Careers

We're seeking an Applied Scientist to lead and innovate in applying advanced AI technologies that will reshape how businesses sell on Amazon. Our team is passionate about leveraging Machine Learning, GenAI, and Agentic AI to help B2B sellers optimize their operations and drive growth. Join Amazon Business 3P (Third Party - Sellers) - a rapidly growing global organization where we innovate at the intersection of AI technology and B2B commerce. We're reimagining how sellers reach and serve business customers, creating intelligent solutions that help them grow their B2B business on Amazon. From AI-powered Seller Central tools to smart business certifications, dynamic pricing capabilities, and advanced analytics, we're transforming how B2B selling happens. As an Applied Scientist II on our AB 3P Tech team, you'll drive the development and implementation of state-of-the-art algorithms and models for supervised fine-tuning and reinforcement learning. You'll work with highly technical, entrepreneurial teams to: - Design and implement AI models that power the B2B selling experience - Lead the development of GenAI products that can handle Amazon-scale use cases - Drive research and implementation of advanced algorithms for human feedback and complex reasoning - Make strategic AI technology decisions and mentor technical talent - Own critical AI systems spanning from Seller Central to Amazon Business detail pages Join us in shaping the future of B2B selling - we're building applied AI solutions that businesses love and trust for their day-to-day success. If you are scrappy and bias for action is your favorite Leadership Principle, you'll fit right in as we innovate across the seller experience to create significant impact in this fast-growing business. Key job responsibilities Key job responsibilities: - Collaborate with cross-functional teams of engineers, product managers, and scientists to identify and solve complex problems in Gen AI - Design and execute experiments to evaluate the performance of different algorithms and models, and iterate quickly to improve results - Think big about the arc of development of Gen AI over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems - Communicate results and insights to both technical and non-technical audiences About the team At Amazon Business Third Party (AB3P) Tech, we're revolutionizing B2B e-commerce by empowering sellers in the business marketplace. Our scope spans the complete B2B selling journey, from Seller Central to Amazon Business detail pages, cart, and checkout for merchant-fulfilled offers. Our entrepreneurial culture and global reach define us. We develop features across seller experience, delivery, certifications, fees, registration, and analytics, collaborating with worldwide teams and leveraging advanced AI technologies to continuously innovate. Working in true Day 1 spirit, we build next-generation solutions that shape the future of B2B commerce. Join us in building next-generation solutions that shape the future of B2B commerce.

RBS (Retail Business Services) Tech team works towards enhancing the customer experience (CX) and their trust in product data by providing technologies to find and fix Amazon CX defects at scale. Our platforms help in improving the CX in all phases of customer journey, including selection, discoverability & fulfilment, buying experience and post-buying experience (product quality and customer returns). The team also develops GenAI platforms for automation of Amazon Stores Operations. As a Sciences team in RBS Tech, we focus on foundational ML research and develop scalable state-of-the-art ML solutions to solve the problems covering customer experience (CX) and Selling partner experience (SPX). We work to solve problems related to multi-modal understanding (text and images), task automation through multi-modal LLM Agents, supervised and unsupervised techniques, multi-task learning, multi-label classification, aspect and topic extraction for Customer Anecdote Mining, image and text similarity and retrieval using NLP and Computer Vision for product groupings and identifying duplicate listings in product search results. Key job responsibilities As an Applied Scientist, you will be responsible to design and deploy scalable GenAI, NLP and Computer Vision solutions that will impact the content visible to millions of customer and solve key customer experience issues. You will develop novel LLM, deep learning and statistical techniques for task automation, text processing, image processing, pattern recognition, and anomaly detection problems. You will define the research and experiments strategy with an iterative execution approach to develop AI/ML models and progressively improve the results over time. You will partner with business and engineering teams to identify and solve large and significantly complex problems that require scientific innovation. You will help the team leverage your expertise, by coaching and mentoring. You will contribute to the professional development of colleagues, improving their technical knowledge and the engineering practices. You will independently as well as guide team to file for patents and/or publish research work where opportunities arise. The RBS org deals with problems that are directly related to the selling partners and end customers and the ML team drives resolution to organization level problems. Therefore, the Applied Scientist role will impact the large product strategy, identifies new business opportunities and provides strategic direction which is very exciting.

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!

Amazon Industrial Robotics is seeking exceptional talent to help develop the next generation of advanced robotics systems that will transform automation at Amazon's scale. We're building revolutionary robotic systems that combine cutting-edge AI, sophisticated control systems, and advanced mechanical design to create adaptable automation solutions capable of working safely alongside humans in dynamic environments. This is a unique opportunity to shape the future of robotics and automation at unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic manipulation, locomotion, and human-robot interaction. This role presents an opportunity to shape the future of robotics through innovative applications of deep learning and large language models. At Amazon Industrial Robotics we leverage advanced robotics, machine learning, and artificial intelligence to solve complex operational challenges at unprecedented scale. Our fleet of robots operates across hundreds of facilities worldwide, working in sophisticated coordination to fulfill our mission of customer excellence. We are pioneering the development of robotics foundation models that: - Enable unprecedented generalization across diverse tasks - Enable unprecedented robustness and reliability, industry-ready - Integrate multi-modal learning capabilities (visual, tactile, linguistic) - Accelerate skill acquisition through demonstration learning - Enhance robotic perception and environmental understanding - Streamline development processes through reusable capabilities The ideal candidate will contribute to research that bridges the gap between theoretical advancement and practical implementation in robotics. You will be part of a team that's revolutionizing how robots learn, adapt, and interact with their environment. Join us in building the next generation of intelligent robotics systems that will transform the future of automation and human-robot collaboration. Key job responsibilities As an Applied Science Manager in the Foundations Model team, you will: - Build and lead a team of scientists and developers responsible for foundation model development - Define the right ‘FM recipe’ to reach industry ready solutions - Define the right strategy to ensure fast and efficient development, combining state of the art methods, research and engineering. - Lead Model Development and Training: Designing and implementing the model architectures, training and fine tuning the foundation models using various datasets, and optimize the model performance through iterative experiments - Lead Data Management: Process and prepare training data, including data governance, provenance tracking, data quality checks and creating reusable data pipelines. - Lead Experimentation and Validation: Design and execute experiments to test model capabilities on the simulator and on the embodiment, validate performance across different scenarios, create a baseline and iteratively improve model performance. - Lead Code Development: Write clean, maintainable, well commented and documented code, contribute to training infrastructure, create tools for model evaluation and testing, and implement necessary APIs - Research: Stay current with latest developments in foundation models and robotics, assist in literature reviews and research documentation, prepare technical reports and presentations, and contribute to research discussions and brainstorming sessions. - Collaboration: Work closely with senior scientists, engineers, and leaders across multiple teams, participate in knowledge sharing, support integration efforts with robotics hardware teams, and help document best practices and methodologies.

We are seeking an Applied Scientist to join our Generate AI Visual Media - Core Experiences Science team. This organization drives significant business value by revolutionizing how customers interact with product imagery and videos across Amazon. Working at the intersection of Computer Vision and Generative AI, you will help customers make confident purchase decisions through optimized visual content. Our goal is to transform shopping into a personalized journey of inspiration, discovery, and evaluation by helping customers evaluate how products will fit and flatter their unique self before they ship. In this role, you will be responsible for building scalable computer vision and machine learning (CVML) models, and automating their application and expansion to power customer-facing features. We are seeking domain expertise specifically in 3D Generative AI and Inverse Rendering. Relevant topics include Neural Fields, Implicit 3D Representations, NeRFs, Differentiable Rendering/Simulation, and Physically Based Rendering (PBR) Materials. We expect strong expertise at the intersection of Computer Graphics, Computer Vision, and Deep Learning. An inclination towards Generative AI, such as GANs, VQ-VAE/GAN, and Diffusion Models, is essential. Additionally, experience in application-specific domains such as Neural Avatars, Parametric Body Models, and Differentiable Rendering/Simulation will be highly advantageous. Key job responsibilities - Explore, collect, and process data - Frame and transform ambiguous business challenges into science hypotheses. Design and implement offline and online experiments to evaluate them - Develop prototypes to test new concepts/proposals for models and algorithms - Design and build automated, scalable pipelines to train and deploy ML models

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 team is currently looking for Senior Applied Scientists with a strong background in NLP and/or CV to design and develop ML solutions in the RAI space using generative AI across all languages and countries. A Senior Applied Scientist will be a tech lead for a team of exceptional scientists to develop novel algorithms and modeling techniques to advance the state of the art in NLP or CV related tasks. You will work in a hybrid, fast-paced organization where scientists, engineers, and product managers work together to build customer facing experiences. You will collaborate with and mentor other scientists to raise the bar of scientific research in Amazon. Your work will directly impact our customers in the form of products and services that make use of speech, language, and computer vision technologies. We are looking for a leader with strong technical experiences a passion for building scientific driven solutions in a fast-paced environment. You should have good understanding of Artificial Intelligence (AI), Natural Language Understanding (NLU), Machine Learning (ML), Dialog Management, Automatic Speech Recognition (ASR), and Audio Signal Processing where to apply them in different business cases. You leverage your exceptional technical expertise, a sound understanding of the fundamentals of Computer Science, and practical experience of building large-scale distributed systems to creating reliable, scalable, and high-performance products. In addition to technical depth, you must possess exceptional communication skills and understand how to influence key stakeholders. 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 as a leader, this may be the place for you. Key job responsibilities You'll lead the science solution design, run experiments, research new algorithms, and find new ways of optimizing customer experience. You set examples for the team on good science practice and standards. Besides theoretical analysis and innovation, you will work closely with talented engineers and ML scientists to put your algorithms and models into practice. Your work will directly impact the trust customers place in Alexa, globally. You contribute directly to our growth by hiring smart and motivated Scientists to establish teams that can deliver swiftly and predictably, adjusting in an agile fashion to deliver what our customers need. A day in the life You will be working with a group of talented scientists on researching algorithm and running experiments to test scientific proposal/solutions to improve our sensitive contents detection and mitigation. This will involve collaboration with partner teams including engineering, PMs, data annotators, and other scientists to discuss data quality, policy, and model development. You will mentor other scientists, review and guide their work, help develop roadmaps for the team. You work closely with partner teams across Alexa to deliver platform features that require cross-team leadership. About the hiring group About the team The mission of the Alexa Sensitive Content Intelligence (ASCI) team is to (1) minimize negative surprises to customers caused by sensitive content, (2) detect and prevent potential brand-damaging interactions, and (3) build customer trust through appropriate interactions on sensitive topics. The term “sensitive content” includes within its scope a wide range of categories of content such as offensive content (e.g., hate speech, racist speech), profanity, content that is suitable only for certain age groups, politically polarizing content, and religiously polarizing content. The term “content” refers to any material that is exposed to customers by Alexa (including both 1P and 3P experiences) and includes text, speech, audio, and video.

AWS Deep Science for Systems & Services is looking for a Sr. Manager, Applied Science who will lead a team of world class scientists to work on foundation models, large-scale representation learning, and distributed learning methods and systems. At AWS Deep Science for Systems & ServicesL you lead a team inventing, implementing, and deploying state of the art machine learning algorithms and systems. You will build prototypes and innovate on new representation learning solutions, interact closely with our customers and with the academic and research communities. You will be at the heart of a growing and exciting focus area for AWS and work with other acclaimed engineers and world famous scientists. Large-scale foundation models have been the powerhouse in many of the recent advancements in computer vision, natural language processing, automatic speech recognition, recommendation systems, and time series modeling. Developing such models requires not only skillful modeling in individual modalities, but also understanding of how to synergistically combine them, and how to scale the modeling methods to learn with huge models and on large datasets. Join us to work as an integral part of a team that has diverse experiences in this space. We actively work on these areas: - Hardware-informed efficient model architecture, training objective and curriculum design - Distributed training, accelerated optimization methods - Continual learning, multi-task/meta learning - Reasoning, interactive learning, reinforcement learning - Robustness, privacy, model watermarking - Model compression, distillation, pruning, sparsification, quantization

We are looking for a Data Scientist to join our Prime Video team in Israel, focusing on personalizing customer experiences through Search and Recommendations. Our team leverages Machine Learning (ML) to deliver tailored content discovery, helping millions of customers find the entertainment they love. You will work on large-scale experimentation, measurement frameworks, and data-driven decision-making that directly shapes how customers interact with Prime Video. Key job responsibilities - Design metrics frameworks and evaluation systems to measure the quality, performance, and reliability of algorithmic solutions - Lead the design, execution, and analysis of A/B tests to validate product hypotheses and quantify customer impact - Communicate analytical findings and recommendations clearly to both technical teams and business stakeholders, driving data-informed decisions - Partner with Applied Scientists, Software Engineers, and Product Managers to define requirements, evaluate models, and drive data-informed product decisions - Act as the subject matter expert for data structures, metrics definitions, and analytical best practices - Identify opportunities for improving customer experience through deep-dive analyses of user behavior and algorithm performance

Are you a scientist interested in pushing the state of the art in Information Retrieval, Large Language Models and Recommendation Systems? Are you interested in innovating on behalf of millions of customers, helping them accomplish their every day goals? Do you wish you had access to large datasets and tremendous computational resources? Do you want to join a team of capable scientist and engineers, building the future of e-commerce? Answer yes to any of these questions, and you will be a great fit for our team at Amazon. Our team is part of Amazon’s Personalization organization, a high-performing group that leverages Amazon’s expertise in machine learning, generative AI, large-scale data systems, and user experience design to deliver the best shopping experiences for our customers. Our team is building next-generation personalization systems powered by Large Language Models. We are tackling novel research challenges to help customers discover products they'll love - at Amazon scale and latency requirements. We are a team uniquely placed within Amazon, to have a direct window of opportunity to influence how customers will think about their shopping journey in the future. As an Applied Science Manager, you will lead a team of scientists working at the frontier of LLM-based personalization. You will set the technical vision, drive the research agenda, and ensure your team delivers production-ready solutions. You will hire, mentor, and develop world-class scientists while fostering a culture of innovation and scientific rigor. You will partner closely with engineering and product teams to translate ambitious research into customer-facing impact, and represent your team's work to senior leadership. Please visit https://www.amazon.science for more information.

Are you fascinated by the power of Natural Language Processing (NLP) and Large Language Models (LLM) to transform the way we interact with technology? Are you passionate about applying advanced machine learning techniques to solve complex challenges in the e-commerce space? If so, Amazon's International Seller Services team has an exciting opportunity for you as an Applied Scientist. At Amazon, we strive to be Earth's most customer-centric company, where customers can find and discover anything they want to buy online. Our International Seller Services team plays a pivotal role in expanding the reach of our marketplace to sellers worldwide, ensuring customers have access to a vast selection of products. As an Applied Scientist, you will join a talented and collaborative team that is dedicated to driving innovation and delivering exceptional experiences for our customers and sellers. You will be part of a global team that is focused on acquiring new merchants from around the world to sell on Amazon’s global marketplaces around the world. Join us at the Central Science Team of Amazon's International Seller Services and become part of a global team that is redefining the future of e-commerce. With access to vast amounts of data, technology, and a diverse community of talented individuals, you will have the opportunity to make a meaningful impact on the way sellers engage with our platform and customers worldwide. Together, we will drive innovation, solve complex problems, and shape the future of e-commerce. Please visit https://www.amazon.science for more information Key job responsibilities - Apply your expertise in LLM models to design, develop, and implement scalable machine learning solutions that address complex language-related challenges in the international seller services domain. - Collaborate with cross-functional teams, including software engineers, data scientists, and product managers, to define project requirements, establish success metrics, and deliver high-quality solutions. - Conduct thorough data analysis to gain insights, identify patterns, and drive actionable recommendations that enhance seller performance and customer experiences across various international marketplaces. - Continuously explore and evaluate state-of-the-art NLP techniques and methodologies to improve the accuracy and efficiency of language-related systems. - Communicate complex technical concepts effectively to both technical and non-technical stakeholders, providing clear explanations and guidance on proposed solutions and their potential impact. - Mentor and guide team of Applied Scientists from technical and project advancement stand point - Contribute research to science community and conference quality level papers.