions, including demand prediction, out of stock, seasonality, and varying lead times and spans - Interpret data, write reports, and communicate measurement results to stakeholders by translating technical frameworks into business-oriented insights and actionable recommendations - Keys to success in this role include exceptional analytics, statistics, judgment, and communication skills. The candidate will need to be able to extract insights from data and clearly communicate appropriate triggers and actions A day in the life Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: - Medical, Dental, and Vision Coverage - Maternity and Parental Leave Options - Paid Time Off (PTO) - 401(k) Plan If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!

At Amazon's FinTech organization, we are building AI systems that process hundreds of millions of financial transactions, turn complex documents into actionable intelligence, and power autonomous agents that learn from every customer interaction. We are looking for a Senior Applied Scientist to lead the development of generative AI applications that change how finance teams work, tackling problems at the intersection of large language models, multi-agent systems, and real-world financial operations. Key job responsibilities What You'll Work On - Building AI systems that finance teams trust enough to rely on without manual review, where precision isn't a nice-to-have, it's a compliance requirement - Designing agents that learn from user corrections and get measurably better with every interaction, not just at the next model release - Solving inference at massive scale using tiered model architectures, intelligent routing, and small language models that deliver production-grade accuracy at a fraction of frontier model cost - Developing evaluation frameworks that catch quality regressions before customers do and gate every model change before it ships Who Thrives Here - You're someone who cares as much about shipping as about research. - You've built models that run in production, not just in notebooks. - You're comfortable working across the full stack, from model architecture to deployment to measuring whether the customer's workflow actually changed. - You operate well in cross-functional settings where science, engineering, and business teams inform each other continuously. - You'd rather solve a hard real-world problem than optimize a benchmark. What Makes This Different Your work ships to production and directly changes how thousands of finance professionals operate daily The problems are genuinely hard: financial data is messy, regulated, high-stakes, and operates at a scale where naive LLM approaches break down You'll work across multiple domains — from contract intelligence to cash application to financial data investigation — not a single narrow use case 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.

The Challenge How do you orchestrate a fleet of autonomous drones to deliver packages safely in under an hour, while maximizing every minute of flight time? How do you scale a mission planning system to handle thousands of concurrent deliveries in complex, shifting environments? Our team of scientists, engineers, and aerospace professionals is solving these exact problems. We are looking for an Applied Science Manager to lead the evolution of our Mission Planning and Orchestration System. You will be at the forefront of defining how Prime Air moves from point A to point B with maximum efficiency. The Role As an Applied Science Manager, you will lead a high-caliber team of scientists and engineers focused on the "brains" of our fleet orchestration. You will bridge the gap between Geospatial Intelligence and Machine Learning to revolutionize our path planning and scheduling algorithms. Your primary north star? Increasing deliveries per hour (DPH) through intelligent, automated optimization. Key Responsibilities: Lead & Mentor: Manage a cross-functional team of Applied Scientists and Engineers, fostering a culture of scientific rigor and rapid iteration. Innovate Path Planning: Leverage ML/RL and heuristic search techniques to develop dynamic path-planning algorithms that navigate complex airspace and weather patterns. Optimize Orchestration: Drive the development of high-scale scheduling systems that manage battery life, maintenance cycles, and delivery windows to maximize fleet utilization. Geospatial Mastery: Utilize deep geospatial data (3D maps, urban topology, etc.) to improve situational awareness and mission safety. System Architecture: Define the long-term technical roadmap for mission orchestration, ensuring our systems are modular, scalable, and resilient. Cross-Functional Collaboration: Partner with Hardware, Flight Safety, and Supply Chain teams to translate business requirements into technical breakthroughs. Basic Qualifications Experience managing a team of scientists and/or engineers in a production environment. PhD or Master’s degree in Computer Science, Robotics, Operations Research, or a related field. Strong foundation in Geospatial Information Systems (GIS) and spatial data analysis. Proven track record of applying Machine Learning (e.g., Reinforcement Learning, Graph Neural Networks) to optimization problems like path planning or vehicle routing. Preferred Qualifications Experience with autonomous systems, UAVs, or large-scale logistics networks. Knowledge of combinatorial optimization and real-time scheduling constraints. A knack for turning ambiguous "blue sky" research into deployed, high-impact features. Export Control License: This position may require a deemed export control license for compliance with applicable laws and regulations. Placement is contingent on Amazon’s ability to apply for and obtain an export control license on your behalf. Key job responsibilities Strategic Technical Leadership & Throughput: Lead the development of path planning and geospatial orchestration models to maximize deliveries per hour, ensuring complex algorithms are production-ready and integrated into the mission system. Team Management & Delivery: Build and scale a world-class science team by mentoring talent and fostering career growth, while maintaining a high bar for operational excellence to deliver mission-critical software on schedule. A day in the life In a typical day, you lead an agile squad through high-velocity sprints, starting with a stand-up to unblock path-planning prototypes and ensure the team is on track for mission-critical delivery milestones. You spend your time bridging the gap between research and reality, reviewing code and design docs to ensurealgorithms for geospatial orchestration are production-ready and optimized for real-world drone throughput. Between deep-dive technical reviews, you focus heavily on people development—conducting 1:1s to mentor scientists and architecting career growth paths—while collaborating with cross-functional leads to ensure your team's innovations seamlessly integrate into the live mission planning system. About the team We're a mix of software developers, applied and research scientists, and geospatial experts as well as system developers.

Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video technologist, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! The Prime Video Title Lifecycle Presentation team sits at the intersection of science, experimentation, and customer experience. We leverage data signals and rigorous testing to present the most engaging information about our content to customers at precisely the right moment. Our mission is to ensure every customer interaction with Prime Video content is informed, relevant, and compelling in order to drive discovery and engagement across our vast catalog. We're seeking a Sr. Applied Scientist who excels at building sophisticated machine learning systems for content presentation and discovery. The ideal candidate brings deep expertise in: - Multi-modal embeddings for rich metadata representation, enabling nuanced understanding of content attributes and customer preferences - Contextualized ranking systems that adapt to customer intent, viewing context, and real-time signals - Reinforcement learning frameworks that create continuous improvement loops, allowing our systems to learn and optimize from customer interactions over time - General modeling techniques with strong fundamentals in machine learning and statistical methods - Recommender systems experience, with proven ability to build and scale personalization solutions You'll work with technology to solve complex problems in content discovery, leveraging large-scale data to create experiences that delight millions of Prime Video customers worldwide. Key job responsibilities - Lead Cross-Functional Science Initiatives: Drive a diverse portfolio of applied science projects spanning recommender systems, generative AI agent development and evaluation across multiple modalities, and computer vision applications. Demonstrate both breadth of understanding across technical domains and sufficient depth in each area to effectively lead multiple concurrent initiatives to successful outcomes. - Bridge Science and Engineering for Production-Scale Deployment: Partner with engineering teams to productionize machine learning models at Prime Video scale. Develop production-ready science code that meets engineering standards for performance, reliability, and maintainability, ensuring seamless transition from research to deployment. - Mentor and Develop Technical Talent: Provide technical mentorship and guidance to junior scientists and engineers on applied science methodologies, best practices, and professional development. Foster a culture of scientific rigor and continuous learning within the team.

We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to apply their macroeconomics and forecasting skillsets to solve real world problems. The intern will work in the area of forecasting, developing models to improve the success of new product launches in Private Brands. Our PhD Economist Internship Program offers hands-on experience in applied economics, supported by mentorship, structured feedback, and professional development. Interns work on real business and research problems, building skills that prepare them for full-time economist roles at Amazon and beyond. You will learn how to build data sets and perform applied econometric analysis collaborating with economists, scientists, and product managers. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with placement. These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis About the team The Amazon Private Brands Intelligence team applies Machine Learning, Statistics and Econometrics/economics to solve high-impact business problems, develop prototypes for Amazon-scale science solutions, and optimize key business functions of Amazon Private Brands and other Amazon orgs. We are an interdisciplinary team, using science and technology and leveraging the strengths of engineers and scientists to build solutions for some of the toughest business problems at Amazon, covering areas such as pricing, discovery, negotiation, forecasting, supply chain and product selection/development.

Alexa+ is Amazon’s next-generation, AI-powered virtual assistant. Building on the original Alexa, it uses generative AI to deliver a more conversational, personalised, and effective experience. Alexa Sensitive Content Intelligence (ASCI) team is developing responsible AI (RAI) solutions for Alexa+, empowering it to provide useful information responsibly. 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. We are looking for a passionate, talented, and inventive Data Scientist-II to help build industry-leading technology with Large Language Models (LLMs) and multimodal systems, requiring good learning and generative models knowledge. You will be working with a team of exceptional Data Scientists working in a hybrid, fast-paced organization where scientists, engineers, and product managers work together to build customer facing experiences. You will collaborate with other data scientists while understanding the role data plays in developing data sets and exemplars that meet customer needs. You will analyze and automate processes for collecting and annotating LLM inputs and outputs to assess data quality and measurement. You will apply state-of-the-art Generative AI techniques to analyze how well our data represents human language and run experiments to gauge downstream interactions. You will work collaboratively with other data scientists and applied scientists to design and implement principled strategies for data optimization. Key job responsibilities A Data Scientist-II should have a reasonably good understanding of NLP models (e.g. LSTM, LLMs, other transformer based models) or CV models (e.g. CNN, AlexNet, ResNet, GANs, ViT) and know of ways to improve their performance using data. You leverage your technical expertise in improving and extending existing models. Your work will directly impact our customers in the form of products and services that make use of speech, language, and computer vision technologies. You will be joining a select group of people making history producing one of the most highly rated products in Amazon's history, so if you are looking for a challenging and innovative role where you can solve important problems while growing in your career, this may be the place for you. A day in the life You will be working with a group of talented scientists on running experiments to test scientific proposal/solutions to improve our sensitive contents detection and mitigation for worldwide coverage. This will involve collaboration with partner teams including engineering, PMs, data annotators, and other scientists to discuss data quality, policy, model development, and solution implementation. You will work with other scientists, collaborating and contributing to extending and improving solutions for the team. 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.

Alexa+ is Amazon’s next-generation, AI-powered virtual assistant. Building on the original Alexa, it uses generative AI to deliver a more conversational, personalised, and effective experience. Alexa Sensitive Content Intelligence (ASCI) team is developing responsible AI (RAI) solutions for Alexa+, empowering it to provide useful information responsibly. 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. We are looking for a passionate, talented, and inventive Data Scientist-II to help build industry-leading technology with Large Language Models (LLMs) and multimodal systems, requiring good learning and generative models knowledge. You will be working with a team of exceptional Data Scientists working in a hybrid, fast-paced organization where scientists, engineers, and product managers work together to build customer facing experiences. You will collaborate with other data scientists while understanding the role data plays in developing data sets and exemplars that meet customer needs. You will analyze and automate processes for collecting and annotating LLM inputs and outputs to assess data quality and measurement. You will apply state-of-the-art Generative AI techniques to analyze how well our data represents human language and run experiments to gauge downstream interactions. You will work collaboratively with other data scientists and applied scientists to design and implement principled strategies for data optimization. Key job responsibilities A Data Scientist-II should have a reasonably good understanding of NLP models (e.g. LSTM, LLMs, other transformer based models) or CV models (e.g. CNN, AlexNet, ResNet, GANs, ViT) and know of ways to improve their performance using data. You leverage your technical expertise in improving and extending existing models. Your work will directly impact our customers in the form of products and services that make use of speech, language, and computer vision technologies. You will be joining a select group of people making history producing one of the most highly rated products in Amazon's history, so if you are looking for a challenging and innovative role where you can solve important problems while growing in your career, this may be the place for you. A day in the life You will be working with a group of talented scientists on running experiments to test scientific proposal/solutions to improve our sensitive contents detection and mitigation for worldwide coverage. This will involve collaboration with partner teams including engineering, PMs, data annotators, and other scientists to discuss data quality, policy, model development, and solution implementation. You will work with other scientists, collaborating and contributing to extending and improving solutions for the team. 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.

The Amazon Center for Quantum Computing in Pasadena, CA, is looking to hire an Applied Science intern who will specialize in hardware signal train design for quantum computing. Working alongside other scientists and engineers, you will design and validate hardware performing the control and readout functions for Amazon quantum processors, from room to cryogenic temperatures. Candidates must have a solid background in analog or mixed-signal design at the PCB level. Working effectively within a cross-functional team environment is critical. Key job responsibilities Our scientists and engineers collaborate across diverse teams and projects to offer state of the art, cost effective solutions for the control of Amazon quantum processor systems. You’ll bring a passion for innovation and collaboration to: Design cryogenic and room temperature printed circuit board based hardware, used for signal conditioning and control functions. Develop tests to validate hardware with both benchtop and cryogenic test setups with quantum devices. Explore enabling control technologies necessary for Amazon to produce commercially viable quantum computers. 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. 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 in the cloud. Inclusive Team Culture Here at Amazon, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. 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.

Are you a MS or PhD student interested in a 2026 internship in the field of machine learning, deep learning, generative AI, large language models and speech technology, robotics, computer vision, optimization, operations research, quantum computing, automated reasoning, or formal methods? If so, we want to hear from you! We are looking for students interested in using a variety of domain expertise to invent, design and implement state-of-the-art solutions for never-before-solved problems. You can find more information about the Amazon Science community as well as our interview process via the links below; https://www.amazon.science/ https://amazon.jobs/content/en/career-programs/university/science https://amazon.jobs/content/en/how-we-hire/university-roles/applied-science Key job responsibilities As an Applied Science Intern, you will own the design and development of end-to-end systems. You’ll have the opportunity to write technical white papers, create roadmaps and drive production level projects that will support Amazon Science. You will work closely with Amazon scientists and other science interns to develop solutions and deploy them into production. You will have the opportunity to design new algorithms, models, or other technical solutions whilst experiencing Amazon’s customer focused culture. The ideal intern must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. A day in the life At Amazon, you will grow into the high impact person you know you’re ready to be. Every day will be filled with developing new skills and achieving personal growth. How often can you say that your work changes the world? At Amazon, you’ll say it often. Join us and define tomorrow. Some more benefits of an Amazon Science internship include; • All of our internships offer a competitive stipend/salary • Interns are paired with an experienced manager and mentor(s) • Interns receive invitations to different events such as intern program initiatives or site events • Interns can build their professional and personal network with other Amazon Scientists • Interns can potentially publish work at top tier conferences each year About the team Applicants will be reviewed on a rolling basis and are assigned to teams aligned with their research interests and experience prior to interviews. Start dates are available throughout the year and durations can vary in length from 3-6 months for full time internships. This role may available across multiple locations in the EMEA region (Austria, Estonia, France, Germany, Ireland, Israel, Italy, Jordan, Luxembourg, Netherlands, Poland, Romania, Spain, South Africa, UAE, and UK). Please note these are not remote internships.

We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to apply their macroeconomics and forecasting skillsets to solve real world problems. The intern will work in the area of forecasting, developing models to improve the success of new product launches in Private Brands. Our PhD Economist Internship Program offers hands-on experience in applied economics, supported by mentorship, structured feedback, and professional development. Interns work on real business and research problems, building skills that prepare them for full-time economist roles at Amazon and beyond. You will learn how to build data sets and perform applied econometric analysis collaborating with economists, scientists, and product managers. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with placement. These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis About the team The Amazon Private Brands Intelligence team applies Machine Learning, Statistics and Econometrics/economics to solve high-impact business problems, develop prototypes for Amazon-scale science solutions, and optimize key business functions of Amazon Private Brands and other Amazon orgs. We are an interdisciplinary team, using science and technology and leveraging the strengths of engineers and scientists to build solutions for some of the toughest business problems at Amazon, covering areas such as pricing, discovery, negotiation, forecasting, supply chain and product selection/development.