Careers

Do you want to join an innovative team of scientists applying machine learning and advanced statistical techniques to protect Amazon customers and enable a trusted eCommerce experience? Are you excited about modeling terabytes of data and building state-of-the-art algorithms to solve complex, real-world fraud and risk challenges? Do you enjoy owning end-to-end machine learning problems, directly influencing customer experience and company profitability, while collaborating in a diverse, high-performing team? If so, the Amazon Buyer Risk Prevention (BRP) Machine Learning team may be the right fit for you. We are seeking an Applied Scientist to design, develop, and deploy advanced algorithmic systems that safeguard millions of transactions every day. In this role, you will independently drive model development from problem formulation to production deployment, build scalable ML solutions, and leverage emerging technologies—including Generative AI and LLMs—to enhance fraud detection and next-generation risk prevention systems. Key job responsibilities Own end-to-end development of machine learning models for large-scale risk management systems Analyze large volumes of historical and real-time data to identify fraud patterns and emerging risk trends Design, develop, validate, and deploy innovative models to production environments Apply GenAI/LLM technologies to automate risk evaluation and improve operational efficiency Collaborate closely with software engineering teams to implement scalable, real-time model solutions Partner with operations and business stakeholders to translate risk insights into measurable impact Establish scalable and automated processes for data analysis, model experimentation, validation, and monitoring Track model performance and business metrics; communicate insights clearly to technical and non-technical stakeholders Research and implement novel machine learning and statistical methodologies

At Audible, we believe stories have the power to transform lives. It’s why we work with some of the world’s leading creators to produce and share audio storytelling with our millions of global listeners. We are dreamers and inventors who come from a wide range of backgrounds and experiences to empower and inspire each other. Imagine your future with us. ABOUT THIS ROLE As an Applied Scientist, you will solve large complex real-world problems at scale, draw inspiration from the latest science and technology to empower undefined/untapped business use cases, delve into customer requirements, collaborate with tech and product teams on design, and create production-ready models that span various domains, including Machine Learning (ML), Artificial Intelligence (AI) and Generative AI, Natural Language Processing (NLP), Reinforcement Learning (RL), real-time and distributed systems. ABOUT YOU Your work will focus on inventing or adapting scientific approaches, models, and algorithms driven by customer needs at the project level. You will develop components and/or end-to-end solutions that are deployed into production or directly support production systems, delivering consistently high-quality work that meets both scientific and engineering best practices. You will develop reusable science components and services that resolve architecture deficiencies and customers’ pain points, while making technical trade-offs for long-term/short- term. You will work semi-autonomously to deliver solutions, contribute to research papers at peer-reviewed venues when appropriate, and document your work thoroughly to enable others to understand and reproduce it. Your decision-making will consistently incorporate robust, data-driven business and technical judgment. You will collaborate with other scientists to raise the bar of both scientific and engineering complexity for the team and to foster valuable scientific partnership opportunities to help/guide science decisions. We work in a highly collaborative, fast-paced environment where scientists, engineers, and product managers work to test and build scalable foundational capabilities, as well as customer facing experiences. You will have the opportunity to innovate and think big within your projects scope, implement optimization services and algorithms, and influence the experiences of millions of customers. We are looking for a results-oriented Applied Scientist with deep knowledge in ML, NLP, Deep Learning, GenAI, and/or large-scale distributed computation. As an Applied Scientist, you will... - Understand use cases across the business and adopt/extend/design/invent solutions/models that are scalable, efficient, and automated for difficult problems that are not well defined - Work closely with fellow scientists and software engineers (at Audible and Amazon) to build and productionize models, deliver novel and highly impactful features - Review models of peers for the purpose of reducing and managing risk to the business, while improving customer experience - Design, develop, and deploy modeling techniques and solutions for Content Understanding, Recommendations, GenAI-based product features, by employing a wide range of methodologies, working from simple to complex - Contribute to initiatives that employ the most recent advances in ML/AI in a fast-paced, experimental environment - Push the boundary of innovation ABOUT AUDIBLE Audible is the leading producer and provider of audio storytelling. We spark listeners’ imaginations, offering immersive, cinematic experiences full of inspiration and insight to enrich our customers daily lives. We are a global company with an entrepreneurial spirit. We are dreamers and inventors who are passionate about the positive impact Audible can make for our customers and our neighbors. This spirit courses throughout Audible, supporting a culture of creativity and inclusion built on our People Principles and our mission to build more equitable communities in the cities we call home.

Amazon Seller Assistant is our flagship GenAI-first, multi-agent system that reimagines seller experience. Our vision is to provide each seller with a proactive, autonomous, agentic assistant that understands their business and helps them navigate the complexities of selling by anticipating their needs, surfacing insights, resolving issues, taking actions on their behalf, and helping them grow. Amazon Seller Assistant helps millions of sellers on Amazon serve billions of customers worldwide. We are seeking a world-class Applied Scientist to help define and build the next generation of Amazon Seller Assistant. You will partner with top-tier scientists and engineers to launch production-grade agentic capabilities at Amazon's scale — owning your problem space end-to-end, from a crisp customer insight to a shipped product that millions of sellers rely on. Key job responsibilities - Use state-of-the-art Machine Learning and Generative AI techniques to create the next generation of the tools that empower Amazon's Selling Partners to succeed. - Design, develop and deploy highly innovative models to interact with Sellers and delight them with solutions. - Work closely with teams of scientists and software engineers to drive real-time model implementations and deliver novel and highly impactful features. - Establish scalable, efficient, automated processes for large scale data analyses, model benchmarking, model validation and model implementation. - Research and implement novel machine learning and statistical approaches. - Participate in strategic initiatives to employ the most recent advances in ML in a fast-paced, experimental environment. About the team Amazon Seller Assistant team operates at the very frontier of agentic AI and agentic commerce — not as a research group, but as a team shipping production-grade, multi-agent systems used by millions of sellers worldwide. We move with the urgency of a startup and the resources of the world's most customer-obsessed company, transforming the latest breakthroughs in science and engineering into capabilities that sellers rely on every day.

Are you interested in shaping the future of Advertising and B2B Sales? We are a growing team with an exciting AI-first charter and need your passion, innovative thinking, and creativity to help take our products to new heights. Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. Our products are strategically important to our businesses driving long term growth. We break fresh ground in product and technical innovations every day! Within the Advertising Sales organization, we are building a central AI/ML team and are seeking top Applied Science talent to help us build new, science-backed services that drive success for our customers. Our goal is to transform the way account teams operate by creating AI agents that help optimize their end-to-end workflows, and developing actionable insights and recommendations they can share with their advertising accounts As an Applied Scientist on the team with a specific focus on creating autonomous AI agents that can operate accurately at large scale, you will bring deep expertise in Natural Language Processing (inc. tokenization, syntactic parsing, named entity recognition (NER), sentiment analysis, text classification), Large Language Models (inc. foundation model fundamentals, post-training, reward modeling, RAG, transformer architecture), Deep Learning, Reinforcement Learning and/or Recommender Systems. You have the scientific and technical skills to build and refine models that can be implemented in production and you continuously measure the performance of your system to drive continuous improvements. You will contribute to chart new courses with our ad sales support technologies, and you have the communication skills necessary to explain complex technical approaches to a variety of stakeholders and customers. You will be part of a team of fellow scientists and engineers taking on iterative approaches to tackle big, long-term problems. You are fluently able to leverage the latest Generative AI systems and services to accelerate and improve your work while maintaining high quality in your work outputs. Key job responsibilities Scientific Modeling - Conceptualize and lead state-of-the-art research on new Reinforcement Learning, Deep Learning, NLP, LLM, (Generative) Artificial Intelligence and Recommender System solutions to create AI agents and optimize all aspects of the Ad Sales business - Lead the technical approach for the design and implementation of successful models and algorithms in support of expert cross-functional teams delivering on demanding projects - Run regular A/B experiments, gather data, and perform statistical analysis - Improve the scalability, efficiency and automation of large-scale data analytics, model training, deployment and serving - Publish scientific findings in reports and papers that can be shared internally and externally Product Development Support - Partner with software engineering and product management teams to support product and service development, define success metrics and measurement approaches, and help drive adoption of innovative new features for our services. - Lead requirements gathering sessions with product teams and business stakeholders - Maintain scientific documentation and knowledge for product initiatives Collaboration & Communication - Work closely with software engineers to deliver end-to-end solutions into production - Translate complex scientific findings into actionable business recommendations for stakeholders and senior management - Provide clear, compelling reports and presentations on a regular basis with respect to your models and services - Communicate with internal teams to showcase results and identify best practices. About the team Sales AI is a central science and engineering organization within Amazon Advertising Sales that powers selling motions and account team workflows via state-of-the-art of AI/ML services. Sales AI is investing in a range of sales intelligence models, including the development of advertiser insights, recommendations and Generative AI-powered applications throughout account team workflows.

Amazon's Last Mile Geospatial Science team leverages sate of the art computer vision, generative AI, and deep learning to enhance vehicle navigation and ensure safe, efficient deliveries by enriching map data from billions of satellite, aerial, and street-level images and videos. The role involves building large-scale machine learning systems that analyze terabytes of multimodal data to solve novel problems, translating business requirements into prototypes while prioritizing driver and customer safety. The team seeks scientists who can combine domain expertise with machine learning to invent and implement state-of-the-art solutions in a collaborative environment with direct business impact. Key job responsibilities Successful candidates should have a deep knowledge (both theoretical and practical) of various machine learning algorithms for large scale computer vision problems, the ability to map models into production-worthy code, the communication skills necessary to explain complex technical approaches to a variety of stakeholders and customers, and the excitement to take iterative approaches to tackle big, long term problems. The applied scientist should be proficient with image and video analysis using machine learning, including designing architecture from scratch, modify existing loss functions, full model training, fine-tuning, and evaluating the latest deep learning models. The applied scientist optimizes different models for specific platforms, including edge devices with restricted resources. Generative AI, Multi-modal models, e.g., Large Vision Language Models, zero-shot, few-shot, and semi-supervised learning paradigms are used extensively.

Are you inspired by invention? Is problem solving through teamwork in your DNA? Do you like the idea of seeing how your work impacts the bigger picture? Answer yes to any of these and you’ll fit right in here at Amazon Robotics. We are a smart team of doers that work passionately to apply advances in robotics and software to solve real-world challenges that will transform our customers’ experiences in ways we can’t even imagine yet. We invent new improvements every day. We are Amazon Robotics and we will give you the tools and support you need to invent with us in ways that are rewarding, fulfilling and fun. Amazon Robotics is seeking experienced and Senior Applied Scientist with a passion for robotic research. Our team works on challenging and high-impact projects within robotics. Examples of projects include allocating resources to complete a million orders a day, coordinating the motion of thousands of robots and identifying objects and damage. Key job responsibilities - Lead research initiatives advancing AI-driven structured field robotics (path planning, fleet coordination, control systems) and translate breakthroughs into production solutions at global scale - Own end-to-end delivery of complex algorithmic solutions from design through production deployment and operational maintenance - Drive technical decisions for Control, Coordination, and Path Planning systems meeting performance, scalability, and reliability requirements - Partner with cross-functional teams to translate business requirements into research problems and assess technical risks - Influence technical direction across the broader robotics organization through design reviews and technical discussions with senior engineers and scientists - Demonstrate measurable impact through AI-driven algorithmic improvements: fleet efficiency gains, operational cost reduction, system reliability improvements, and enhanced customer experience - Publish findings at top-tier AI and robotics conferences representing organizational technical leadership - Mentor junior Applied Scientists on research methodology and balancing innovation with production constraints - Operate independently on ambiguous, multi-quarter problems requiring novel AI approaches while navigating tradeoffs between research innovation and production constraints A day in the life 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: - Medical, Dental, and Vision Coverage - Maternity and Parental Leave Options - Paid Time Off (PTO) - 401(k) Plan 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! About the team We're the structured field robotics organization powering large-scale mobile robotics operations globally. Our mission is to enable safe, efficient, and reliable robotic operations through intelligent Control, Coordination, and Path Planning systems. We operate at the intersection of planning, algorithmic, and ML research with production systems, owning the full stack from innovation to deployment. Our culture balances research excellence with operational ownership. Applied Scientists partner closely with engineers: reviewing code, contributing to research discussions, and solving problems together. We value deep technical expertise alongside pragmatic engineering judgment. We invest in our people through mentorship and encourage conference participation and knowledge sharing.

Are you interested in shaping the future of Advertising and B2B Sales? We are a growing team with an exciting AI-first charter and need your passion, innovative thinking, and creativity to help take our products to new heights. Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. Our products are strategically important to our businesses driving long term growth. We break fresh ground in product and technical innovations every day! Within the Advertising Sales organization, we are building a central AI/ML team and are seeking top Applied Science talent to help us build new, science-backed services that drive success for our customers. Our goal is to transform the way account teams operate by creating actionable insights and recommendations they can share with their advertising accounts, and ingesting Generative AI throughout their end-to-end workflows to improve their work efficiency. As an Applied Scientist on the team focused on creating customer-facing recommendations related to our advertising products and budget allocations, you will bring deep expertise in quantitative modeling techniques such as Sequential Recommender Systems, Deep Learning, Reinforcement Learning or Hidden Markov Models. You have the scientific and technical skills to build and refine models that can be implemented in production, and you leverage Natural Language Processing and Generative AI models to enhance their explainability. You will contribute to chart new courses with our ad sales support technologies, and you have the communication skills necessary to explain complex technical approaches to a variety of stakeholders and customers. You will be part of a team of fellow scientists and engineers taking on iterative approaches to tackle big, long-term problems. You are fluently able to leverage the latest Generative AI systems and services to accelerate and improve your work while maintaining high quality in your work outputs. Key job responsibilities Scientific Modeling - Conceptualize and lead state-of-the-art research on new Machine Learning and Generative Artificial Intelligence solutions to optimize all aspects of the Ad Sales business - Lead the technical approach for the design and implementation of successful models and algorithms in support of expert cross-functional teams delivering on demanding projects - Run regular A/B experiments, gather data, and perform statistical analysis - Improve the scalability, efficiency and automation of large-scale data analytics, model training, deployment and serving - Publish scientific findings in reports and papers that can be shared internally and externally Product Development Support - Partner with software engineering and product management teams to support product and service development, define success metrics and measurement approaches, and help drive adoption of innovative new features for our services. - Lead requirements gathering sessions with product teams and business stakeholders - Maintain scientific documentation and knowledge for product initiatives Collaboration & Communication - Work closely with software engineers to deliver end-to-end solutions into production - Translate complex scientific findings into actionable business recommendations for stakeholders and senior management - Provide clear, compelling reports and presentations on a regular basis with respect to your models and services - Communicate with internal teams to showcase results and identify best practices. About the team Sales AI is a central science and engineering organization within Amazon Advertising Sales that powers selling motions and account team workflows via state-of-the-art of AI/ML services. Sales AI is investing in a range of sales intelligence models, including the development of advertiser insights, recommendations and Generative AI-powered applications throughout account team workflows. We are truly working on the cutting edge of innovation within Deep Learning, RL, Generative AI and Sequential Recommender Systems within the advertising and sales domains.

Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the limits. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. As a Senior Applied Scientist on our team, you will focus on building state-of-the-art ML models for healthcare. Our team rewards curiosity while maintaining a laser-focus in bringing products to market. Competitive candidates are responsive, flexible, and able to succeed within an open, collaborative, entrepreneurial, startup-like environment. At the forefront of both academic and applied research in this product area, you have the opportunity to work together with a diverse and talented team of scientists, engineers, and product managers and collaborate with other teams. This role offers a unique opportunity to work on projects that could fundamentally transform healthcare outcomes. Key job responsibilities In this role, you will: • Design and implement novel AI/ML solutions for complex healthcare challenges • Drive advancements in machine learning and data science • Balance theoretical knowledge with practical implementation • Work closely with customers and partners to understand their requirements • Navigate ambiguity and create clarity in early-stage product development • Collaborate with cross-functional teams while fostering innovation in a collaborative work environment to deliver impactful solutions • Establish best practices for ML experimentation, evaluation, development and deployment • Partner with leadership to define roadmap and strategic initiatives You’ll need a strong background in AI/ML, proven leadership skills, and the ability to translate complex concepts into actionable plans. You’ll also need to effectively translate research findings into practical solutions. A day in the life You will solve real-world problems by getting and analyzing large amounts of data, generate insights and opportunities, design simulations and experiments, and develop statistical and ML models. The team is driven by business needs, which requires collaboration with other Scientists, Engineers, and Product Managers across the Special Projects organization. You will prepare written and verbal presentations to share insights to audiences of varying levels of technical sophistication. About the team We represent Amazon's ambitious vision to solve the world's most pressing challenges. We are exploring new approaches to enhance research practices in the healthcare space, leveraging Amazon's scale and technological expertise. We operate with the agility of a startup while backed by Amazon's resources and operational excellence. We're looking for builders who are excited about working on ambitious, undefined problems and are comfortable with ambiguity.

Employer: Audible, Inc. Title: Data Scientist II Location: 1 Washington Street, Newark, NJ 07102 Duties: Independently own, design, and implement scalable and reliable solutions to support or automate decision making throughout the business. Apply a range of data science techniques and tools combined with subject matter expertise to solve difficult business problems and cases in which the approach is unclear. Acquire data by building the necessary SQL/ETL queries. Import processes through various company specific interfaces for accessing RedShift, and S3/edX storage systems. Deliver artifacts on medium size projects that affect important business decisions. Build relationships with stakeholders and counterparts, and communicate model outputs, observations, and key performance indicators (KPIs) to the management to develop sustainable and consumable products and product features. Explore and analyze data by inspecting univariate distributions and multivariate interactions, constructing appropriate transformations, and tracking down the source and meaning of anomalies. Build production-ready models using statistical modeling, mathematical modeling, econometric modeling, machine learning algorithms, network modeling, social network modeling, natural language processing, large language models and/or genetic algorithms. Validate models against alternative approaches, expected and observed outcome, and other business defined key performance indicators. Implement models that comply with evaluations of the computational demands, accuracy, and reliability of the relevant ETL processes at various stages of production. Position reports to Newark, NJ office; however, telecommuting from a home office may be allowed. Requirements: Requires a Master’s degree in Statistics, Computer Science, Computer Engineering, Data Science, Machine Learning, Applied Math, Operations Research, or a related field plus two (2) years of experience as a Data Scientist or other occupation involving data processing and predictive Machine Learning modeling at scale. Experience may be gained concurrently and must include: Two (2) years in each of the following: - Utilizing specialized modelling software including Python or R - Building statistical models and machine learning models using large datasets from multiple resources - Building non-linear models including Neural Nets, Deep Learning, or Gradient Boosting. One (1) year in each of the following: - Building production-ready solutions or applications relying on Large Language Models (LLM), accessed programmatically and beyond just prompting - Evaluating LLM results at scale or fine-tuning LLMs - Building production-ready recommendation systems - Using database technologies including SQL or ETL. Alternatively, will accept a Bachelor’s degree and five (5) years of experience. Salary: $169,550 - 207,500 /year. Multiple positions. Apply online: www.amazon.jobs Job Code: ADBL175.

Amazon AGI Autonomy develops foundational capabilities for useful AI agents. We are the research lab behind Amazon Nova Act, a state-of-the-art computer-use agent. Our work combines Large Language Models (LLMs) with Reinforcement Learning (RL) to solve reasoning, planning, and world modeling in the virtual world. We are a small, talent-dense lab with the autonomy to move fast and the long-term commitment to pursue high-risk, high-payoff research. Come be a part of our journey! -- About the team: We are a research engineering team responsible for data ingestion and research tooling that support model development across the lab. The lab’s ability to train state-of-the-art models depends on generating high-quality training data and having useful tools for understanding experimental outcomes. We accelerate research work across the lab while maintaining the operational reliability expected of critical infrastructure. -- About the role: As a backend engineer on the team, you will build and operate core services that ingest, process, and distribute large-scale, multi-modal datasets to internal tools and data pipelines across the lab. This is a hands-on technical leadership role. You will ship a lot of code while defining backend architecture and operational standards across the platform. The platform is built primarily in TypeScript today, with plans to introduce Python services in the future. We are looking for someone who can balance rapid experimentation with operational rigor to build reliable services in a fast-moving research environment. Key job responsibilities - Be highly productive in the codebase and drive the team’s engineering velocity. - Design and evolve backend architecture and interfaces for core services. - Define and own standards for production health, performance, and observability. - Collaborate directly with Research, Human Feedback, Product Engineering, and other teams to understand workflows and define requirements. - Write technical RFCs to communicate design decisions and tradeoffs across teams. - Own projects end to end, from technical design through long-term maintenance. - Raise the team’s technical bar through thoughtful code reviews, architectural guidance, and mentorship.