Careers

Are you inspired by invention? Is problem solving through teamwork in your DNA? Do you like the idea of seeing how your work impacts the bigger picture? Answer yes to any of these and you’ll fit right in here at Amazon Robotics. We are a smart team of doers that work passionately to apply cutting edge advances in robotics and software to solve real-world challenges that will transform our customers’ experiences in ways we can’t even imagine yet. We invent new improvements every day. We are Amazon Robotics and we will give you the tools and support you need to invent with us in ways that are rewarding, fulfilling and fun. The Research Science team at Amazon Robotics is seeking interns with a passion for robotic research to work on cutting edge algorithms for robotics. Our team works on challenging and high-impact projects, including allocating resources to complete a million orders a day, coordinating the motion of thousands of robots, autonomous navigation in warehouses, and learning how to grasp all the products Amazon sells. We are seeking internship candidates with backgrounds in computer vision, machine learning, resource allocation, discrete optimization, search, planning/scheduling, and reinforcement learning. As an intern you will develop a new algorithm to solve one of the challenging computer vision and manipulation problems in Amazon's robotic warehouses. Your project will fit your academic research experience and interests. You will code and test out your solutions in increasingly realistic scenarios and iterate on the idea with your mentor to find the best solution to the problem.

Here at Amazon, we embrace our differences. We are committed to furthering our culture of diversity and inclusion of our teams within the organization. How do you get items to customers quickly, cost-effectively, and—most importantly—safely, in less than an hour? And how do you do it in a way that can scale? Our teams of hundreds of scientists, engineers, aerospace professionals, and futurists have been working hard to do just that! We are delivering to customers, and are excited for what’s to come. Check out more information about Prime Air on the About Amazon blog (https://www.aboutamazon.com/news/transportation/amazon-prime-air-delivery-drone-reveal-photos). If you are seeking an iterative environment where you can drive innovation, apply state-of-the-art technologies to solve real world delivery challenges, and provide benefits to customers, Prime Air is the place for you. Come work on the Amazon Prime Air Team! Our Prime Air Drone Flight Sciences High Fidelity Methods (HFM) team is looking for an outstanding member to develop and verify our Aerodynamic Database and associated aerodynamics models used for engineering analyses and vehicle simulations. These models are the backbone of every flight simulation performed within Prime Air and are a critical element in the aircraft design, verification, and certification process. These models are used to predict many attributes of the vehicle performance including range, maneuverability, tracking error, and aircraft stability. They are a key input to design decisions, vehicle component sizing and flight software algorithm development. The accuracy and reliability of these flight model are critical to the success of Prime Air. Key job responsibilities The person in this role is responsible for owning the development, deployment, verification, and maintenance of models from end-to-end. This includes the initial gathering of the downstream customer needs, identifying the most suitable modelling approach, coordinating the generation of input data, training models, developing and maintaining software interfaces, and verifying the model accuracy. This person will also be responsible for determining the most suitable modeling approach for a given physical phenomena. They need to possess knowledge of various machine learning techniques, and their respective advantages and limitations. They will need to have a detailed understanding of the types of physics to be modelled including vehicle aerodynamics, multibody dynamics, and atmosphere physics. They will be responsible for designing experiments for generating data used to train and verify surrogate models. They need to have a basic understanding of the methods used to generate high-fidelity aerodynamics predictions including CFD, wind tunnel testing, and flight testing. They will be responsible for validating the models by leveraging uncertainty quantification, system identification, and statistical analyses.

The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and innovative applied scientist with a strong background in deep learning, to help build industry-leading technology with Large Language Models (LLMs) and multimodal systems. Key job responsibilities As an Applied Scientist with the AGI team, you will work with world-class scientists and engineers to develop novel data, modeling and engineering solutions to support the responsible AI initiatives at AGI. Your work will directly impact our customers in the form of products and services that make use of AI technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in AGI in order to provide the best-possible experience for our customers. About the team Our team has a mission to push the envelope of AGI, in order to provide the best-possible experience for our customers.

We are hiring a Director, Economics who is excited about leading a team that develops and implements a research agenda that drives value for AWS customers and the business. The problem space includes identifying new cross org and cross function workstreams with measurable impact. The right person in this role will command a broad suite of economic and science areas, develop new ones as appropriate, and apply them to highly ambiguous business problems. This person will earn the trust of AWS executives to handle the hardest science problems in a collaboration with their teams and other scientists. The person with recruit top talent and foster an enviably fun and supportive workplace environment where ICs and managers grow and reach their career goals. Key job responsibilities This role with interface directly with executives, product owners and science ICs and leadership to create multi-year research agendas that drive step change growth for the business. This role is important for development of the strategic direction of the AWS Central Economics and Science team. This role will report directly to the Chief Economist of AWS and help develop and implement science best practices for the team in collaborative partnership with other scientists, economists and engineers in the org. A day in the life Our team takes big swings and works on hard cross organizational problems where the optimal success rate is not 100%. We also ask people to grow their skills and stretch and make sure we do it in a supportive and fun environment. It’s about empirically measured impact, advancement, and fun on our team. We work hard during work hours but we also don’t encourage working at nights or on weekends except in very rare, high stakes cases. Burn out isn’t a successful long run strategy. Because we invest in the long run success of our group it’s important to have hobbies, relax and then come to work refreshed and excited. It makes for bigger impact, faster skill accrual and thus career advancement. About the team Our group is technically rigorous and encourages ongoing academic conference participation and publication. Our leaders are here for you and to enable you to be successful. We believe in being servant leaders focused on influence: good data work has little value if it doesn’t translate into actionable insights that are rolled out and impact the real economy. We are communication centric since being able to explain what we do ensures high success rates and lowers administrative churn. Also, we laugh a lot. If it’s not fun, what’s the point?

Amazon Advertising is one of Amazon's fastest growing 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 Creative X team within Amazon Advertising time aims to democratize access to high-quality creatives (images, videos) by building AI-driven solutions for advertisers. To accomplish this, we are investing in latent-diffusion models, large language models (LLM), computer vision (CV), reinforced learning (RL), and image + video and audio synthesis. You will be part of a close-knit team of applied scientists and product managers who are highly collaborative and at the top of their respective fields. We are looking for talented Applied Scientists who are adept at a variety of skills, especially with computer vision, latent diffusion or related foundational models that will accelerate our plans to generate high-quality creatives on behalf of advertisers. Every member of the team is expected to build customer (advertiser) facing features, contribute to the collaborative spirit within the team, publish, patent, and bring cutting edge research to raise the bar within the team. As an Applied Scientist on this team, you will: * Drive end-to-end GenAI projects that have a high degree of ambiguity, scale and 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. * 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. * Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving. * Identify and action data collection and labelling in conjunction with team members. * Research new and innovative machine learning approaches. * Present results and explain methods to senior leadership. 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. Key job responsibilities This role is focused on computer vision, latent diffusion models, and the related foundational models to produce generative imagery and videos. You will develop core models that will be the foundational of the core advertising-facing tools that we are launching. You will conduct literature reviews to stay on the cutting edge of the field. You will regularly engage with product managers, who will partner with you to productize your work. A day in the life On a day-to-day basis, you will be doing your independent research and work to develop models, you will participate in sprint planning, collaborative sessions with your peers, and demo new models and share results with peers, other partner teams and leadership. About the team The team consists of applied scientists and machine learning engineers. We reside in the Creative X organization, which focuses on creating products for advertisers that will improve the quality of the creatives within Amazon Ads.

Amazon ‘s Tax engine organisation is looking for a passionate and innovative science leader to take its science initiatives to new heights. Amazon Tax Engine platform backs all of the orders placed across Amazon e-commerce. We serve Amazon customers and sellers by correctly computing and collecting the tax amounts when an Amazon order is placed globally. We are responsible for correctly attributing products to the correct Tax categories applicable for the specific country, state and county, providing core calculation services that calculate taxes (sales tax and VAT) for all Amazon sales, physical and digital. Our challenges include staying on top of the complex and ever-changing global tax legislations as well as computing calculations correctly and quickly, thousands of times a second, with accuracy close to 100%. We use language models at scale for Tax classification of the diverse products in Amazon catalogue We have a growing portfolio of science problems that includes balance of predictive and generative AI -including language comprehension, causal reasoning and active learning. Key job responsibilities - Manage and mentor a talented team of senior Appleid Scientists and SDEs. - Improve process and methodologies pertaining to deliverables of the team. - Strike the right balance between experimentation and delivery for sustained impact and long term gains. - Partner with stakeholders and customers to build roadmap for new products and services.

Come build the future of smart security with us. Are you interested in helping shape the future of devices and services designed to keep people close to what’s important? ABOUT RING We started in a garage in 2012 when our founder asked a simple question: what if you could answer the front door from your phone? What if you could be there without needing to actually, you know, be there? After many late nights and endless tinkering, our first Video Doorbell was born. That invention has grown into over a decade of groundbreaking products and next-level features. And at the core of all that, everything we’ve done and everything we’ve yet to build, is that same inventor's spirit and drive to bridge the distance between people and what they care about. Whatever it is, at Ring we’re committed to helping you be there for it. (https://www.ring.com) ABOUT THE ROLE The Senior Data Scientist within Ring Data Science and Engineering plays a pivotal role in shaping how we carry the voice of our customers. We strive to understand their behaviors and preferences in order to provide them with the best experience connecting with the places, people and things that matter to them. This role will build scalable solutions and models to support our business functions (Subscriptions, Product, Customer Service). By leveraging a range of methods including statistical analysis and machine learning, you will explain, quantify, predict and prescribe in support of informing critical business decisions. You will translate business goals into agile, insightful analytics. You will seek to create value for both stakeholders and customers and inform findings in a clear, actionable way to managers and senior leaders. Key job responsibilities - Drive shared understanding among business, engineering, and science teams of domain knowledge of processes, system structures, and business requirements. - Apply domain knowledge to identify product roadmap, growth, engagement, and retention opportunities; quantify impact; and inform prioritization. - Advocate technical solutions to business stakeholders, engineering teams, and executive level decision makers. - Lead development and validation of state-of-the-art technical designs (data pipelines, data models, causal inference, predictive models, data insights/visualizations, etc) - Contribute to the hiring and development of others - Communicate strategy, progress, and impact to senior leadership A day in the life Translate/Interpret • Complex and interrelated datasets describing customer behavior, messaging, content, product design and financial impact. Measure/Quantify/Expand • Retrieve, synthesize, and present critical data in a format that is immediately useful to answering specific questions or improving system performance. • Analyze historical data to identify trends and support decision making. • Improve upon existing methodologies by developing new data sources, testing model enhancements, and fine-tuning model parameters. • Provide requirements to develop analytic capabilities, platforms, and pipelines. • Apply statistical or machine learning knowledge to specific business problems and data. Explore/Enlighten • Formalize assumptions about how users are expected to behave, create statistical definition of the outlier, and develop methods to systematically identify these outliers. Work out why such examples are outliers and define if any actions needed. • Given anecdotes about anomalies or generate automatic scripts to define anomalies, deep dive to explain why they happen, and identify fixes. • Make decisions and recommendations. • Build decision-making models and propose solution for the business problem you defined. • Conduct written and verbal presentation to share insights and recommendations to audiences of varying levels of technical sophistication. • Utilize code (Python/R/SQL) for data analyzing and modeling algorithms.

At Audible, we believe stories have the power to transform lives. It’s why we work with some of the world’s leading creators to produce and share audio storytelling with our millions of global listeners. We are dreamers and inventors who come from a wide range of backgrounds and experiences to empower and inspire each other. Imagine your future with us. ABOUT THIS ROLE The playback team at Audible owns the core playback logic end-to-end. All our services, systems and players are invoked each time customers click play (or download a title for offline playback) to enjoy the best playback experience. Specifically we own 1) Core playback logic on players such as Android, iOS and Web, 2) Playback services related to content delivery infrastructure, security & digital rights management, and processing / synchronization of listening data across devices, 3) listening statistics that power royalties, returns, creator metrics, and more, 4) Playback metrics, insights and platform, obsessing over the core playback metrics and trends that represent the service health of Audible Playback and delivery, 5) Unified Audible Playback SDK, that can be shared with both 3P and 1P customers, 6) Player optimizations related to QoE, ABR and Quality/CDN selection across Android, iOS and web, Server optimizations to segment the customer data and tune playback parameters in real-time, 7) all of the efforts around quality of experience monitoring which enable timely, accurate and automated detection of QoS performance degradations and identify opportunities to improve playback experience, 8) automated ML based review and sentiment analysis system that will proactively analyze posts across social media feeds, customer reviews to automatically establish relational models to identify and cross correlate issues detected by tools such as Anomaly detection, and finally, 9) Driving Audible’s playback initiatives to establish faculty collaborations to advance state of the art in Internet Audio. ABOUT YOU As an applied scientist on our team, you will wear many hats and work in a highly collaborative environment that’s more startup than big company. You'll need to tackle complex problems that span a variety of domains: Machine learning, Artificial intelligence, Natural Language processing, real-time and distributed systems and help us build services and systems from the ground up which scale and serve billions of requests per day, with obsessively high reliability and low operational overhead. You'll have an opportunity to explore, innovate, invent and simplify various Playback state-of-art services and algorithms which leverage both custom and Industry proven Machine Learning, Natural Language processing and Artificial Intelligence technologies. Your work will focus on training and evaluating models and deploying them to production where we continuously monitor and evaluate. You'll work on large engineering efforts that solve significantly complex problems facing global customers. You'll be trusted to operate with independence and are often assigned to focus on areas with significant impact on audience satisfaction. You must be equally comfortable digging in to customer requirements as you are drilling into design with development teams and developing production ready learning models. You consistently bring strong, data-driven business and technical judgment to decisions. We experiment a lot and it is a must to learn and be curios. You'll be encouraged to see the big picture, be innovative, and positively impact millions of customers. As a Senior Applied Scientist, you will... - Understand large complex use cases across the Playback org and design scalable, efficient, and automated solutions - Design, develop, and deploy state-of-art Optimization services & algorithms and novel adaptive bitrate algorithms - Partner closely with other Amazon scientists focused on streaming insights and optimization use cases - Work closely with teams of scientists and software engineers to drive real-time model implementations and deliver novel and highly impactful features - Push the boundary of innovation - Mentor and grow the scientists in the team and across Amazon ABOUT AUDIBLE Audible is the leading producer and provider of audio storytelling. We spark listeners’ imaginations, offering immersive, cinematic experiences full of inspiration and insight to enrich our customers daily lives. We are a global company with an entrepreneurial spirit. We are dreamers and inventors who are passionate about the positive impact Audible can make for our customers and our neighbors. This spirit courses throughout Audible, supporting a culture of creativity and inclusion built on our People Principles and our mission to build more equitable communities in the cities we call home.

At Audible, we believe stories have the power to transform lives. It’s why we work with some of the world’s leading creators to produce and share audio storytelling with our millions of global listeners. We are dreamers and inventors who come from a wide range of backgrounds and experiences to empower and inspire each other. Imagine your future with us. ABOUT THIS ROLE In this role, you'll employ scalable cutting-edge machine learning (ML), deep learning (DL), and Natural Language Processing (NLP) techniques to detect and predict fraudulent activities, enhance fraud investigation capabilities, and develop advanced fraud protection and defense mechanisms. You'll leverage these technologies to analyze complex patterns in transaction data, identify anomalies, and create predictive models that can anticipate potential fraud before it occurs. Your work will be crucial in safeguarding the company's assets, protecting customers from financial harm, and maintaining the integrity of our systems. You'll translate intricate fraud patterns into actionable insights, enabling rapid response to emerging threats and informing critical business decisions related to risk management. You'll operate in an agile environment in which we own and collaborate on the life cycle of research, design, and model development of relevant projects. As an Applied Scientist, you will... - Protect Audible’s customers and content creators against the onslaught of AI-generated fraud - Develop Amazon-scale data engineering & modeling pipelines - Imagine and invent before the business asks, and create groundbreaking fraud detection and mitigation solutions using cutting-edge approaches - Work closely with other data scientists, ML experts, engineers as well as business across the globe, and on cross-disciplinary efforts with other scientists within Amazon - Contribute to the growth of the Audible Data Science team by sharing your ideas, intellectual property and learning from others ABOUT AUDIBLE Audible is the leading producer and provider of audio storytelling. We spark listeners’ imaginations, offering immersive, cinematic experiences full of inspiration and insight to enrich our customers daily lives. We are a global company with an entrepreneurial spirit. We are dreamers and inventors who are passionate about the positive impact Audible can make for our customers and our neighbors. This spirit courses throughout Audible, supporting a culture of creativity and inclusion built on our People Principles and our mission to build more equitable communities in the cities we call home.

As part of the AWS Solutions organization, we have a vision to provide business applications, leveraging Amazon’s unique experience and expertise, that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers’ businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. We blend vision with curiosity and Amazon’s real-world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are no-brainers to buy and easy to use. AWS Industry Products (IP) is a new AWS engineering organization chartered to build new AWS products by applying Amazon’s innovation mechanisms along with AWS digital technologies to transform the world, industry by industry. We dive deep with leaders and innovators to solve the problems which block their industries, enabling them to capitalize on new digital business models. Simply put, our goal is to use the skill and scale of AWS to make the benefits of a connected world achievable for all businesses. We are looking for Research Scientists who are passionate about transforming industries through AI. This is a unique opportunity to not only listen to industry customers but also to develop AI and generative AI expertise in multiple core industries. You will join a team of scientists, product managers and software engineers that builds AI solutions in automotive, manufacturing, healthcare, sustainability/clean energy, and supply chain/operations domains. Leveraging and advancing generative AI technology will be a big part of your charter as we seek to apply the latest advancements in generative AI to industry-specific problems Using your in-depth expertise in machine learning and generative AI, you will take the lead on tactical and strategic initiatives to deliver reusable science components and services that differentiate our industry products and solve customer problems. You will be the voice of scientific rigor, delivery, and innovation as you work with our segment teams on AI-driven product differentiators. You will conduct and advance research in AI and generative AI within and outside Amazon. Extensive knowledge of both state-of-the-art and emerging AI methods and technologies is expected. Hands-on knowledge of generative AI, foundation models and commitment to learn and grow in this field are expected. Basic qualifications PhD, or Master's degree and 10+ years of quantitative field research experience Experience investigating the feasibility of applying scientific principles and concepts to business problems and products Experience analyzing both experimental and observational data sets Preferred qualifications Knowledge of R, MATLAB, Python or similar scripting language About the team 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. Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the 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. Inclusive Team Culture Here at AWS, 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 & 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. 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. Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.