Careers

The Artificial General Intelligence (AGI) team is looking for a highly skilled and experienced Applied Scientist, to support the development and implementation of state-of-the-art algorithms and models for supervised fine-tuning and reinforcement learning through human feedback and and complex reasoning; with a focus across text, image, and video modalities. As an Applied Scientist, you will play a critical role in supporting the development of Generative AI (Gen AI) technologies that can handle Amazon-scale use cases and have a significant impact on our customers' experiences. 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, including through presentations and written reports

The Sponsored Products and Brands (SPB) team at Amazon Ads is re-imagining the advertising landscape through state-of-the-art generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. The Off-Search team within Sponsored Products and Brands (SPB) is focused on building delightful ad experiences across various surfaces beyond Search on Amazon—such as product detail pages, the homepage, and store-in-store pages—to drive monetization. Our vision is to deliver highly personalized, context-aware advertising that adapts to individual shopper preferences, scales across diverse page types, remains relevant to seasonal and event-driven moments, and integrates seamlessly with organic recommendations such as new arrivals, basket-building content, and fast-delivery options. To execute this vision, we work in close partnership with Amazon Stores stakeholders to lead the expansion and growth of advertising across Amazon-owned and -operated pages beyond Search. We operate full stack—from backend ads-retail edge services, ads retrieval, and ad auctions to shopper-facing experiences—all designed to deliver meaningful value. Curious about our advertising solutions? Discover more about Sponsored Products and Sponsored Brands to see how we’re helping businesses grow on Amazon.com and beyond! Key job responsibilities This role will be pivotal in redesigning how ads contribute to a personalized, relevant, and inspirational shopping experience, with the customer value proposition at the forefront. Key responsibilities include, but are not limited to: - Contribute to the design and development of GenAI, deep learning, multi-objective optimization and/or reinforcement learning empowered solutions to transform ad retrieval, auctions, whole-page relevance, and/or bespoke shopping experiences. - Collaborate cross-functionally with other scientists, engineers, and product managers to bring scalable, production-ready science solutions to life. - Stay abreast of industry trends in GenAI, LLMs, and related disciplines, bringing fresh and innovative concepts, ideas, and prototypes to the organization. - Contribute to the enhancement of team’s scientific and technical rigor by identifying and implementing best-in-class algorithms, methodologies, and infrastructure that enable rapid experimentation and scaling. - Mentor and grow junior scientists and engineers, cultivating a high-performing, collaborative, and intellectually curious team. A day in the life As an Applied Scientist on the Sponsored Products and Brands Off-Search team, you will contribute to the development in Generative AI (GenAI) and Large Language Models (LLMs) to revolutionize our advertising flow, backend optimization, and frontend shopping experiences. This is a rare opportunity to redefine how ads are retrieved, allocated, and/or experienced—elevating them into personalized, contextually aware, and inspiring components of the customer journey. You will have the opportunity to fundamentally transform areas such as ad retrieval, ad allocation, whole-page relevance, and differentiated recommendations through the lens of GenAI. By building novel generative models grounded in both Amazon’s rich data and the world’s collective knowledge, your work will shape how customers engage with ads, discover products, and make purchasing decisions. If you are passionate about applying frontier AI to real-world problems with massive scale and impact, this is your opportunity to define the next chapter of advertising science. About the team The Off-Search team within Sponsored Products and Brands (SPB) is focused on building delightful ad experiences across various surfaces beyond Search on Amazon—such as product detail pages, the homepage, and store-in-store pages—to drive monetization. Our vision is to deliver highly personalized, context-aware advertising that adapts to individual shopper preferences, scales across diverse page types, remains relevant to seasonal and event-driven moments, and integrates seamlessly with organic recommendations such as new arrivals, basket-building content, and fast-delivery options. To execute this vision, we work in close partnership with Amazon Stores stakeholders to lead the expansion and growth of advertising across Amazon-owned and -operated pages beyond Search. We operate full stack—from backend ads-retail edge services, ads retrieval, and ad auctions to shopper-facing experiences—all designed to deliver meaningful value. Curious about our advertising solutions? Discover more about Sponsored Products and Sponsored Brands to see how we’re helping businesses grow on Amazon.com and beyond!

The Artificial General Intelligence (AGI) team is looking for a highly skilled and experienced Applied Scientist, to support the development and implementation of state-of-the-art algorithms and models for supervised fine-tuning and reinforcement learning through human feedback and and complex reasoning; with a focus across text, image, and video modalities. As an Applied Scientist, you will play a critical role in supporting the development of Generative AI (Gen AI) technologies that can handle Amazon-scale use cases and have a significant impact on our customers' experiences. 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, including through presentations and written reports About the team We are passionate scientists dedicated to pushing the boundaries of innovation in Gen AI with focus on Software Development use cases for LLMs.

The Artificial General Intelligence (AGI) team is looking for a highly skilled and experienced Sr. Applied Scientist, to support the development and implementation of state-of-the-art algorithms and models for supervised fine-tuning and reinforcement learning through human feedback and and complex reasoning; with a focus across text, image, and video modalities. As an Sr. Applied Scientist, you will play a critical role in supporting the development of Generative AI (Gen AI) technologies that can handle Amazon-scale use cases and have a significant impact on our customers' experiences. 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, including through presentations and written reports About the team We are passionate scientists dedicated to pushing the boundaries of innovation in Gen AI with focus on Software Development use cases.

We are seeking an exceptional Senior Applied Scientist specializing in ML Systems, training, and inference optimization to join DS3. This role requires deep expertise in performance engineering, kernel development, distributed systems optimization, and AI workload optimization across heterogeneous compute platforms. You will invent and implement novel optimization techniques that directly impact the performance and cost-efficiency of ML training and inference for AWS customers worldwide. As a Senior Applied Scientist in DS3, you will work at the lowest levels of the software stack—writing custom CUDA kernels, optimizing PTX assembly, developing high-performance operators for GPUs and AWS Neuron, designing efficient communication patterns for multi-GPU and multi-node training, and inventing new algorithmic approaches to accelerate transformer models and emerging architectures. Your work will span from single-node inference optimization to large-scale distributed training systems, influencing the design of AWS training and inference services and setting new standards for ML systems performance across the industry. Deep Science for Systems and Services (DS3) is a part of AWS Utility Computing (UC) which provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services. Key job responsibilities Systems-Level Scientific Innovation: Design and implement novel kernel-level optimizations for ML inference and training workloads, including custom CUDA kernels, PTX-level optimizations, and cross-platform acceleration for CUDA and AWS Neuron SDK. Performance Engineering Leadership: Drive 2-10× performance improvements in latency, throughput, and memory efficiency for production ML inference & training systems through systematic profiling, analysis, and optimization. Cross-Platform Optimization: Develop and port high-performance ML operators across GPUs, AWS Inferentia/Trainium, and emerging AI accelerators, ensuring optimal performance on each platform. Product-Level Impact: Lead the design, implementation, and delivery of scientifically-complex optimization solutions that directly improve customer experience and reduce AWS operational costs at scale. Scientific Rigor: Produce technical documentation and internal research reports demonstrating the correctness, efficiency, and scalability of your optimizations. Contribute to external publications when aligned with business needs. Technical Leadership: Influence your team's technical direction and scientific roadmap. Build consensus across engineering and science teams on optimization strategies and architectural decisions. Mentorship & Knowledge Sharing: Actively mentor junior scientists and engineers on performance engineering best practices, kernel development, and systems-level optimization techniques. About the team Deep Science for Systems and Services (DS3) is a science organization within AWS Compute & ML Services focused on advancing AI/ML technologies at the systems level. Our team works at the intersection of machine learning and high-performance computing, developing optimizations for large model inference across diverse hardware platforms. We push the boundaries of what's possible in ML inference performance, working directly with CUDA, AWS Neuron, and other low-level compute abstractions to deliver industry-leading latency, throughput, and cost-performance for AWS customers deploying AI at scale. About AWS 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. 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 AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do. 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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

The Artificial General Intelligence (AGI) team is seeking a dedicated, skilled, and innovative Applied Scientist with a robust background in deep learning, to build industry-leading technology with Large Language Models (LLMs) and multimodal systems. Key job responsibilities As part of the AGI team, the Applied Scientist will collaborate closely with talented colleagues to lead the development of advanced approaches and modeling techniques, driving forward the frontier of LLM technology. This includes innovating model-in-the-loop and human-in-the-loop approaches to ensure the collection of high-quality data, safeguarding data privacy and security for LLM training, and more. The Applied Scientist will also have a direct impact on enhancing customer experiences through state-of-the-art products and services. A day in the life The Applied Scientist with the AGI team will support the science solution design, run experiments, research new algorithms, and find new ways of optimizing the customer experience; while setting examples for the team on good science practice and standards. Besides theoretical analysis and innovation, an Applied Scientist will also work closely with talented engineers and scientists to put algorithms and models into practice. The ideal candidate should be passionate about delivering experiences that delight customers and creating robust solutions. They will also create reliable, scalable and high-performance products that require exceptional technical expertise, and a sound understanding of Machine Learning.

AWS Agentic AI is looking for a world-class Applied Scientist with a strong deep learning background to help build industry-leading Agentic AI (models, systems, and applications). Our mission is to provide a delightful experience to Amazon’s customers by pushing the envelope in Natural Language Understanding (NLU), AI assisted code development, reasoning and planning with LLMs, LLM training and fine-tuning, and Applied Machine Learning (ML). As part of our AI team in Amazon AWS, you will work alongside internationally recognized experts to develop novel algorithms and modeling techniques to advance the state-of-the-art in Agentic AI. Your work will directly impact millions of our customers in the form of products and services that make use AI technology. You will gain hands on experience with Amazon’s heterogeneous text, structured data sources, and large-scale computing resources to accelerate advances in language understanding. We are looking for experienced scientists who can make complex, autonomous systems understandable and debuggable through intelligent instrumentation and simulation. Key job responsibilities - Develop technical breakthroughs in agentic infrastructure and applications - Mentor and guide junior scientists. - Manage a small team of scientists - Develop technology strategy and roadmap supporting product development - Develop prototypes for key technology, oversee the productization of the prototype, and develop critical assessment for the prototype - Write technical reports summarizing R&D progresses and communicate such progresses with stakeholders - Engage with cross-functional stakeholders to drive alignment and outcomes About the team The Amazon Web Services (AWS) Agentic AI team uses generative AI and foundation models to advance application development. In the space of software development and life cycle management, we see the application of AI anywhere: from the IDE to web-based tools and services, AI helps engineers work many applications. We explore new technologies and find creative solutions. Curiosity and an explorative mindset can find a place here to impact the life of engineers around the world. If you are excited about this space and want to enlighten your peers with new capabilities, this is the team for you.

Are you a scientist interested in pushing the state of the art in machine learning and recommendation systems? Are you interested in working on novel ideas that can positively impact millions of customers? Do you wish you had access to large datasets and tremendous computational resources? 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, big data, distributed systems, and user experience design to deliver the best shopping experiences for our customers. Our team builds large-scale machine-learning solutions that delight customers with personzlized content recommendations, at the right time, with the right level of explanation. As an Applied Scientist in our team, you will be responsible for the research, design, and development of new AI technologies for personalization. You will adopt or invent new machine learning and analytical techniques in the realm of recommendations and large language models. You will collaborate with scientists, engineers, and product partners locally and abroad. Your work will include inventing, experimenting with, and launching new features, products and systems. Please visit https://www.amazon.science for more information.

Do you want a role with deep meaning and the ability to make a major impact? As part of Intelligent Talent Acquisition (ITA), you'll have the opportunity to reinvent the hiring process and deliver unprecedented scale, sophistication, and accuracy for Amazon Talent Acquisition operations. ITA is an industry-leading people science and technology organization made up of scientists, engineers, analysts, product professionals and more, all with the shared goal of connecting the right people to the right jobs in a way that is fair and precise. Last year we delivered over 6 million online candidate assessments, and helped Amazon deliver billions of packages around the world by making it possible to hire hundreds of thousands of workers in the right quantity, at the right location and at exactly the right time. You’ll work on state-of-the-art research, advanced software tools, new AI systems, and machine learning algorithms, leveraging Amazon's in-house tech stack to bring innovative solutions to life. Join ITA in using technologies to transform the hiring landscape and make a meaningful difference in people's lives. Together, we can solve the world's toughest hiring problems. The conversion domain ensures the necessary labor force to fulfill customer orders across global operations. The Senior Applied Scientist serves as the science leader for the conversion domain, supporting leadership teams across North America and Europe while providing guidance to generation, hiring event, and coordination teams. The Senior Applied Scientist optimizes recruitment processes for specific demands within cost constraints across various markets, each with distinct deadlines. As the technical lead, you own signals that coordinate multiple functions: determining optimal job postings, coordinating with marketing for lead generation, managing hiring event appointments, and implementing candidate management strategies when needed. The Senior Applied Scientist develops sophisticated theory-based decision models to create a scalable framework that balances business and candidate preferences, extending beyond simple conversion predictions. The role requires careful consideration of local regulations and market-specific requirements. The Senior Applied Scientist owns scientific models across multiple countries, with expertise in stochastic dynamic programming, machine learning with panel data, survival analysis, and causal inference from non-experimental data. They optimize job application release timing and predict conversion rates while designing experiments for new mechanism rollouts. The Senior Applied Scientist leads automation of hiring processes through AI systems, developing decision-making models built on economic theory principles while ensuring system trustworthiness through automated reasoning and formal verification. Key job responsibilities • Own science models across North America and Europe, that managing job posting optimization, candidate management, and recruitment coordination. • Create data-driven models that optimize candidate experience and business outcomes while considering market-specific requirements and regulations. • Manage conversion models, application demand forecasting, and optimization algorithms using machine learning, survival analysis, and causal inference techniques. • Lead development of AI systems that automate recruitment decisions while ensuring reliability and alignment with business objectives. • Plan and implement controlled experiments to test new recruitment mechanisms and optimize hiring processes across different markets. About the team Intelligent Talent Acquisition (ITA) is Amazon's internal people science and technology organization with the singular mission of connecting the right people to the right jobs through fair and precise methods across Amazon's global operations. This strategic hiring approach directly contributes to Amazon's ability to deliver billions of packages worldwide. Through data-driven insights and innovative technology, ITA continues to enhance Amazon's hiring processes, assessment systems, and talent acquisition capabilities, with scientific breakthroughs affecting thousands of hiring decisions and millions in operational efficiency across 200+ job families globally.

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 a Senior 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 Senior Applied Scientist role will impact the large product strategy, identifies new business opportunities and provides strategic direction which is very exciting.