Careers

Lead the development of cutting-edge AI models to power Amazon's eCommerce ontology - the authoritative source of product knowledge driving exceptional customer experiences. Applied Scientists in this role solve problems related to product classification, attribute extraction, ontology modeling, data integration and enrichment, and scalable knowledge services. It's challenging due to the vast scale, heterogeneous data sources, and evolving domains, but exciting for pushing boundaries in ML, NLP, and knowledge representation research. If you're passionate about driving innovation at scale, we want to hear from you! Key job responsibilities - Lead the research and development of novel AI solutions to enrich and curate Amazon's product ontology (Product Knowledge) at scale - Develop scalable data processing pipelines and architectures to ingest, transform, and enrich product data from various sources (seller listings, customer reviews, etc.) - Collaborate with engineers to design and implement robust services - Work closely with product managers, stakeholders, and subject matter experts to identify opportunities for innovation and drive the roadmap for Product Knowledge - Mentor and upskill junior scientists and engineers, fostering a culture of continuous learning and knowledge sharing - Communicate complex technical concepts and research findings effectively to diverse audiences, including leadership, cross-functional teams, and the wider scientific community - Stay up-to-date with the latest advancements in machine learning, natural language processing, knowledge representation, and related fields, and identify opportunities to apply them to Product Knowledge A day in the life The Amazon product ontology is a structured knowledge base representing product types, attributes, classes, and relationships. It standardizes product data, enabling enhanced customer experiences through improved search and recommendations, streamlined selling processes, and internal data enrichment across Amazon's eCommerce ecosystem. You will work with following stakeholders: - Product Managers represent customer experiences and selling partner experiences - Category Leaders (e.g., apparel, electronics) provide domain knowledge and guidance as subject matter experts - Engineers build and maintain data pipelines and services in production - Ontologists design data models and define guidelines - Other Applied Scientists collaborate on research and innovation About the team The Product Knowledge team at Amazon is dedicated to creating the industry-standard eCommerce product and services ontology. Our diverse team of applied scientists, engineers, ontologists and subject matter experts build a comprehensive ontology enabling exceptional customer and selling partner experiences through high-quality, contextual product knowledge at scale.

Amazon's Devices Economic Value team enables measurement and optimization of Amazon Devices long-term value to help Amazon build better products for their customers. Delivering lasting value to customers is in Amazon's DNA and we are at the core of how the Devices business prioritizes its investments in innovation and optimization on behalf of customers. Join us to be a part of the team that is at the core of understanding how Amazon Devices drive deeper customer engagement and helps the business make decisions about how to optimize and balance between short term monetization and long term value creation for Amazon Device users. We are seeking a skilled Senior Applied Scientist to build the future of long term value measurement and optimization for Amazon Devices. About you: We are looking for a talented Senior Applied Scientist to partner with a highly-talented team. You will work closely with engineering and multiple partner teams to continuously identify opportunities to enable and accelerate impactful business initiatives related to measurement and optimization of Devices long-term value. Strong technical skills, judgment and communication skills, and continuous focus on the actionability of our models and insights for our customers are essential for the success in this role. About us together: We're going to help Amazon make better decisions in our Devices business by measuring the long-term value generated via purchase and engagement with devices and integrating it into decision making across the whole business ranging from high level strategic decisions to production level optimizations in promotions, pricing and marketing. Our work will inform some of the biggest decisions in the Devices business. We have decades of combined experience in many areas of science, product and engineering so it's a great environment in which to learn and grow. Optimization for long-term value is one of the most challenging areas of research and development today and this is a chance to learn and enhance how it works in a company that keeps this focus at its core. The candidate's responsibilities will include: - Build Machine Learning models, conduct statistical/machine learning analyses, or design experiments to measure the value of the business and its many features - Partner closely with Business, Finance, Science, and Tech partners to implement production solutions - Independently identify new opportunities for leveraging science insights and models in the Devices business - Write both technical science papers and business-facing documents to clearly explain complex technical concepts

The Applied Scientist will play a critical role in the research, develop, and implementation of solutions to key challenges in developing conversational AI systems that can understand and communicate with customers in a natural and contextually appropriate manner. This involves tackling complex problems in areas such as multi-turn dialogue management, knowledge grounding, and open-ended generation. Key job responsibilities 1. Research and development of LLM-based chatbots and conversational AI systems for customer service applications. 2. Design and implement state-of-the-art NLP and ML models for tasks such as language understanding, dialogue management, and response generation. 3. Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to integrate LLM-based solutions into Amazon's customer service platforms. 4. Develop and implement strategies for data collection, annotation, and model training to ensure high-quality and robust performance of the chatbots. 5. Conduct experiments and evaluations to measure the performance of the developed models and systems, and identify areas for improvement. 6. Stay up-to-date with the latest advancements in NLP, LLMs, and conversational AI, and explore opportunities to incorporate new techniques and technologies into Amazon's customer service solutions. 7. Collaborate with internal and external research communities, participate in conferences and publications, and contribute to the advancement of the field. 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 Join our team of scientists and engineers who develop and deploy LLM-based Conversational AI systems to enhance Amazon's customer service experience and effectiveness. We work on innovative solutions that help customers solve their issues and get their questions answered efficiently, and associate-facing products that support our customer service associate workforce.

Amazon’s Last Mile Team is looking for a passionate individual with strong optimization and analytical skills to join its Last Mile Science team in the endeavor of designing and improving the most complex planning of delivery network in the world. Last Mile builds global solutions that enable Amazon to attract an elastic supply of drivers, companies, and assets needed to deliver Amazon's and other shippers' volumes at the lowest cost and with the best customer delivery experience. Last Mile Science team owns the core decision models in the space of jurisdiction planning, delivery channel and modes network design, capacity planning for on the road and at delivery stations, routing inputs estimation and optimization. Our research has direct impact on customer experience, driver and station associate experience, Delivery Service Partner (DSP)’s success and the sustainable growth of Amazon. Optimizing the last mile delivery requires deep understanding of transportation, supply chain management, pricing strategies and forecasting. Only through innovative and strategic thinking, we will make the right capital investments in technology, assets and infrastructures that allows for long-term success. Our team members have an opportunity to be on the forefront of supply chain thought leadership by working on some of the most difficult problems in the industry with some of the best product managers, scientists, and software engineers in the industry. Key job responsibilities Candidates will be responsible for developing solutions to better manage and optimize delivery capacity in the last mile network. The successful candidate should have solid research experience in one or more technical areas of Operations Research or Machine Learning. These positions will focus on identifying and analyzing opportunities to improve existing algorithms and also on optimizing the system policies across the management of external delivery service providers and internal planning strategies. They require superior logical thinkers who are able to quickly approach large ambiguous problems, turn high-level business requirements into mathematical models, identify the right solution approach, and contribute to the software development for production systems. To support their proposals, candidates should be able to independently mine and analyze data, and be able to use any necessary programming and statistical analysis software to do so. Successful candidates must thrive in fast-paced environments, which encourage collaborative and creative problem solving, be able to measure and estimate risks, constructively critique peer research, and align research focuses with the Amazon's strategic needs. As an applied scientist, you will also help coach/mentor junior scientists in the team.

Are you interested in the world's largest Cloud Network? Are you interested in applying new methods to extremely hard problems such as anomaly detection to have a lasting impact on business? Do you want to play a key role in the future of AWS's infrastructure? Come and join us! The Fleet Orchestration and Release Automation team is looking for an Applied Scientist Scientists to join our team. Our team owns multiple services that drive the decision-making behind the world's largest Network, and we are looking for excellent Scientists that can help us answer tough and ambiguous questions. Working collaboratively, you will improve and develop solutions to complex problems, such as identifying anomalies in the Network performance across Data-Centers worldwide, or automating the monitoring process of production network after OS or configuration deployments. You will work with a team of Engineers among others to test your solutions and push them into production so the business can meet its goals. You will be the POC for Science based innovation in the org. 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. A day in the life You must ensure our solutions meet the needs of our most important customers. You will work with customers to gather requirements, understand the space and impact, generate and test end-to-end proposals to carry the project through all the development stages. You’ll develop algorithms that enable Network Engineers to develop, monitor and operate robust, high-quality networks safely, securely, and reliably deploy it. You will have an opportunity to work directly with complex and high volume data and models to analyze network performance intelligently. You will use your strong leadership and communication skills to educate other team members, provide training and support for our products/models/technologies. You will have access to senior leadership and engineering staff. About the team We have created a new team that will own several new highly-visible initiatives and goals that will impact the whole organization as well as benefit across orgs. This includes developing and integrating various science based software solutions and collaborating with multiple teams and customers in order to achieve the goal of building software systems to deploy OS and config changes to the AWS datacenter network reliably. Our goal is to automate the process of identifying regressions in the network allowing teams to take action on it immediately with the long-term goal of providing specific root cause for regressions observed in network performance. 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 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 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 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. Working at AWS in the Core Networking Team • Meet Matt, Director, Core Networking --- https://youtu.be/DqTStjRtjX4

We’re building a foundational LLM for Amazon Stores that fuses general world knowledge with Amazon e-commerce domain knowledge to provide new and improved shopping experiences for our customers. We 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, engineers, and technical program managers (TPM) 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!

Have you ever ordered a product on Amazon and when that box with the smile arrived you wondered how it got to you so fast? Have you wondered where it came from and how much it cost Amazon to deliver it to you? If so, Amazon Logistics (AMZL), Last Mile team is for you. We manage the delivery of tens of millions of products every week to Amazon’s customers, achieving on-time delivery in a cost-effective manner to deliver a smile for our customers. As part of Amazon Last Mile Execution Analytics organization, the Data Scientist will work closely with other research scientists, machine learning experts, and economists to design and run experiments, create analyses, carry over solutions from other regions, and find new ways to improve last mile analytics to optimize the Customer experience. The Scientist will partner with technology and product leaders to solve business and technology problems using scientific approaches to build new services that surprise and delight our customers. They also work on cross-disciplinary, cross-regions efforts with other scientists within Amazon. We are seeking candidates with robust skills in Optimization modeling (Mixed Integer Programming, Dynamic Programming, Decomposition Methods), Python coding, data collection, and analysis. Background in Machine Learning or Economics would be advantageous. The ideal candidate should possess the ability to interpret regression model coefficients in non-mathematical terms, familiarity with various probability distributions, and the capability to elucidate how actions taken by business partners influence their desired outcomes. Strong communication skills to articulate complex analytical concepts to non-technical stakeholders. Key job responsibilities - Design and develop advanced mathematical, optimization models and apply them to define strategic and tactical needs and drive the appropriate business and technical solutions in the areas of routing planning, supply chain optimization, network optimization, economics, and control theory. - Apply mathematical optimization and control techniques (linear, quadratic, SOCP, robust, stochastic, dynamic, mixed-integer programming, network flows, nonlinear, nonconvex programming, decomposition methods, model predictive control) and algorithms to design optimal or near optimal solution methodologies to be used by in-house decision support tools and software. - Research, prototype, simulate, and experiment with these models by using modeling languages such as Python or R; participate in the production level deployment. - Create, enhance, and maintain technical documentation - Present to other Scientists, Product, and Software Engineering teams, as well as Stakeholders. - Lead project plans from a scientific perspective by managing product features, technical risks, milestones and launch plans. - Influence organization's long-term roadmap and resourcing, onboard new technologies onto Science team's toolbox, mentor other Scientists.

Join an innovative team of scientists and engineers who use machine learning and statistical techniques to create state-of-the-art solutions for providing better value to Amazon's customers. Key job responsibilities “Amazon Science gives you insight into the company’s approach to customer-obsessed 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 Do you want to join an innovative team of scientists and engineers who use machine learning and statistical techniques to create state-of-the-art solutions for providing better value to Amazon's customers? Do you want to build advanced algorithmic systems that help optimize millions of transactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data to solve real world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Machine Learning team for our International Consumer Businesses. The team builds the next generation of Machine Learning solutions for a wide spectrum of problems by leveraging generative-AI and LLMs, in areas such as Recommendations, Search Relevance, Catalog Quality, Online Ads, Pricing, Demand/Forecasting, Computer Vision, and Conversational Systems. A day in the life Build advanced algorithmic systems that help optimize millions of transactions every day. About the team The team builds the next generation of Machine Learning services for a wide spectrum of problems in areas such as Recommendations, Search Relevance, Computer Vision, Catalog Quality, Online Ads, Pricing, Demand/Forecasting, and Conversational Systems.

Our customers have immense faith in our ability to deliver packages timely and as expected. A well planned network seamlessly scales to handle millions of package movements a day. It has monitoring mechanisms that detect failures before they even happen (such as predicting network congestion, operations breakdown), and perform proactive corrective actions. When failures do happen, it has inbuilt redundancies to mitigate impact (such as determine other routes or service providers that can handle the extra load), and avoids relying on single points of failure (service provider, node, or arc). Finally, it is cost optimal, so that customers can be passed the benefit from an efficiently set up network. Amazon Shipping is hiring Applied Scientists to help improve our ability to plan and execute package movements. As an Applied Scientist in Amazon Shipping, you will work on multiple challenging machine learning problems spread across a wide spectrum of business problems. You will build ML models to help our transportation cost auditing platforms effectively audit off-manifest (discrepancies between planned and actual shipping cost). You will build models to improve the quality of financial and planning data by accurately predicting ship cost at a package level. Your models will help forecast the packages required to be pick from shipper warehouses to reduce First Mile shipping cost. Using signals from within the transportation network (such as network load, and velocity of movements derived from package scan events) and outside (such as weather signals), you will build models that predict delivery delay for every package. These models will help improve buyer experience by triggering early corrective actions, and generating proactive customer notifications. Your role will require you to demonstrate Think Big and Invent and Simplify, by refining and translating Transportation domain-related business problems into one or more Machine Learning problems. You will use techniques from a wide array of machine learning paradigms, such as supervised, unsupervised, semi-supervised and reinforcement learning. Your model choices will include, but not be limited to, linear/logistic models, tree based models, deep learning models, ensemble models, and Q-learning models. You will use techniques such as LIME and SHAP to make your models interpretable for your customers. You will employ a family of reusable modelling solutions to ensure that your ML solution scales across multiple regions (such as North America, Europe, Asia) and package movement types (such as small parcel movements and truck movements). You will partner with Applied Scientists and Research Scientists from other teams in US and India working on related business domains. Your models are expected to be of production quality, and will be directly used in production services. You will work as part of a diverse data science and engineering team comprising of other Applied Scientists, Software Development Engineers and Business Intelligence Engineers. You will participate in the Amazon ML community by authoring scientific papers and submitting them to Machine Learning conferences. You will mentor Applied Scientists and Software Development Engineers having a strong interest in ML. You will also be called upon to provide ML consultation outside your team for other problem statements. If you are excited by this charter, come join us!

The Central Science Team within Amazon’s People Experience and Technology org (PXTCS) 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. We are an interdisciplinary team, which combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal. We are looking for an economist with expertise in applying causal inference methods, especially experimental design to topics in labor, personnel, education, or behavioral economics. We are particularly interested in candidates with experience applying these skills to strategic problems with significant business and/or social policy impact. The candidate will work with economists and engineers to estimate and validate their models on large scale data, and will help business partners turn the results of their analysis into policies, programs, and actions that have a major impact on Amazon’s business and its workforce. We are looking for a creative thinker who can combine a strong economic toolbox with a desire to learn from others, and who knows how to execute and deliver on big ideas. Ideal candidates will own key inputs to all stages of research projects, including model development, survey administration, experimental design, and data analysis. They will be customer-centric, working closely with business partners to define key research questions, communicate scientific approaches and findings, listen to and incorporate partner feedback, and deliver successful solutions.