Careers

Do you want to join an innovative team of scientists who leverage cutting-edge techniques like reinforcement learning (RL), large language models (LLMs), graph analytics, and machine learning to help Amazon provide the best customer experience by protecting Amazon customers from hackers and bad actors? Do you want to build advanced algorithmic systems that integrate these state-of-the-art techniques to help manage the trust and safety of millions of customers every day? Are you excited by the prospect of analyzing and modeling terabytes of data and creating sophisticated algorithms that combine RL, LLMs, graph embeddings, and traditional machine learning methods to solve complex real-world problems? Do you like to innovate, simplify, and push the boundaries of what's possible? If yes, then you may be a great fit to join the Amazon Account Integrity team, where you'll have the opportunity to work at the forefront of AI and machine learning, tackling challenging problems that have a direct impact on the security and trust of Amazon's customers. The Amazon Account Integrity team works to ensure that customers are protected from bad actors trying to access their accounts. Our greatest challenge is protecting customer trust without unjustly harming good customers. To strike the right balance, we invest in mechanisms which allow us to accurately identify and mitigate risk, and to quickly correct and learn from our mistakes. This strategy includes continuously evolving enforcement policies, iterating our Machine Learning risk models, and exercising high‐judgement decision‐making where we cannot apply automation. Please visit https://www.amazon.science for more information

The Team: Amazon Go is a new kind of store with no lines and no checkout—you just grab and go! Customers simply use the Amazon Go app to enter the store, take what they want from our selection of fresh, delicious meals and grocery essentials, and go! Our checkout-free shopping experience is made possible by our Just Walk Out Technology, which automatically detects when products are taken from or returned to the shelves and keeps track of them in a virtual cart. When you’re done shopping, you can just leave the store. Shortly after, we’ll charge your Amazon account and send you a receipt. Check it out at amazon.com/go. Designed and custom-built by Amazonians, our Just Walk Out Technology uses a variety of technologies including computer vision, sensor fusion, and advanced machine learning. Innovation is part of our DNA! Our goal is to be Earths’ most customer centric company and we are just getting started. We need people who want to join an ambitious program that continues to push the state of the art in computer vision, machine learning, distributed systems and hardware design. The Role: Everyone on the team needs to be entrepreneurial, wear many hats and work in a highly collaborative environment that’s more startup than big company. We’ll need to tackle problems that span a variety of domains: computer vision, image recognition, machine learning, real-time and distributed systems. As a Machine Learning or Computer Vision Research Scientist, you will help solve a variety of technical challenges and mentor other engineers. You will tackle challenging, novel situations every day and given the size of this initiative, you’ll have the opportunity to work with multiple technical teams at Amazon in different locations. You should be comfortable with a degree of ambiguity that’s higher than most projects and relish the idea of solving problems that, frankly, haven’t been solved at scale before - anywhere. Along the way, we guarantee that you’ll learn a ton, have fun and make a positive impact on millions of people. 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. 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. 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. 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. 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.

Advertising at Amazon is a fast-growing multi-billion dollar business that spans across desktop, mobile and connected devices; encompasses ads on Amazon and a vast network of hundreds of thousands of third party publishers; and extends across US, EU and an increasing number of international geographies. One of the key focus areas is Traffic Quality where we endeavour to identify non-human and invalid traffic within programmatic ad sources, and weed them out to ensure a high quality advertising marketplace. We do this by building machine learning and optimization algorithms that operate at scale, and leverage nuanced features about user, context, and creative engagement to determine the validity of traffic. The challenge is to stay one step ahead by investing in deep analytics and developing new algorithms that address emergent attack vectors in a structured and scalable fashion. We are committed to building a long-term traffic quality solution that encompasses all Amazon advertising channels and provides state-of-the-art traffic filtering that preserves advertiser trust and saves them hundreds of millions of dollars of wasted spend. We are looking for talented applied scientists who enjoy working on creative machine learning algorithms and thrive in a fast-paced, fun environment. An Applied Scientist is responsible for solving inherently hard problems in advertising fraud detection using deep learning, self-supervised techniques, representation learning and advanced clustering. An ideal candidate should have strong depth and breadth knowledge in machine learning, data mining and statistics. Traffic quality systems process billions of ad-impressions and clicks per day, by leveraging cutting-edge open source technologies like Hadoop, Spark, Redis and Amazon's cloud services like EC2, S3, EMR, DynamoDB and RedShift. The candidate should have reasonable programming and design skills to manipulate unstructured and big data and build prototypes that work on massive datasets. The candidate should be able to apply business knowledge to perform broad data analysis as a precursor to modeling and to provide valuable business intelligence.

Amazon has a rare opportunity for a talented Machine Learning Scientist to join an international team of ML experts changing the way our customers experience the everything store. At Amazon's International Machine Learning team, we partner with businesses across the Amazon ecosystem to drive innovation and deliver exceptional experiences for customers around the globe. Our team works on large-scale, high-impact projects that leverage the latest advancements in machine learning and artificial intelligence. As part of Amazon's Research and Development organization, you will have the opportunity to push the boundaries of applied science and deploy cutting-edge solutions that directly benefit millions of Amazon customers worldwide. Whether you are developing next-generation recommender systems, exploring the frontiers of generative AI, or tackling novel scientific challenges, your work at Amazon has the power to truly change the world. Join us in this exciting journey as we redefine the present and the future of innovative applied science. Key job responsibilities - You will take on complex problems, work on solutions that either leverage or extend existing academic and industrial research, and utilize your own out-of-the-box pragmatic thinking. - In addition to coming up with novel solutions and building prototypes, you will deliver these to production in customer facing applications, in partnership with product and development teams. - You will publish papers internally and/or externally, contributing to advancing knowledge in the field of information retrieval and machine learning. About the team Our team is composed of scientists with PhDs, with a strong publication profile and an appetite to see the impact of innovation on real-world systems at scale.

We are seeking a highly talented Applied Scientist to join our MENA Science team and drive the development of state-of-the-art machine learning solutions for our customers in the MENA region. In this role, you will leverage state-of-the-art machine learning and data science techniques to create cutting-edge solutions that directly address critical customer problems. Your work will directly impact the customer experience and profitability of our MENA businesses, helping us enhance catalog quality, improve machine translation, prevent abuse and fraud etc. Key job responsibilities • Invent, implement, and deploy cutting-edge machine learning algorithms and models to solve complex, real-world problems for our MENA customers. • Collaborate closely with cross-functional teams, including product managers, engineers, and other applied scientists, to identify high-impact areas for innovation. • Prototype and test new approaches, such as leveraging large language models (LLMs) and other advanced techniques, to drive measurable improvements in key business metrics. • Tackle a diverse range of challenges, such as improving catalog quality through large language models, enhancing machine translation, developing abuse prevention systems etc. • Staying up-to-date with the latest advancements in machine learning and data science, and proactively identifying opportunities to apply these techniques to drive business impact. • Contribute to the broader scientific community by publishing your work at top-tier conferences and journals. A day in the life Diving deep in to ambiguous and complex business problems and translating them to ML problem statements. Applying relevant science solutions for the ML problems. Staying abreast with evolving science landscape and applying the state-of-the-art. About the team MENA tech is a 200 people tech organization spread across Jordan, UAE, India and Seattle, building amazing solutions for customers in the region. We deploy in MENA first but build for the world

We’re working to improve shopping on Amazon using the conversational capabilities of large language models, and are searching for pioneers who are passionate about technology, innovation, and customer experience, and are ready to make a lasting impact on the industry. You'll be working with talented scientists and engineers to innovate on behalf of our customers. If you're fired up about being part of a dynamic, driven team, then this is your moment to join us on this exciting journey! Key job responsibilities We seek strong Applied Scientists with domain expertise in machine learning and deep learning, transformers, generative models, large language models, computer vision and multimodal models. You will devise innovative solutions at scale, pushing the technological and science boundaries. You will guide the design, modeling, and architectural choices of state-of-the-art large language models and multimodal models. You will devise and implement new algorithms and new learning strategies and paradigms. You will be technically hands-on and drive the execution from ideation to productionization. You will work in collaborative environment with other technical and business leaders, to innovate on behalf of the customer.

Join us in the evolution of Amazon’s Seller business! The Seller Growth Business organization is the growth and development engine for our Store. Partnering with business, product, and engineering, we catalyze SP growth with comprehensive and accurate data, unique insights, and actionable recommendations and collaborate with WW SP facing teams to drive adoption and create feedback loops. We strongly believe that any motivated SP should be able to grow their businesses and reach their full potential by using our scaled, automated, and self-service tools. We aim to accelerate the growth of Sellers by providing tools, insights, and recommendations that enable them to make better and faster decisions at each step of selection management. To accomplish this, we offer intelligent insights that are both detailed and actionable, allowing Sellers to introduce new products and engage with customers effectively. We leverage extensive structured and unstructured data to generate science-based insights about their business. Furthermore, we provide personalized recommendations tailored to individual Sellers' business objectives in a user-friendly format. These insights and recommendations are integrated into our products, including Amazon Brand Analytics (ABA), Product Opportunity Explorer (OX), and Manage Your Growth (MYG). Additionally, we leverage the start-of-art technology, such as Gen AI to enable efficient insights consumption and recommendation digestion for Sellers, as well as providing an interactive experiences to Sellers using our tools. We are looking for a talented and passionate Sr. Applied Science manager to lead our research endeavors and develop world-class statistical and machine learning models. The successful candidate will work closely with Product Managers (PM), User Experience (UX) designers, engineering teams, and Seller Growth Consulting teams to provide actionable insights that drive improvements in Seller businesses. Key job responsibilities Your responsibilities will include: • Taking full service ownership of your teams including developing research and engineering (product roadmaps), developing and tracking relevant metrics, and ensuring system performance. • Ensuring the team are publishing high-quality research in top conferences and journals, which are also directly impactful for our customers. • Delivering against project plans and program commitments. • Managing the day-to-day activities of a combined science and engineering team within an Agile environment, but paying attention to the different timescales of development. • Hiring research scientist and engineers to continue to grow the team. • Coaching and developing scientists to maintain standards and to drive career growth for your direct reports. • Building a team culture around technical excellence and strong delivery. About the team The Seller Growth science team aims to provide data and science solutions to drive Seller growth and create better Seller experiences. We structure our science domain with three key themes and two horizontal components. We discover the opportunity space by identifying opportunities with unrealized potential, then generate actionable analytics to identify high value actions (HVAs) that unlock the opportunity space, and finally, empower Sellers with personalized Growth Plans and differentiated treatment that help them realize their potential.

Amazon.com strives to be Earth's most customer-centric company where people can find and discover anything they want to buy online. We hire the world's brightest minds, offering them a fast paced, technologically sophisticated and friendly work environment. Are you seeking an environment where you can drive innovation? Do you want to apply learning techniques and advanced mathematical modeling to solve real world problems? Do you want to play a key role in the future of Amazon's Retail business? This job for you! The Customer Behavior Analytics (CBA) team at Amazon is responsible for the architecture, design, implementation of tools used to understand customer behavior and value generation for all Amazon programs. Our vision is to ensure that every decision at Amazon is customer-obsessed and maximizes long-term free cash flow (LTFCF). To achieve this we build the best, unbiased and most trusted measures of incremental customer long-term value and make them universally adopted as the company standard for customer-obsessed decisions. Come and join us! Amazon’s CBA team is looking for Economists, who can work at the intersection of economics, statistics and machine learning; and leverage the power of big data to solve complex problems like long-term causal effect estimation. Key job responsibilities Economists at Amazon are expected to work directly with other Economists and senior management on key business problems in retail, international retail, cloud computing, third party merchants, search, Kindle, streaming video, and operations. Amazon economists will apply the frontier of economic thinking to market design, pricing, forecasting, program evaluation, online advertising and other areas. You will build econometric models, using our world class data systems, and apply economic theory to solve business problems in a fast moving environment. Economists at Amazon will be expected to develop new techniques to process large data sets, build trust in the techniques with rigorous science and validation, address quantitative problems, and contribute to design of automated systems around the company.

Amazon revolutionized customer service, now we are changing what customers expect from technical support. Device, Digital and Alexa Support (D2AS) is responsible for the Customer Service operations and solutions for all Amazon Devices and Digital products, from Kindle and Echo, to Amazon Music and Prime Video. We’re seeking an Applied Scientist to develop cutting-edge AI solutions leveraging Large Language Models (LLM), Machine Learning (ML) and Natural Language Processing (NLP) techniques to understand and resolve customer issues and provide earth's best customer service. We are looking for individuals with a passion for learning, researching, and deploying production-ready science solutions in a highly collaborative environment. We like to ideate, experiment, iterate, optimize and scale quickly, while thoughtfully balancing speed and quality If you have experience with two or more of the following: - Research and implementation of multi-turn task-oriented dialogue systems - Natural Language Understanding / Spoken Language Understanding - Information Retrieval, Question Answering, Semantic Representation - Zero-shot or Few-shot Learning - Crowdsourced NLU annotation best practices - Reinforcement Learning (preferably in an NLP application) - Computational Linguistics - Large scale text classification Then we want to hear from you! Key job responsibilities - Drive collaborative research and creative problem solving. - Apply scientific concepts to real-world business problems. - Create experiments and prototype implementations of new learning algorithms and prediction techniques. - Collaborate with engineering teams to design and implement software solutions for science problems - Constructively critique peer research and mentor junior s and engineers. A day in the life We thrive on solving challenging problems to innovate for our customers. By pushing the boundaries of technology, we create unparalleled experiences that enable us to rapidly adapt in a dynamic environment. Our decisions are guided by data, and we collaborate with engineering, science, and product teams to foster an innovative learning environment. 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! Benefits summary: 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: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan About the team We at D2AS strive to make digital experiences effortless for customers. Our goal is to anticipate, evaluate, prevent, and eliminate any effort required from customers. We achieve this by setting the strategy for digital support and accelerating the delivery of seamless support experiences across Amazon's digital products. Our team combines strategic thinking, technology expertise, and customer experience best practices. This ensures customers can easily get the most value from Amazon's digital offerings. We focus on providing the right support at the right time, tailored to each customer's needs. By eliminating friction and making support effortless, we enhance the overall customer experience.

Amazon's Global Transportation Services Network Design Analytics is seeking a Senior Applied Science Manager to build & lead an exceptional tech team in charge of devoloping the operations research models to design Amazon’s transportation network design with which we can keep offering the fastest and most cost-effective service to our customers. We are looking for a talented, organized, and customer-focused leader to head a multidisciplinary team with Applied/Research Science, Data Science, Data Engineering, and Business Intelligence branches, with a charter to build optimization models and heuristics, ML models to infer KPI, pipelines holding models’s infrastructures, and connecting the dots between real operations and models formulation. This role requires an individual with excellent team leadership skills, always-updated science breath/depth, outstanding business acumen, and an entrepreneurial spirit. We are looking for an experienced leader who is a self-starter comfortable with ambiguity, demonstrates strong attention to detail, and has the ability to work in a fast-paced and ever-changing environment. Key job responsibilities - Build the team. Lead and foster a highly talented group of applied/research/data scientists and data/business intel engineers that work together as a single unit. Establish internal and external talent acquisition opportunities. - See the big picture. Shape long term vision for Amazon's science-based operations modelling and optimization - Build strong collaborations. Partner with product, engineering, and science teams within Transportation and Supply Chain to deploy and connect models and services that connect different teams solutions at Amazon scale - Stay informed. Establish mechanisms to stay up to date on latest scientific advancements in local search, linear/integer programming, algorithms, machine learning, neural networks, probabilistic forecasting/modelling,. Identify opportunities to apply them to relevant supply chain business problems - Keep innovating for our customers. Foster an environment that promotes rapid experimentation, continuous learning, and incremental value delivery. About the team Within Global Transportation Services, the Network Design team leverages planet scale multi-modal data on Amazon shipments and capabilities to build advanced optimization and machine learning models. We preserve long term customer trust by ensuring Amazon's network is always as fast and cost-effective as possible.