Careers

The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and innovative principal applied scientist with a strong background in deep learning, to help build industry-leading technology with Large Language Models (LLMs) and multimodal systems. Key job responsibilities As a Principal Applied Scientist within the AGI team, you will work with world-class scientists and engineers to develop novel data, modeling and engineering solutions to support the responsible AI initiatives at AGI. Your work will directly impact our customers in the form of products and services that make use of AI technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in AGI in order to provide the best-possible experience for our customers. About the team Our team has a mission to push the envelope of AGI, in order to provide the best-possible experience for our customers.

We are a part of Amazon Alexa Devices organization with the mission “delight customers through contextual and personalized proactive experiences that keep customers informed, engaged, and productive without cognitive burden”. We are developing an advanced system using Large Language Model (LLM) technologies to deliver engaging, intuitive, and adaptive content recommendations across all Amazon surfaces. We aim to facilitate seamless reasoning and customer experiences, surpassing the capabilities of previous machine learning models. We are looking for a passionate, talented, and resourceful Applied Scientist in the field of Natural Language Processing (NLP), Recommender Systems and/or Information Retrieval, to invent and build scalable solutions for a state-of-the-art context-aware speech assistant. 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 enjoy operating in dynamic environments, be self-motivated to take on challenging problems to deliver big customer impact, shipping solutions via rapid experimentation and then iterating on user feedback and interactions. Key job responsibilities As an Applied Scientist on the team, you will collaborate with other applied scientists and engineers to develop novel algorithms to enable timely, relevant and delightful recommendations and conversations. Your work will directly impact our customers in the form of products and services that make use of various machine learning, deep learning and language model technologies. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in the state of art.

We are a part of Amazon Artificial General Intelligence (AGI) organization where our mission is “delight customers through contextual and personalized proactive experiences that keep customers informed, engaged, and productive without cognitive burden”. We are developing advanced systems to deliver engaging, intuitive, and adaptive content recommendations across all Amazon surfaces. We aim to facilitate seamless reasoning and customer experiences, surpassing the capabilities of previous machine learning models. We are looking for a passionate, talented, and resourceful Senior Applied Scientist in the field of Natural Language Processing (NLP), Large Language Model (LLM), Recommender Systems and/or Information Retrieval, to invent and build scalable solutions for a state-of-the-art context-aware personal assistant. 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 enjoy operating in dynamic environments, be self-motivated to take on challenging problems to deliver big customer impact, shipping solutions via rapid experimentation and then iterating on user feedback and interactions. Key job responsibilities As a Senior Applied Scientist, you will leverage your technical expertise and experience to demonstrate leadership in tackling large complex problems, setting the direction and collaborating with applied scientists and engineers to develop novel algorithms and modeling techniques to enable timely, relevant and delightful recommendations and conversations. Your work will directly impact our customers in the form of products and services that make use of various machine learing, deep learning and language model technologies. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in the state of art.

Amazon Worldwide Advertising is one of Amazon's fastest growing and most profitable businesses. Partner Experience and Growth (PEG) team leverages advanced analytics and experimentation to unlock value for our advertising partners and mutual customers i.e. the advertisers. The Science charter in PEG spearheads these efforts by optimizing the onboarding journey and providing data-driven insights to agencies and tool providers in the Amazon Ads ecosystem. Our proprietary tools provide granular visibility into what's working across audiences, creatives, targeting strategies, and more. These custom algorithmic recommendations uncover growth opportunities previously hidden in the data fog. Partners can confidently allocate budgets based on predicted performance, unlocking improved return on ad spend. And advertisers reap the benefits through expanded brand awareness, increased sales, and stronger customer loyalty over time. Key job responsibilities You will participate in driving features from idea to deployment, and your work will directly impact millions of customers. You are going to love this job because you will: Map business requirements and customer needs to a scientific problem. Align the research direction to business requirements and make the right judgments on research/development schedule and prioritization. Research, design and implement scalable machine learning (ML), natural language, or supervised and unsupervised models to solve problems that matter to our customers in an iterative fashion. Mentor and develop junior scientists and developers who work on science problems in the same organization. Stay informed on the latest machine learning, natural language and/or artificial intelligence trends and make presentations to the larger engineering and science communities. Communicate complex technical concepts effectively to both technical and non-technical stakeholders, providing clear explanations on proposed solutions and their potential impact. About the team The Partner Science team’s vision is to drive the Advertising Partner flywheel by infusing science-based interventions at all stages of their journey with Amazon Ads including demand generation, partner selection, partner engagement, partner competition and innovation, ultimately improving the partner managed advertiser experience. We drive the vision by attracting and growing top scientist talents in an innovative, experimental, and collaborative culture.

Job Description Are you interested in applying your strong quantitative analysis and big data skills to world-changing problems? Are you interested in driving the development of methods, models and systems for capacity planning, transportation and fulfillment network? If so, then this is the job for you. Our team is responsible for creating core analytics tech capabilities, platforms development and data engineering. We develop scalable analytics applications and research modeling to optimize operation processes. We standardize and optimize data sources and visualization efforts across geographies, builds up and maintains the online BI services and data mart. You will work with professional software development managers, data engineers, scientists, business intelligence engineers and product managers using rigorous quantitative approaches to ensure high quality data tech products for our customers around the world, including India, Australia, Brazil, Mexico, Singapore and Middle East. Amazon is growing rapidly and because we are driven by faster delivery to customers, a more efficient supply chain network, and lower cost of operations, our main focus is in the development of strategic models and automation tools fed by our massive amounts of available data. You will be responsible for building these models/tools that improve the economics of Amazon’s worldwide fulfillment networks in emerging countries as Amazon increases the speed and decreases the cost to deliver products to customers. You will identify and evaluate opportunities to reduce variable costs by improving fulfillment center processes, transportation operations and scheduling, and the execution to operational plans. You will also improve the efficiency of capital investment by helping the fulfillment centers to improve storage utilization and the effective use of automation. Finally, you will help create the metrics to quantify improvements to the fulfillment costs (e.g., transportation and labor costs) resulting from the application of these optimization models and tools. Major responsibilities include: · Translating business questions and concerns into specific analytical questions that can be answered with available data using BI tools; produce the required data when it is not available. · Apply Statistical and Machine Learning methods to specific business problems and data. · Create global standard metrics across regions and perform benchmark analysis. · Ensure data quality throughout all stages of acquisition and processing, including such areas as data sourcing/collection, ground truth generation, normalization, transformation, cross-lingual alignment/mapping, etc. · Communicate proposals and results in a clear manner backed by data and coupled with actionable conclusions to drive business decisions. · Collaborate with colleagues from multidisciplinary science, engineering and business backgrounds. · Develop efficient data querying and modeling infrastructure. · Manage your own process. Prioritize and execute on high impact projects, triage external requests, and ensure to deliver projects in time. · Utilizing code (Python, R, Scala, etc.) for analyzing data and building statistical models.

The Alexa Smart Home team is focused on making Alexa the user interface for the home. From the simplest voice commands (turn on the lights, turn down the heat) to use cases spanning home security, home entertainment, and the home environment; we are evolving Alexa into an intelligent, indispensable companion that automates daily routines, simplifies interaction with appliances and electronics, and alerts when something unusual is detected. You can be part of a team delivering features that are highly anticipated by media and well received by our customers. As a Sr. Data Scientist, you will work with other scientists and software developers to design and build the next generation of Smart Home voice control using the latest Large Language Models (LLM's). And, you will have the satisfaction of working on a product your friends and family can relate to, and want to use every day. Key job responsibilities - Develop new inference and training techniques to improve the performance of LLMs for Smart Home control and automation - Develop robust techniques for synthetic data generation for training large models and maintaining model generalization - Mentoring junior scientists to improve their skills, knowledge, and ability to contribute to team projects About the team We are a team of Scientists, Machine Learning Engineers, and Software Developers that work together to make Alexa more insightful and proactive through ambient intelligence, with features like Alexa Hunches that automatically control Smart Home devices. We are interdisciplinary and we act like it. We ask each other questions and value our different perspectives.

The Alexa Smart Home team is focused on making Alexa the user interface for the home. From the simplest voice commands (turn on the lights, turn down the heat) to use cases spanning home security, home entertainment, and the home environment; we are evolving Alexa into an intelligent, indispensable companion that automates daily routines, simplifies interaction with appliances and electronics, and alerts when something unusual is detected. You can be part of a team delivering features that are highly anticipated by media and well received by our customers. As an Applied Scientist, you will work with other scientists and software developers to design and build the next generation of Smart Home voice control using the latest Large Language Models (LLM's). And, you will have the satisfaction of working on a product your friends and family can relate to, and want to use every day. Key job responsibilities - Develop new inference and training techniques to improve the performance of LLMs for Smart Home control and Automation - Develop robust techniques for synthetic data generation for training large models and maintaining model generalization - Mentoring junior scientists to improve their skills, knowledge, and their ability to get things done About the team We are a team of Scientists, Machine Learning Engineers, and Software Developers that work together to make Alexa more insightful and proactive through ambient intelligence, with features like Alexa Hunches that automatically control Smart Home devices. We are interdisciplinary and we act like it. We ask each other questions and value our different perspectives.

Amazon Search owns the global search engine for the Amazon shopping site. The Japan team improves the search engine and related systems with new data sources, cutting-edge language models and Document Understanding features, to enhance the search experience and UX. We are looking for highly motivated applied scientists and engineers interested in delivering the next level of innovation to product search for Amazon. The position is based in the Amazon Japan Meguro (Tokyo) office. As an Applied Scientist for Search, you will lead the design, implementation and delivery of search features on Amazon worldwide, helping millions of customers every day to find quickly what they are looking for, and to discover products they didn't even know Amazon carried. Your improvements to the product search engine will include tailoring search for global marketplaces, using advanced techniques and tools to mine petabytes of data, and running experiments to detect important areas of improvement and measure success. You will be designing solutions, sometimes from the ground up, that scale to efficiently handle billions of queries and items each day. You will be working closely with international teams of bright and talented people all over the world, both in business and in technology. The models that you develop, supported by industrial scale development tools, integrates smoothly and efficiently into one of the largest code bases in the world and runs in data centers worldwide. By joining us, you will help to build up global development expertise in a team of engineers based in Tokyo working on solutions used locally, and worldwide. Besides possessing knowledge and problem solving expertise in applied science discipline, you must be an innovative thinker and a strong communicator. Working in this position will involve collaborating with engineers and scientists in the US, Europe, and other places. About the team The Core Search NLP Document Enhancement (DocE) ‘s mission is to enhance and update the representations of products and related information in the Search index, via the use and understanding of new and existing data sources including third-party sources, to improve search relevance and related experiences for customers.

Do you want to leverage your expertise in translating innovative science into impactful products to improve the lives and work of over a million people worldwide? If so, People eXperience Technology Central Science (PXTCS) would love to discuss how you can make that a reality. PXTCS is an interdisciplinary team that uses economics, behavioral science, statistics, and machine learning to identify products, mechanisms, and process improvements that enhance Amazonians' well-being and their ability to deliver value for Amazon's customers. We collaborate with HR teams across Amazon to make Amazon PXT the most scientific human resources organization in the world. In this role you will lead and grow a team of scientists responsible for the science strategy and technical implementation innovations across our predictive modeling and forecasting work-streams. These machine learning work-streams include existing models and future models that power leaders across Amazon to make decisions about their businesses. You will build and develop a high-performing team while serving as the strategic science advisor to PXT leaders operating at the Director, VP, and SVP level. As a people manager, you will coach and mentor your team to identify opportunities where science investment can have material impact on our long-term objectives or annual goals, and help them build consensus around needed investments. You will guide your team across different business domains (corporate, operations, safety) and analysis levels (individual, group, organizational), using various modeling approaches (linear, tree, deep neural network, and LLM-based), enabling stakeholders to make challenging and strategic decisions. While primarily focused on people leadership, you maintain technical depth to effectively review and guide your team's development and delivery of complex science modeling and implementation problems. You will develop your team's technical vision while staying current with emergent AI/ML science and engineering trends, helping your organization focus in a rapidly evolving landscape. Key responsibilities include organizational planning, hiring strategy, career development, and building the next generation of technical leaders. We are looking for a people leader who can create an inclusive team environment, think big, move fast, and inspire their team to transform the way leaders use data to drive business success. If you excel at building and leading high-performing technical teams and are passionate about developing both technology and people, come join us as we work hard, have fun, and make history.

Do you want to join an innovative team of scientists who use deep learning, natural language processing, large language models to help Amazon provide the best seller experience across the entire Seller life cycle, including recruitment, growth, support and provide the best customer and seller experience by automatically mitigating risk? Do you want to build advanced algorithmic systems that help manage the trust and safety of millions of customer interactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data and creating state-of-the-art algorithms to solve real world problems? Are you excited by the opportunity to leverage GenAI and innovate on top of the state-of-the-art large language models to improve customer and seller experience? Do you like to build end-to-end business solutions and directly impact the profitability of the company? Do you like to innovate and simplify processes? If yes, then you may be a great fit to join the Machine Learning Accelerator team in the Amazon Selling Partner Services (SPS) group. Key job responsibilities The scope of an Applied Scientist III in the Selling Partner Services (SPS) Machine Learning Accelerator (MLA) team is to research and prototype Machine Learning applications that solve strategic business problems across SPS domains. Additionally, the scientist collaborates with engineers and business partners to design and implement solutions at scale when they are determined to be of broad benefit to SPS organizations. They develop large-scale solutions for high impact projects, introduce tools and other techniques that can be used to solve problems from various perspectives, and show depth and competence in more than one area. They influence the team’s technical strategy by making insightful contributions to the team’s priorities, approach and planning. They develop and introduce tools and practices that streamline the work of the team, and they mentor junior team members and participate in hiring.