Careers

AWS Payments is seeking a Data Scientist to drive high-impact science initiatives to help mitigate financial losses, create frictionless payment experience, minimize the cost of payment processing, and prevent abuses/exploitations of payment systems by bad actors. As a Data Scientist within AWS Payments organization, your role is to leverage your strong background in Data Science and Machine Learning to build best-in-class payment risk assessment frameworks that enable efficient, data-driven decisions anytime, anywhere across payment lifecycle. You will analyze rich datasets at Amazon scale and provide insights to improve existing machine learning solutions as well as drive new scientific initiatives that enhance the payments experience of millions of customers. This role requires a pragmatic technical leader who is comfortable navigating ambiguous environments and is capable of effectively summarizing complex data analysis and modeling results through clear verbal explanations and written documentations. The ideal candidate will have experience with machine learning models and applying science to various business contexts, especially experience in dealing with payments or financial services data. You will have to work with a group of other research scientists, product managers and engineers and play an integral role in strategic decision-making. The right candidate will possess excellent business and communication skills, define business objectives and prioritize work across the team to support business outcomes, and develop solutions to key business problems. Key job responsibilities - Interact with product managers, business teams, and engineering teams to develop an understanding and domain knowledge of business requirements, processes and system structures. - Apply domain knowledge and business judgment to identify opportunities and quantify the impact aligning research direction to business requirements and make the right judgment on research project prioritization. - Develop scalable mathematical models to derive optimal or near-optimal solutions to existing and new challenges in the AWS payments space. - Improve upon existing methodologies by integrating new data sources, developing new models or algorithmic enhancements and fine-tuning model parameters. - Advocate technical solutions to business stakeholders, engineering teams, as well as executive level decision makers. - Work closely with engineers to integrate prototypes into production systems. - Frame evaluation methods to monitor the actual performance of devised solutions in production systems, identify areas with potential for improvement and work with internal teams to improve the solution with new features. - Lead the project plan from a scientific perspective on product launches including identifying key milestones, potential risks and paths to mitigate risks. About the team About AWS Diverse Experiences AWS 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. 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 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. 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 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. This team is part of AWS Utility Computing: 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.

Come build the future of entertainment with us. Are you interested in helping shape the future of movies and television? Do you want to help define the next generation of how and what Amazon customers are watching? Prime Video is a premium streaming service that offers customers a vast collection of TV shows and movies - all with the ease of finding what they love to watch in one place. We offer customers thousands of popular movies and TV shows including Amazon Originals and exclusive licensed content to exciting live sports events. We also offer our members the opportunity to subscribe to add-on channels which they can cancel at anytime and to rent or buy new release movies and TV box sets on the Prime Video Store. Prime Video is a fast-paced, growth business - available in over 240 countries and territories worldwide. The team works in a dynamic environment where innovating on behalf of our customers is at the heart of everything we do. If this sounds exciting to you, please read on. We are looking for a Senior Applied Scientist to embark on our journey to build a Prime Video Sports tech team in Israel from ground up. Our team will focus on developing products to allow for personalizing the customers’ experience and providing them real-time insights and revolutionary experiences using Computer Vision (CV) and Machine Learning (ML). You will get a chance to work on greenfield, cutting-edge and large-scale engineering and science projects, and a rare opportunity to be one of the founders of the Israel Prime Video Sports tech team in Israel. Key job responsibilities We are looking for a Senior Applied Scientist with domain expertise in Computer Vision or Recommendation Systems to lead development of new algorithms and E2E solutions. You will be part of a team of applied scientists and software development engineers responsible for research, design, development and deployment of algorithms into production pipelines. As a technologist, you will also drive publications of original work in top-tier conferences in Computer Vision and Machine Learning. You will be expected to deal with ambiguity! We're looking for someone with outstanding analytical abilities and someone comfortable working with cross-functional teams and systems. You must be a self-starter and be able to learn on the go. About the team In September 2018 Prime Video launched its first full-scale live streaming experience to world-wide Prime customers with NFL Thursday Night Football. That was just the start. Now Amazon has exclusive broadcasting rights to major leagues like NFL Thursday Night Football, Tennis major like Roland-Garros and English Premium League to list few and are broadcasting live events across 30+ sports world-wide. Prime Video is expanding not just the breadth of live content that it offers, but the depth of the experience. This is a transformative opportunity, the chance to be at the vanguard of a program that will revolutionize Prime Video, and the live streaming experience of customers everywhere.

Conversational AI ModEling and Learning (CAMEL) team is part of Amazon Devices organization where our mission is to build a best-in-class Conversational AI that is intuitive, intelligent, and responsive, by developing superior Large Language Models (LLM) solutions and services which increase the capabilities built into the model and which enable utilizing thousands of APIs and external knowledge sources to provide the best experience for each request across millions of customers and endpoints. We are looking for a passionate, talented, and resourceful Applied Scientist in the field of LLM, Artificial Intelligence (AI), Natural Language Processing (NLP), Recommender Systems and/or Information Retrieval, to invent and build scalable solutions for a state-of-the-art context-aware conversational AI. A successful candidate will have strong machine learning background and a desire to push the envelope in one or more of the above areas. The ideal candidate would also have hands-on experiences in building Generative AI solutions with LLMs, enjoy operating in dynamic environments, be self-motivated to take on challenging problems to deliver big customer impact, moving fast to ship solutions and then iterating on user feedback and interactions. Key job responsibilities As an Applied Scientist, you will leverage your technical expertise and experience to collaborate with other talented applied scientists and engineers to research and develop novel algorithms and modeling techniques to reduce friction and enable natural and contextual conversations. You will analyze, understand and improve user experiences by leveraging Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in artificial intelligence. You will work on core LLM technologies, including Prompt Engineering and Optimization, Supervised Fine-Tuning, Learning from Human Feedback, Evaluation, Self-Learning, etc. Your work will directly impact our customers in the form of novel products and services.

We’re working to improve shopping on Amazon using the conversational capabilities of large language models and are searching for pioneers who are passionate about AI and innovation in a fast moving environment. You'll be working with talented scientists, engineers, and technical program managers (TPM) to innovate on behalf of our customers. Your focus will be in post-training problems and solutions including grounding, fine-tuning and personalization. Key job responsibilities As a Sr. Applied Science, you will drive strategic investments in the applied science team while delivering impact in short term iterations. Your focus will be in post-training problems and solutions including grounding, fine-tuning and personalization. You will stay in tune with state of the art and mentor other applied scientists.

AWS AI/ML is looking for world class scientists and engineers to join its group working on deploying reinforcement (RL) and machine learning (ML) methods in real-world applications, studying, and building new approaches. Our vision is to advance the state-of-the-art in RL/ML especially as applicability of RL methods has not translated quite well to real world scenarios as they are known to be expensive to train, sample inefficient, sensitive to hyper-parameter settings, and lacking transferability to new tasks. Our team’s mission is to study these problems and make RL/ML approaches more robust and reliable. Building these solutions requires a solid foundation in machine learning and reinforcement learning technologies. We are seeking a Senior Applied Scientist for the team. This is a role that combines science knowledge (around machine learning and reinforcement learning), technical strength, and product focus. It will be your job to develop novel ML/RL systems and algorithms while working with the engineering team to integrate them into different projects. You will be at the heart of a growing and exciting focus area for AWS and work with other acclaimed engineers and world famous scientists. 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.

Are you looking for a challenge? Imagine being part of a team that owns one of the largest supply chain simulation systems in the world to predict inventory flows for the millions of items available on Amazon.com worldwide. Inventory planning involves many algorithms to buy inventory in the right quantities, at the right frequencies, from the right vendors, and assigning to the best warehouse to fulfill customer demand to optimize long term free cash flow for Amazon. Our system lives at the heart of these algorithms, keeping up with the rapid pace of optimization improvements and simulating how they interact with each other. We simulate what these systems will do for months into the future, predicting inventory flows and key operational and financial metrics across the network. This experimentation platform is critical in understanding labor needs, managing our network capacity, and allowing continued optimizations to the many algorithms we simulate. Imagine enabling Amazon's supply chain systems to make data driven decisions based on simulations of trillions of inventory events per day. Every time an Amazon customer makes a purchase, a number of systems are involved: these systems help optimize inventory acquisition, enable a number of purchase options, ensure great pricing, store products so they are available for fast delivery, and minimize package frustration. The Supply Chain Optimization Technology (SCOT) Group develops and manages these systems. We are central to Amazon customers' ability to find what they want and get it when they want it. Within SCOT, the Inventory Planning Control (IPC) Simulation team is responsible for designing and executing the simulations to predict inventory flows for labor planning, predict the impact of new supply chain initiatives, and enable experimentation of new inventory policies developed by SCOT teams, expediting their development cycle. We are looking for a science manager to drive research innovation in SCOT by pushing IPC Simulation systems further upstream in the innovation process, developing new techniques and methodologies for both experimentation and prediction use cases, and applying existing models to our problem space and beyond. As an Amazon Science Manager, your work will impact on how we serve our customers so that they get the right product at the right time. In our team, you will be working in one of the world's largest data warehouse environments. You need to be a sophisticated user of data querying tools and advanced quantitative and modeling techniques, and an expert at synthesizing and communicating insights and recommendations to audiences of varying levels of technical sophistication to drive change, as your work will be visible up to the highest business leaders in SCOT. You will own the roadmap and vision of IPC Simulation. Much of the job will require close collaboration with software development engineers, other scientists, science managers, and business teams to innovate for and solve problems of the future. Key job responsibilities As a Senior Applied Science Manager in IPC, you will partner with the senior tech leaders in the organization to define the long term architecture of our decision optimization and prediction systems. You will play a key role in developing long term strategic solutions that have business impact beyond the scope of the organization. You will bring technical expertise in several technical areas of Operations Research or Machine Learning, and are able to help team to define and deliver the science vision. You will ensure senior leaders in the organization are up to speed on important trends, tools and technologies and how they will be used to impact the business. You are able to quickly approach large ambiguous problems, turn high-level business requirements into mathematical models, identify the right solution approach, and contribute to the software development for production systems. Successful candidates must thrive in fast-paced environments, which encourage collaborative and creative problem solving, be able to measure and estimate risks, constructively critique peer research, and align research focuses with the Amazon's strategic needs.

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 and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day! We are looking for an accomplished and visionary machine learning expert to lead the Applied Science strategy for our Media Planning Science program. In this role, you will work closely with business leaders, stakeholders, and cross-functional teams to drive program success through ML-driven solutions. You will shape the applied science roadmap, promote a culture of data-driven decision-making, and deliver significant business impact using advanced data techniques and cutting-edge applied science methodologies. Key job responsibilities As an Applied Scientist on this team, you will: - Serve as the technical leader in Machine Learning, guiding efforts within the team and collaborating with other teams. - Conduct hands-on analysis and modeling of large-scale data to generate insights that boost traffic monetization and merchandise sales while maintaining a positive shopper experience. - Lead end-to-end Machine Learning projects that involve high levels of ambiguity, scale, and complexity. - Build, experiment, optimize, and deploy machine learning models, collaborating with software engineers to bring your models into production. - Run A/B experiments, gather data, and perform statistical analysis to validate your models. - Develop scalable and automated processes for large-scale data analysis, model development, validation, and serving. - Explore and research innovative machine learning approaches to push the boundaries of what’s possible. About the team The Media Planning Science team builds and deploys models that provide insights and recommendations for media planning. Our mission is to assist advertisers in activating plans that align with their goals. Our insights and recommendations leverage heuristic and machine learning models to simplify the complex tasks of forecasting, outcome prediction, budget planning, optimized audience selection and measurements for media planners. We integrate our insights into user interfaces and programmatic integrations via APIs, ensuring reliable data, timely delivery, and optimal advertising outcomes for our advertisers.

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 and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day! The Customer - Advertiser Success & Insights (CASI) team is seeking an Applied Scientist to help increase the effectiveness of online advertising. You will leverage computer vision, generative AI, natural language processing, casual inference, and machine learning to enhance the customer experience with online advertising. In this role, you will collaborate closely with business leaders, stakeholders, and cross-functional teams to drive success for our customers through data-driven solutions. This is an excellent opportunity for a technically-minded individual to make a tangible impact on the online advertising landscape. The role offers the chance to work with state-of-the-art technologies and contribute to the evolution of a rapidly changing industry. Key job responsibilities As an Applied Scientist in CASI, you will: -> Shape the science roadmap for CASI, fostering a culture of data-driven decision-making. -> Deliver significant business impact through advanced ML models, generative AI, and cutting-edge causal inference methodologies. -> Produce and deliver models that help drive best-in-class customer experiences and build systems that allow us to deploy these models to production with low latency and high throughput. -> Collaborate with cross-functional teams, including software engineers, data scientists, and product managers, to define project requirements, establish success metrics, and deliver high-quality solutions. -> Research new and innovative machine learning approaches.

AEE Science and AI team is focused on advancing customer experience on 1) Expansions: building the end-to-end Day0 search relevance models (ranking and matching) for new Amazon marketplaces, 2) Exports: improving the search relevance for cross-border (exports) customers, and 3) Emerging Markets Retail Efficiency related initiatives. We focus on algorithms and machine learning model developments, and optimize for recall (completeness) and precision (accuracy), measured through Spare Result Rate (SRR) and Irrelevant Result Rate (IRR) respectively. We are also leveraging Generative AI and LLMs to improve retail operations and reduce cost-to-serve. In this role, you will leverage your expertise in machine learning, information retrieval, and natural language processing to design, implement, and optimize ranking and matching algorithms that improve user experience and satisfaction. Key responsibilities include analyzing large datasets to identify patterns and insights, developing and fine-tuning models to improve search result relevance, and collaborating with cross-functional teams to integrate these models into our search systems. You will conduct experiments to evaluate model performance, utilizing A/B testing and other methodologies to ensure continuous improvement. The ideal candidate will possess a strong background in applied mathematics, computer science, or a related field, with experience in search technologies and a passion for solving complex problems. You will have the opportunity to make a significant impact on our product by driving advancements in search relevance that directly enhance user engagement and outcomes. Key job responsibilities 1. Model Development: Design, implement, and refine machine learning models for ranking and matching to enhance search relevance and user satisfaction. 2. Data Analysis: Analyze large datasets to extract insights, identify trends, and inform model improvements, ensuring data-driven decision-making. 3. Algorithm Optimization: Continuously evaluate and optimize existing algorithms to improve search accuracy and performance through experimentation and iteration. 4. Performance Evaluation: Conduct A/B testing and other evaluation methodologies to assess model effectiveness, drawing actionable conclusions to guide further development. 5. Cross-Functional Collaboration: Work closely with product managers, engineers, and UX researchers to integrate search models into production systems and align with overall product goals. 6. Research and Innovation: Stay current with advancements in machine learning, natural language processing, and information retrieval to drive innovation in search technologies. 7. Reporting: Document methodologies, findings, and model performance metrics, and communicate results effectively to stakeholders at all levels.

At Amazon, we believe that scientific innovation is essential to being the most customer-centric company in the world. Our scientists' ability to have an impact at scale allows us to attract some of the brightest minds in machine learning, artificial intelligence and related fields. Amazon scientists employ the company's working backwards method to identify problems to solve on behalf of customers in research areas ranging from machine learning to operations, GenAI, robotics, quantum computing, computer vision, economics, search, sustainability and more. Learn more about Amazon Science here: https://www.amazon.science/ We are hiring across multiple businesses and in many locations across the US. Apply here to learn more about open roles that could be a compelling fit for your background. Key job responsibilities You will be responsible for defining key research directions, adopting or inventing new machine learning techniques, conducting rigorous experiments, publishing results, and ensuring that research is translated into practice. You will develop long-term strategies, persuade teams to adopt those strategies, propose goals and deliver on them. You will also participate in organizational planning, hiring, mentorship and leadership development. You will be technically fearless and with a passion for building scalable science and engineering solutions. You will serve as a key scientific resource in full-cycle development (conception, design, implementation, testing to documentation, delivery, and maintenance).