Careers

Are you fueled by a passion for computer vision, machine learning and AI, and are eager to leverage your skills to enrich the lives of millions across the globe? Join us at Ring AI team, where we're not just offering a job, but an opportunity to revolutionize safety and convenience in our neighborhoods through innovations. You will be part of a dynamic team dedicated to pushing the boundaries of computer vision, machine learning and AI to deliver an unparalleled user experience for our neighbors. This position presents an exceptional opportunity for you to pioneer and innovate in AI, making a profound impact on millions of customers worldwide. You will partner with world-class AI scientists, engineers, product managers and other experts to develop industry-leading AI algorithms and systems for a diverse array of Ring and Blink products, enhancing the lives of millions of customers globally. Join us in shaping the future of AI innovation at Ring and Blink, where exciting challenges await! #HKJobfair Key job responsibilities Key job responsibilities - Research and implement the state-of-the-art computer vision and machine learning methods to deliver high-quality artifacts that meets product specifications. - Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and gap analysis. - Provide technical leadership and research new machine learning approaches to drive continued scientific innovation. - Work in a collaborative environment with other scientists, engineers, product managers and cross-functional teams.

We are looking for a Principal Economist at the frontier of applied econometrics to join the Last Mile Economics team. They will develop rigorous but interpretable models to understand the past and present, predict the future, and identify relevant risks and opportunities across all the Last Mile programs. The team supports Amazon Flex, the Delivery Service Partner program, and the Hub Delivery Partner program. This leader will build tools to forecast the internal and external drivers of the engagement and effectiveness of our transporters. These tools will enable Amazon to innovate ways to incentivize our transporters to deliver for our customers in the short, medium and long term. They will also build econometric models of dynamic systems using our world class data tools, and formalize problems using rigorous science to solve business issues and further delight customers. Key job responsibilities The ideal candidate will have extensive knowledge of both the theory and practice of econometrics, strong collaboration skills, proven ability to lead highly ambiguous and large projects, and a drive to deliver results. They will work closely with and influence a broad set of stakeholders across Last Mile. They will partner closely with Economists, Applied Scientists, Research Scientists, and software engineers to integrate their forecasts and estimates into a larger ecosystem of predictive and optimizing models; with Product leaders to help define analytic product use cases, requirements, and success critera; with Operations and Financial leaders to drive adoption of these tools in both day-to-day operational settings as well as in financial forecasting exercises; and with Leadership to share insights, learnings, and recommendations for taking opportunities and mitigating risk. This position is well suited for economists adept at combining time-series statistical methods with rigorous structural microeconomic modeling and causal inference. It could be a good fit for candidates with research experience in: macroeconometrics and/or empirical macroeconomics; time-series econometrics; forecasting; financial econometrics and/or empirical finance; and the use of micro and panel data to improve and validate traditional aggregate models. A day in the life Economists at Amazon partner closely with senior management, business stakeholders, scientist and engineers, and economist leadership to solve key business problems ranging from Amazon Web Services, Kindle, Prime, inventory planning, international retail, third party merchants, search, pricing, labor and employment planning, effective benefits (health, retirement, etc.) and beyond. Amazon Economists build econometric models using our world class data systems and apply approaches from a variety of skillsets – applied macro/time series, applied micro, econometric theory, empirical IO, empirical health, labor, public economics and related fields are all highly valued skillsets at Amazon. You will work in a fast moving environment to solve business problems as a member of either a cross-functional team embedded within a business unit or a central science and economics organization. You will be expected to develop techniques that apply econometrics to large data sets, address quantitative problems, and contribute to the design of automated systems around the company. About the team The Last Mile Economics team builds forecasting, optimization, and incentive design tools to help connect supply and demand for delivery capacity across Last Mile, delighting millions of customers worldwide. Our forecasts, experimental design, causal inference, dynamic optimization, and mechanism/information design provide timely and effective incentives that shape pools of capacity across Amazon Flex, the Delivery Service Partner program, and our Hub Delivery Partner programs to meet growing demand for high-quality deliveries.

Are you excited by the opportunity to define how Amazon builds and scales intelligent AI systems that influence strategic decisions across a massive transportation network? Do you want to lead the development of agentic AI solutions and mentor the next generation of scientists while shaping how we use generative AI at scale? Amazon’s North American Transportation Data Science & Analytics team is looking for a Senior Applied Scientist to lead the design and implementation of agentic AI systems that simulate, reason, and deliver insights across Amazon’s dynamic supply chain and delivery operations. You will set scientific direction, define development strategy, and lead by example—building intelligent agents that accelerate our ability to analyze complex data and make customer-centric decisions at scale. This is a high-impact, highly visible role. You'll collaborate closely with product, engineering, science, and business leaders across planning, forecasting, operations, and last-mile delivery. Delivery speed is one of Amazon’s core customer value propositions and a key differentiator—your work will directly shape how we measure and improve that experience. Key job responsibilities - Define the AI and agentic development strategy for transportation analytics, including use case prioritization, architecture principles, and integration frameworks - Lead the design and development of autonomous AI agents that deliver insights, simulate system behavior, and support experimentation across analytics workflows - Build systems that allow agents to interact with APIs, knowledge bases, structured and unstructured data sources - Mentor and develop junior scientists and engineers, providing scientific guidance, code reviews, and career development support - Collaborate with Data Scientists, BIEs, and Engineering teams to integrate agentic systems into production workflows and internal tools - Define and own agent evaluation frameworks—measuring business impact, correctness, and efficiency at scale - Drive adoption of shared infrastructure like reusable APIs, prompt libraries, and model registries - Partner with AWS teams and internal technical stakeholders to leverage emerging AI/ML technologies, and serve as an evangelist for scalable, interoperable solutions - Influence cross-org discussions on AI strategy, experimentation tooling, and reusable architecture to support Amazon-wide analytics goals About the team We enable data-driven decision-making for Amazon’s North American Transportation network by combining deep analytics, causal modeling, and experimentation. Our team supports business and tech stakeholders across planning, delivery, and customer experience by developing scalable tools, dashboards, and metrics. As we evolve toward agentic and generative AI, we are reimagining how insights are produced—moving from static reports to intelligent, autonomous systems that proactively surface opportunities and drive operational excellence.

Are you passionate about building intelligent AI systems that deliver insights and shape strategic decisions at scale? Do you want to redefine how analytics is done by leveraging generative AI and autonomous agents? Amazon’s North American Transportation Data Science & Analytics team is looking for an exceptional Applied Scientist to lead the development of agentic AI solutions that simulate, reason, and deliver insights across our complex transportation network. You will build intelligent agents that act as data analysts—identifying patterns, generating hypotheses, and accelerating decision-making for high-impact logistics and delivery challenges. This is a high-impact role that combines deep scientific thinking with practical system building. You'll work closely with product, engineering, and science teams across domains—including planning, forecasting, supply chain, and operations—to shape the future of how Amazon analyzes and improves delivery speed to customers. Delivery speed is one of Amazon’s key differentiators and a critical driver of customer satisfaction. This is a fast-moving, customer-obsessed space where the work you do will have direct and measurable impact on the customer experience across North America. Key job responsibilities - Design, build, and deploy autonomous AI agents that support advanced analytics and experimentation workflows in transportation. - Develop agents that can interact with APIs, query internal data/knowledge sources, and reason over structured and unstructured data. - Collaborate with Data Scientists, BIEs, and Engineers to integrate agentic systems into existing analytical pipelines and business tools. - Use agentic AI to simulate customer or system behavior and define new performance and quality metrics for delivery experience. - Develop evaluation frameworks to measure agent performance, scalability, and business impact. - Contribute to the development of shared infrastructure for agent development—such as reusable APIs, prompt libraries, and model registries. - Partner with internal AWS teams to stay aligned with best-in-class tools and infrastructure for generative and agentic AI. - Stay current on emerging AI/ML technologies and act as an evangelist within the team—driving adoption of new approaches and ensuring scalable, modern solutions are leveraged where appropriate. - Guide quality improvement programs through data-driven insights generated by agentic systems. About the team We enable data-driven decision-making for Amazon’s North American Transportation network by combining deep analytics, causal modeling, and experimentation. Our team supports business and tech stakeholders across planning, delivery, and customer experience by developing scalable tools, dashboards, and metrics. As we evolve toward agentic and generative AI, we are reimagining how insights are produced—moving from static reports to intelligent, autonomous systems that proactively surface opportunities and drive operational excellence.

Amazon Advertising operates at the intersection of eCommerce and advertising, offering a rich array of advertising solutions with the goal of helping our customers find and discover anything they want to buy. We help advertisers reach Amazon customers on Amazon owned and operated sites, other high quality sites across the web, and on millions of TV, tablet, and mobile devices. We start with the customer and work backwards in everything we do, including advertising. If you're interested in working in a world-class organization with a relentless focus on the customer, you've come to the right place! Our team within the CreativeX organization drives engaging user experiences through content and interactivity enrichment, enabling advertisers to reach target audiences at scale. We are looking for a passionate, talented, and resourceful Senior Applied Scientist in the field of Large Language Model (LLM) and Recommender Systems to invent and build scalable solutions for more engaging and customized ads for brands of all sizes across the marketing funnel. Key job responsibilities The scientist will lead research and development for creative defect detection and content personalization, partner with engineering and product teams to execute our product vision, design and implement scalable machine learning solutions, drive innovation in content optimization and audience engagement, and demonstrate strong technical leadership and project execution skills.

MULTIPLE POSITIONS AVAILABLE Employer: AMAZON.COM SERVICES LLC Offered Position: Applied Scientist III Job Location: Seattle, Washington Job Number: AMZ9160677 Position Responsibilities: Participate in the design, development, evaluation, deployment and updating of data-driven models and analytical solutions for machine learning (ML) and/or natural language (NL) applications. Develop and/or apply statistical modeling techniques (e.g. Bayesian models and deep neural networks), optimization methods, and other ML techniques to different applications in business and engineering. Routinely build and deploy ML models on available data, and run and analyze experiments in a production environment. Identify new opportunities for research in order to meet business goals. Research and implement novel ML and statistical approaches to add value to the business. Mentor junior engineers and scientists. Position Requirements: Master’s degree or foreign equivalent degree in Computer Science, Machine Learning, Engineering, or a related field and two years of research or work experience in the job offered, or as a Research Scientist, Research Assistant, Software Engineer, or a related occupation. Employer will accept a Bachelor’s degree or foreign equivalent degree in Computer Science, Machine Learning, Engineering, or a related field and five years of progressive post-baccalaureate research or work experience in the job offered or a related occupation as equivalent to the Master’s degree and two years of research or work experience. Must have one year of research or work experience in the following skill(s): (1) programming in Java, C++, Python, or equivalent programming language; and (2) conducting the analysis and development of various supervised and unsupervised machine learning models for moderately complex projects in business, science, or engineering. Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation. 40 hours / week, 8:00am-5:00pm, Salary Range $167,100/year to $226,100/year. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, visit: https://www.aboutamazon.com/workplace/employee-benefits. #0000

Are you excited to help customers discover the hottest and best reviewed products? The Discovery Tech team helps customers discover and engage with new, popular and relevant products across Amazon worldwide. We do this by combining technology, science, and innovation to build new customer-facing features and experiences alongside agentic tools for marketers. You will be responsible for creating and building critical services that automatically generate, target, and optimize Amazon’s cross-category marketing and merchandising. Through the enablement of intelligent marketing campaigns that leverage machine-learning models, you will help to deliver the best possible shopping experience for Amazon’s customers all over the globe. We are looking for analytical problem solvers who enjoy diving into data, excited about data science and statistics, can multi-task, and can credibly interface between engineering teams and business stakeholders. Your analytical abilities, business understanding, and technical savvy will be used to identify specific and actionable opportunities to solve existing business problems and look around corners for future opportunities. Your domain spans the design, development, testing, and deployment of data-driven and highly scalable machine learning solutions in product recommendation. As an Applied Scientist, you bring business and industry context to science and technology decisions. You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems, acquiring expertise as needed. You decompose complex problems into straightforward solutions. To know more about Amazon science, please visit https://www.amazon.science

The Amazon Alexa AI team in India is seeking a talented, self-driven Applied Scientist to work on prototyping, optimizing, and deploying ML algorithms within the realm of Generative AI. Key responsibilities include: - Research, experiment and build Proof Of Concepts advancing the state of the art in AI & ML for GenAI. - Collaborate with cross-functional teams to architect and execute technically rigorous AI projects. - Thrive in dynamic environments, adapting quickly to evolving technical requirements and deadlines. - Engage in effective technical communication (written & spoken) with coordination across teams. - Conduct thorough documentation of algorithms, methodologies, and findings for transparency and reproducibility. - Publish research papers in internal and external venues of repute - Support on-call activities for critical issues

The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Senior Applied Scientist with a strong deep learning background, to help build industry-leading technology with Large Language Models (LLMs). Key job responsibilities As a Senior 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 LLM foundational models. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate development with LLMs . About the team The AGI team has a mission to advance the state of the art LLMs, in order to provide the best-possible experience for our customers.

Are you fueled by a passion for computer vision, machine learning and AI, and are eager to leverage your skills to enrich the lives of millions across the globe? Join us at Ring AI team, where we're not just offering a job, but an opportunity to revolutionize safety and convenience in our neighborhoods through innovations. You will be part of a dynamic team dedicated to pushing the boundaries of computer vision, machine learning and AI to deliver an unparalleled user experience for our neighbors. This position presents an exceptional opportunity for you to pioneer and innovate in AI, making a profound impact on millions of customers worldwide. You will partner with world-class AI scientists, engineers, product managers and other experts to develop industry-leading AI algorithms and systems for a diverse array of Ring and Blink products, enhancing the lives of millions of customers globally. Join us in shaping the future of AI innovation at Ring and Blink, where exciting challenges await! Key job responsibilities - Research and implement the state-of-the-art computer vision and machine learning methods to deliver high-quality artifacts that meets product specifications. - Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and gap analysis. - Provide technical leadership and research new machine learning approaches to drive continued scientific innovation. - Work in a collaborative environment with other scientists, engineers, product managers and cross-functional teams.