Careers

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 Economist to build the future of long term value measurement and optimization for Amazon Devices. Key job responsibilities We are looking for a talented Senior Economist to drive the science evolution within the Devices Economic Value space (DEV). The Senior Economist will be responsible for evolving the DEV paradigm towards driving direct business value via actionable business levers and influencing the Devices org business strategy through a better understanding of the DEV drivers. They will be responsible for science solutions to better align DEV product and engineering systems towards direct value generation through production systems. We expect the Senior Economist to drive Economic Value innovation, leveraging current advances in causal inference and machine learning. About the team DEV Science team’s mission is to drive measurement and optimization of long term economic value of the devices business that balances short term and long term tradeoffs across product lifecycle, and drive clear value for Amazon shoppers. We leverage science advancements across causal inference, structural modeling and machine learning, to solve challenging business problems in Amazon Devices. The team spans scientists across a wide range of seniority, tenure and specialization, including economists, data and applied scientists, with dedicated product and engineering partners.

Amazon is seeking an exceptional Senior Applied Scientist to join AGI Info Content team. In this role, you will be at the forefront of developing and enhancing the intelligence of AmazonBot crawler and content processing. The team is a key enabler of Amazon's AGI initiatives such as data pipelines for Olympus model training and collecting data for AGI Info grounding services. Our systems operate on web scale. This requires great combination of innovation to utilize all SOTA ML techniques in combination with model optimization to operate on 100k+ requests/decision per second. Your work will directly impact the quality and efficiency of our data acquisition efforts, ultimately benefiting millions of customers worldwide. Key job responsibilities - Design, develop, and implement advanced algorithms and machine learning models to improve the intelligence and effectiveness of our web crawler and content processing pipelines. - Collaborate with cross-functional teams to identify and prioritize crawling targets, ensuring alignment with business objectives - Analyze and optimize crawling strategies to maximize coverage, freshness, and quality of acquired data while minimizing operational costs as well as dive deep into data to select the highest quality data for LLM model training and grounding. - Conduct in-depth research to stay at the forefront of web acquisition and processing. - Develop and maintain scalable, fault-tolerant systems to handle the vast scale of Amazon's web crawling operations - Monitor and analyze performance metrics, identifying opportunities for improvement and implementing data-driven optimizations - Mentor and guide junior team members, fostering a culture of innovation and continuous learning

The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Applied Scientist with a strong deep learning background, to help build industry-leading technology with multimodal systems. Key job responsibilities As an Applied Scientist with the AGI team, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art with multimodal systems. Your work will directly impact our customers in the form of products and services that make use of vision and language technology. You will leverage large-scale computing resources to accelerate development with multimodal Large Language Models (LLMs) and Generative Artificial Intelligence (Gen AI) in Computer Vision. About the team The AGI team has a mission to push the envelope with multimodal LLMs and Gen AI in Computer Vision, in order to provide the best-possible experience for our customers.

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 (GenAI) 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 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 (GenAI) 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 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 (GenAI) 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 Automated Reasoning Group is looking for an Applied Scientist with interest in building scalable machine learning systems. You will be part of a world-class team building the next generation of neuro-symbolic tools and services by combining Automated Reasoning and Machine Learning. AWS has the most services and more features within those services, than any other cloud provider–from infrastructure technologies like compute, storage, and databases–to emerging technologies, such as machine learning and artificial intelligence, data lakes and analytics, and Internet of Things. You will apply your knowledge to propose solutions, create software prototypes, and move prototypes into production systems using modern software development tools and methodologies. In addition, you will support and scale your solutions to meet the ever-growing demand of customer use. You will use your strong verbal and written communication skills, are self-driven and own the delivery of high quality results in a fast-paced environment. Each day, hundreds of thousands of developers make billions of transactions worldwide on AWS. They harness the power of the cloud to enable innovative applications, websites, and businesses. Using automated reasoning technology and mathematical proofs, AWS allows customers to answer questions about security, availability, durability, and functional correctness. We call this provable security, absolute assurance in security of the cloud and in the cloud. See https://aws.amazon.com/security/provable-security/ As an Applied Scientist in AWS AI, you will play a pivotal role in shaping the definition, vision, design, roadmap and development of product features from beginning to end. You will: * Define and implement new neuro-symbolic applications that employ scalable and efficient approaches to solve complex problems using Automated Reasoning and Machine Learning * Apply software engineering best practices to ensure a high standard of quality for all team deliverables * Work in an agile, startup-like development environment, where you are always working on the most important stuff * Deliver high-quality scientific artifacts * Work with the team to help drive business decisions Key job responsibilities * Design and implement scalable neuro-symbolic systems using automated reasoning and machine learning. * Collaborate closely with internal and external users to understand their requirements for AI agents and guardrails. * Proactively identify and explore new opportunities for deploying and leveraging neuro-symbolic solutions across various domains. About the team Why AWS Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Utility Computing (UC) AWS Utility Computing (UC) 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. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Mentorship and Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

Have you ever wondered how Amazon designs and builds its vast transportation and supply chain network? Do you get excited about optimizing global supply chain operations to reduce costs and enhance efficiency? If you thrive in a fast-paced environment and are eager to make a significant impact on a global scale, we want to hear from you! We are the Intelligence & Industrialization (I&I) team within the Global Supply Chain and Transportation Procurement/ Amazon Customs & Trade (GSCTP/ ACT) organization, at the forefront of 3P transportation logistics procurement and customs & trade operations. We are seeking an experienced and talented data scientist passionate about applying science and machine learning techniques to uncover actionable insights for business decision-making. Examples of these decisions include configuring contractual stipulations, negotiating optimal terms with vendors, and minimizing trade penalty risks and operational delays in customs clearance. The successful candidate must work from concept to execution with minimal guidance, influence system and process changes with science thought leadership, and make trade-off recommendations for short-term vs. long-term business needs. Key job responsibilities - Work closely with business stakeholders to identify data science use cases, build consensus on project priorities based on data availability, science applicability, implementation challenges, and business impact. - Lead large data science projects with significant business impact, requiring expertise in both business and technical domains. - Conduct advanced statistical analyses to uncover causal and other relationships among business metrics and operational characteristics. - Design and develop robust forecasting models for freight rates, customer demand, and transportation capacity across various dimensions such as geography and mode. - Build and implement robust ML models for customer segmentation, profitability maximization, performance outlier identification, and risk prediction. - Leverage state-of-the-art LLM models to build AI tools that reduce manual processes and increase business productivity, such as extracting key terms from vendor contracts, answering SOP and business review questions, and writing narratives and executive summaries. - Educate non-technical business audience on complex modeling concepts, and explain modeling results, implications, and performance in an accessible manner. - Collaborate with BIEs, DEs, and other scientists to design and implement end-to-end software solutions powered by science - Coach junior scientists and mentor fellow data team members in data science best practices, methodologies, techniques, and trends. About the team The Intelligence & Industrialization (I&I) Team is a functional data analytics sub team embedded across GSCTP & ACT. Global Supply Chain and Transportation Procurement (GSCTP) is an organization under worldwide operations that manages over 100 third-party supply chain and transportation service providers for Amazon; holding strategic relationships with major providers across modes of transportation, and responsible for an annual spend in excess of $22B. GSCTP’s mission is to secure capacity from third-party providers, increase cost efficiencies of the business, expand supplier capabilities, and improve the quality of our products and services. Amazon Customs & Trade (ACT) is an expanding business unit under worldwide operations for Customs Brokerage services. Customs brokerage involves the coordination of a complex network of sellers, shippers, logistics service providers (LSP), compliance, and government authorities to facilitate clearance of goods for cross-border transportation. Timely submission of documents and coordination with customs agents to ensure hassle free clearance of shipments is a crucial step in the logistics process to ensure on-time delivery of products to our customers.

Join the Amazon AGI team to revolutionize the future of AI by developing breakthrough technologies that dramatically improve the efficiency of large language and foundation models. Work at the frontier of AI research, designing novel approaches for model compression, efficient architectures, long context extension and training optimization that will shape the next generation of AI systems. We're seeking exceptional Applied Scientists to join our team dedicated to solving one of AI's most critical challenges: making foundation models more efficient through lower latency and higher throughput. You'll work on research and new technology development while collaborating with world-class researchers and engineers. - Pioneer new approaches to foundation models - Publish and present research at top-tier conferences and journals - Work with state-of-the-art LLMs and multi-modal foundation models - Access to substantial computational resources for research - Collaborate across AGI teams to implement solutions at scale Key job responsibilities - Research and develop novel techniques for efficient runtime inference (low latency, high throughput) - Design and evaluate efficient foundation model architectures - Create new methods for improving training efficiency - Conduct experimental studies to validate efficiency improvements - Write high-quality Python code to implement research ideas - Collaborate with team members to integrate solutions into production systems - Author technical documentation and research papers - Present findings to technical and non-technical stakeholders A day in the life Your day might start with a team stand-up to discuss ongoing projects and brainstorm solutions to technical challenges. You'll spend time implementing and testing new efficiency optimization techniques in Python, analyzing performance metrics, and iterating on approaches. You'll collaborate with team members to review code and research results, participate in technical discussions about architecture designs, and engage with other AGI teams to understand their efficiency needs. You might end your day analyzing experimental results or writing up findings for a research paper. Throughout the week, you'll have opportunities to present your work to stakeholders and contribute to the team's research roadmap. Our stakeholders include other AGI teams within Amazon, and our work directly impacts the cost and performance of AI systems used across Amazon's products and services. You'll be solving complex technical challenges that make advanced AI more accessible and efficient at scale. About the team The Neural Efficiency Science team was founded in 2024 to develop new technologies that improve the cost-to-performance ratio of AGI foundation models. Amazon believes in customer-obsessed research and as a large number of AI applications are getting built, we see a need to invest in making the underlying foundation models serving these applications cheaper, faster and more accurate at a given price point. Our team keeps up with all of the latest research and trends in what we call "neural efficiency" and publishes our own findings at top conferences such as ICML and NeurIPS while also making our technology available in production for internal and external customers.

Amazon's Pricing & Promotions Optimization Science is seeking a motivated Applied Scientist to harness planet scale multi-modal datasets, and navigate a continuously evolving competitor landscape, in order to regularly generate fresh customer-relevant prices and promotions on billions of Amazon and Third Party Seller products worldwide. We are looking for a talented, organized, and customer-focused applied scientists to define, measure, and launch customer-obsessed solutions across all products listed on Amazon. This role requires an individual with exceptional AI and data science expertise, excellent cross-functional collaboration skills, strong business acumen, and an entrepreneurial spirit. We are looking for an experienced innovator, who is a self-starter, comfortable with ambiguity, demonstrates strong attention to detail, and has the ability to work in a fast-paced and ever-changing environment. Key job responsibilities - See the big picture. Understand and influence the long term vision for Amazon's science-based competitive, perception-preserving pricing/promotion techniques - Build strong collaborations. Partner with product, engineering, and science teams within and outside Pricing & Promotions org to deploy AI/ML solutions at Amazon scale - Stay informed. Establish mechanisms to stay up to date on latest scientific advancements in machine learning, neural networks, natural language processing, probabilistic forecasting, reinforcement learning, and multi-objective optimization techniques. Identify opportunities to apply them to relevant Pricing & Promotions business problems - Keep innovating for our customers. Foster an environment that promotes rapid experimentation, continuous learning, and incremental value delivery - Successfully execute & deliver. Apply your exceptional technical machine learning expertise to incrementally move the needle on some of our hardest science and tech problems About the team About the team: the Pricing and Promotion Optimization team within P2 Science leads the definition, measurement, and implementation of the state-of-the-art AI and data science solutions to improve price/promotion quality across the site and bring value to customers, sellers and Amazon.