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Amazon is looking for an Applied Scientist with a machine learning background to help build industry-leading Speech and Language technology. Key job responsibilities Advertising at Amazon is a fast-growing multi-billion dollar business that spans across desktop, mobile and connected devices; encompasses ads on Amazon and a vast network of hundreds of thousands of third party publishers; and extends across US, EU and an increasing number of international geographies. One of the key focus areas is Traffic Quality where we endeavour to identify non-human and invalid traffic within programmatic ad sources, and weed them out to ensure a high quality advertising marketplace. We do this by building machine learning and optimization algorithms that operate at scale, and leverage nuanced features about user, context, and creative engagement to determine the validity of traffic. The challenge is to stay one step ahead by investing in deep analytics and developing new algorithms that address emergent attack vectors in a structured and scalable fashion. We are committed to building a long-term traffic quality solution that encompasses all Amazon advertising channels and provides state-of-the-art traffic filtering that preserves advertiser trust and saves them hundreds of millions of dollars of wasted spend. We are looking for a dynamic, innovative and accomplished applied sciences manager to lead machine learning and data science for the Advertising Traffic Quality vertical. Are you excited by the prospect of analyzing terabytes of data and leveraging state-of-the-art data science and machine learning techniques to solve real world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? As an applied sciences manager for Traffic Quality, you will lead a team of applied scientists, data scientists and engineers to deliver to conceptualize and build algorithms that efficiently detect and filter invalid traffic. You will be the single-threaded owner of the algorithms that go into our traffic quality systems and will be responsible for both near-term improvements to existing algorithms as well as long-term direction for Traffic Quality algorithms. Your team will include experts in machine learning, statistics and analytics that are working on state-of-the-art modeling techniques, as well as generating insights that fuel critical investments. You will also lead an engineering team that works on handling terabyte scale data and implementing features and algorithms that process billions of events per day. You will interface with product managers and operations teams to bring key advertising initiatives to customers. Your strong management skills will be utilized to help deliver critical projects that cut across organization structures and meet key business goals. Major responsibilities • Deliver key goals to enhance advertiser experience and deliver multi-million dollar savings by building algorithms to detect and mitigate invalid traffic • Use machine learning and statistical techniques to create new, scalable solutions for invalid traffic filtering • Drive core business analytics and data science explorations to inform key business decisions and algorithm roadmap • Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation • Hire and develop top talent in machine learning and data science and accelerate the pace of innovation in the group • Build a culture of innovation and long-term thinking, and showcase this via peer-reviewed publications and whitepapers • Work with your engineering team and product managers to evangelize new algorithms and drive the implementation of large-scale complex ML models in production • Keep updated on the industry landscape in Traffic Quality and identify algorithm investments to achieve an industry leading traffic quality solution. • Learn continuously about new developments in machine learning and AI, as well as recent innovations in creative intelligence and malware detection. Identify how these can be rolled into building an industry leading solution for Amazon advertising

The Amazon Private Brands’ Discovery team develops innovative machine learning solutions to enhance customer awareness of Amazon's private brands and help customers discover products they love. This interdisciplinary team of scientists and engineers incubates and builds disruptive technologies, tackling some of the most complex scientific challenges at Amazon. To achieve this, we leverage a wide range of advanced techniques, including Natural Language Processing (NLP), deep learning, large language models (LLMs), multi-armed bandits, reinforcement learning, Bayesian optimization, causal and statistical inference, and econometrics, to drive discovery throughout the customer journey. Our solutions are not only critical to the success of Amazon's private brands but also serve as a leading example of discovery technologies across Amazon. We are seeking a Principal Scientist to join our team and lead the development of cutting-edge machine learning models and algorithms that will drive innovative discovery solutions for Amazon Private Brands. In this hands-on role, you will apply your expertise to propose solutions, create software prototypes, and successfully transition these prototypes into production systems using modern software development tools and methodologies. You will also be responsible for scaling these solutions to meet the growing and evolving needs of our customers. As a Principal Scientist, you will play a pivotal role in shaping the vision, design, and roadmap for complex, previously unsolved problems, guiding solutions from inception to implementation. Strong verbal and written communication skills, a self-driven mindset, and the ability to deliver high-quality results in a fast-paced environment are essential for success in this role. 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 have 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).

The Private Brands Discovery team designs innovative machine learning solutions to drive customer awareness for Amazon’s own brands and help customers discover products they love. Private Brands Discovery is an interdisciplinary team of Scientists and Engineers, who incubate and build disruptive solutions using cutting-edge technology to solve some of the toughest science problems at Amazon. To this end, the team employs methods from Natural Language Processing, Deep learning, multi-armed bandits and reinforcement learning, Bayesian Optimization, causal and statistical inference, and econometrics to drive discovery across the customer journey. Our solutions are crucial for the success of Amazon’s own brands and serve as a beacon for discovery solutions across Amazon. This is a high visibility opportunity for someone who wants to have business impact, dive deep into large-scale problems, enable measurable actions on the consumer economy, and work closely with scientists and engineers. As a 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.. With a focus on bias for action, this individual will be able to work equally well with Science, Engineering, Economics and business teams. Key job responsibilities - Drive applied science projects in machine learning end-to-end: from ideation over prototyping to launch. For example, starting from deep scientific thinking about new ways to support customers’ journeys through discovery, you analyze how customers discover, review and purchase Private Brands to innovate marketing and merchandising strategies. - Propose viable ideas to advance models and algorithms, with supporting argument, experiment, and eventually preliminary results. - Invent ways to overcome technical limitations and enable new forms of analyses to drive key technical and business decisions. - Present results, reports, and data insights to both technical and business leadership. - Constructively critique peer research and mentor junior scientists and engineers. - Innovate and contribute to Amazon’s science community and external research communities.

The Private Brands Discovery team designs innovative machine learning solutions to enhance customer awareness of Amazon’s own brands and help customers find products they love. This interdisciplinary team of scientists and engineers incubates and develops disruptive solutions using cutting-edge technology to tackle some of the most challenging scientific problems at Amazon. To achieve this, the team utilizes methods from Natural Language Processing, deep learning, large language models (LLMs), multi-armed bandits, reinforcement learning, Bayesian optimization, causal and statistical inference, and econometrics to drive discovery throughout the customer journey. Our solutions are crucial to the success of Amazon’s private brands and serve as a model for discovery solutions across the company. This role presents a high-visibility opportunity for someone eager to make a business impact, delve into large-scale problems, drive measurable actions, and collaborate closely with scientists and engineers. As a team lead, you will be responsible for developing and coaching talent, guiding the team in designing and developing cutting-edge models, and working with business, marketing, and software teams to address key challenges. These challenges include building and improving models for sourcing, relevance, and CTR/CVR estimation, deploying reinforcement learning methods in production etc. In this role, you will be a technical leader in applied science research with substantial scope, impact, and visibility. A successful team lead will be an analytical problem solver who enjoys exploring data, leading problem-solving efforts, guiding the development of new frameworks, and engaging in investigations and algorithm development. You should be capable of effectively interfacing between technical teams and business stakeholders, pushing the boundaries of what is scientifically possible, and maintaining a sharp focus on measurable customer and business impact. Additionally, you will mentor and guide scientists to enhance the team's talent and expand the impact of your work.

AI is the most transformational technology of our time, capable of tackling some of humanity’s most challenging problems. That is why Amazon is investing in generative AI (GenAI) and the responsible development and deployment of large language models (LLMs) across all of our businesses. Come build the future of human-technology interaction with us. We are looking for a Research Scientist with strong technical skills which includes coding and natural language processing experience in dataset construction, training and evaluating models, and automatic processing of large datasets. You will play a critical role in driving innovation and advancing the state-of-the-art in natural language processing and machine learning. You will work closely with cross-functional teams, including product managers, language engineers, and other scientists. Key job responsibilities Specifically, the Research Scientist will: • Ensure quality of speech/language/other data throughout all stages of acquisition and processing, including data sourcing/collection, ground truth generation, normalization, transformation, cross-lingual alignment/mapping, etc. • Clean, analyze and select speech/language/other data to achieve goals • Build and test models that elevate the customer experience • Collaborate with colleagues from science, engineering and business backgrounds • Present proposals and results in a clear manner backed by data and coupled with actionable conclusions • Work with engineers to develop efficient data querying infrastructure for both offline and online use cases

This is a unique opportunity for a postdoc to work on research projects that investigate state of the art NLP, IR, and LLM approaches for understanding retail products and their pricing. This will include working with billion-scale datasets and investigating how the world knowledge captured by LLMs reflects real world prices, and investigating more advanced prompting and reasoning techniques to construct large knowledge graphs that are specialized for various pricing use cases such as probabilistic price estimation, as well as error detection and correction. Key job responsibilities In this role you will: • Work closely with a senior science advisor, collaborate with other scientists and engineers, and be part of Amazon’s vibrant and diverse global science community. • Publish your innovation in top-tier academic venues and hone your presentation skills. • Be inspired by challenges and opportunities to invent cutting-edge techniques in your area(s) of expertise. About the team The retail pricing science team is a centralized diverse team of STEM scientists that develop statistical, ML, RL, optimization and economic models that drive pricing for products sold by Amazon worldwide, as well as monitoring of prices and experimentations in pricing. The team has a dual focus on competitiveness and long term financial optimality.

Are you passionate about automation, optimization, knowledge extraction, and artificial intelligence through the use of Machine Learning, Computer Vision, Optimization, Natural Language Processing, and Recommender systems? We have a team of experienced scientists with a critical business mission making revolutionary leaps forward in these spaces. On this team you will work with large multimodal datasets to build generative and discriminative models for optimizing large-scale manufacturing and fulfillment processes, analyze and model customer reading behavior to measure engagement and detect risks, and build AI-based systems for helping indie authors make their businesses successful. This will involve combining methods from several science domains with domain knowledge across multiple businesses into sophisticated ML workflows. Our team has mature areas and green-field opportunities. We offer scientific autonomy, value end-to-end ownership, and have a strong customer-focused culture. As a Senior Applied Scientist at Amazon, you will connect with world leaders in your field working on similar problems. You will be working with large distributed systems of data and providing technical leadership to the product managers, teams, and organizations building machine learning solutions. You will be tackling Machine Learning challenges in Supervised, Unsupervised, and Semi-supervised Learning; utilizing modern methods such as deep learning and classical methods from statistical learning theory, detection, estimation. Senior Applied Scientists are specialists with the deep expertise to drive the scientific vision for our products. They are externally aware of the state-of-the-art in their respective field of expertise and are constantly focused on advancing that state-of-the-art for improving Amazon’s products and services. Come join us as we revolutionize the book industry and deliver an amazing experience to our Kindle authors and readers. Key job responsibilities Great candidates for this position will be experts in the areas of data science, machine learning, computer vision, optimization, NLP, or statistics. You will have hands-on experience with multiple science initiatives as well as be able to balance technical leadership with strong business judgment to make the right decisions about technology, models and methodological choices. You will strive for simplicity, and demonstrate significant creativity and high judgment. About the team Kindle Direct Publishing (KDP) and Print On Demand (POD) have empowered a new wave of self-motivated creators, tearing down barriers that once blocked writers from reaching readers. Our team builds rich applications and systems that empower anyone to realize their dream of becoming a published author. We strive to provide an experience that is powerful, yet simple to use and accessible to all. We focus on building systems that enable authors to design high quality digital and print books, reaching readers all around the world. This role will help ensure we maintain the trust of both our Authors and Readers by ensuring all books published to Amazon meet our standards.

Are you passionate about automation, optimization, knowledge extraction, and artificial intelligence through the use of Machine Learning, Computer Vision, Optimization, Natural Language Processing, and Recommender systems? We have a team of experienced scientists with a critical business mission making revolutionary leaps forward in these spaces. On this team you will work with large multimodal datasets to build generative and discriminative models for optimizing large-scale manufacturing and fulfillment processes, analyze and model customer reading behavior to measure engagement and detect risks, and build AI-based systems for helping indie authors make their businesses successful. This will involve combining methods from several science domains with domain knowledge across multiple businesses into sophisticated ML workflows. Our team has mature areas and green-field opportunities. We offer scientific autonomy, value end-to-end ownership, and have a strong customer-focused culture. As an Applied Scientist at Amazon, you will connect with world leaders in your field working on similar problems. You will be working with large distributed systems of data and providing technical leadership to the product managers, teams, and organizations building machine learning solutions. You will be tackling Machine Learning challenges in Supervised, Unsupervised, and Semi-supervised Learning; utilizing modern methods such as deep learning and classical methods from statistical learning theory, detection, estimation. Senior Applied Scientists are specialists with the deep expertise to drive the scientific vision for our products. They are externally aware of the state-of-the-art in their respective field of expertise and are constantly focused on advancing that state-of-the-art for improving Amazon’s products and services. Come join us as we revolutionize the book industry and deliver an amazing experience to our Kindle authors and readers. Kindle Direct Publishing (KDP) and Print On Demand (POD) have empowered a new wave of self-motivated creators, tearing down barriers that once blocked writers from reaching readers. Our team builds rich applications and systems that empower anyone to realize their dream of becoming a published author. We strive to provide an experience that is powerful, yet simple to use and accessible to all. We focus on building tools that enable authors to design high quality digital and print books, reaching readers all around the world. This role will help ensure we maintain the trust of both our Authors and Readers by ensuring all books published to Amazon meet our standards. Great candidates for this position will be experts in the areas of data science, machine learning, computer vision, optimization, NLP, or statistics. You will have hands-on experience with multiple science initiatives as well as be able to balance technical leadership with strong business judgment to make the right decisions about technology, models and methodological choices. You will strive for simplicity, and demonstrate significant creativity and high judgment. Come join us as we continue to revolutionize the book industry!

Are you passionate about automation, optimization, knowledge extraction, and artificial intelligence through the use of Machine Learning, Computer Vision, Optimization, Natural Language Processing, and Recommender systems? We have a team of experienced scientists with a critical business mission making revolutionary leaps forward in these spaces. On this team you will work with large multimodal datasets to build generative and discriminative models for optimizing large-scale manufacturing and fulfillment processes, analyze and model customer reading behavior to measure engagement and detect risks, and build AI-based systems for helping indie authors make their businesses successful. This will involve combining methods from several science domains with domain knowledge across multiple businesses into sophisticated ML workflows. Our team has mature areas and green-field opportunities. We offer scientific autonomy, value end-to-end ownership, and have a strong customer-focused culture. As an Applied Scientist at Amazon, you will connect with world leaders in your field working on similar problems. You will be working with large distributed systems of data and providing technical leadership to the product managers, teams, and organizations building machine learning solutions. You will be tackling Machine Learning challenges in Supervised, Unsupervised, and Semi-supervised Learning; utilizing modern methods such as deep learning and classical methods from statistical learning theory, detection, estimation. Senior Applied Scientists are specialists with the deep expertise to drive the scientific vision for our products. They are externally aware of the state-of-the-art in their respective field of expertise and are constantly focused on advancing that state-of-the-art for improving Amazon’s products and services. Come join us as we revolutionize the book industry and deliver an amazing experience to our Kindle authors and readers. Key job responsibilities Great candidates for this position will be experts in the areas of data science, machine learning, computer vision, optimization, NLP, or statistics. You will have hands-on experience with multiple science initiatives as well as be able to balance technical leadership with strong business judgment to make the right decisions about technology, models and methodological choices. You will strive for simplicity, and demonstrate significant creativity and high judgment. About the team Kindle Direct Publishing (KDP) and Print On Demand (POD) have empowered a new wave of self-motivated creators, tearing down barriers that once blocked writers from reaching readers. Our team builds rich applications and systems that empower anyone to realize their dream of becoming a published author. We strive to provide an experience that is powerful, yet simple to use and accessible to all. We focus on building systems that enable authors to design high quality digital and print books, reaching readers all around the world. This role will help ensure we maintain the trust of both our Authors and Readers by ensuring all books published to Amazon meet our standards.

AI for Domains (AIDO) team is part of Alexa Conversational Assistant Services organization where our mission is to create 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 talented and experienced science leader in the field of LLM, Artificial Intelligence (AI), Natural Language Processing (NLP) 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 solid technical background and extensive experience in leading projects and technical teams. The ideal candidate would also have experiences in developing natural language processing systems (particularly LLM based systems) for industry applications, enjoy operating in highly dynamic and ambiguous environments, be self-motivated to take on challenging problems to deliver customer impact. Key job responsibilities As a Senior Applied Scientist, you will: * Build a strong and coherent team with particular focus on sciences and innovations in LLM technologies for conversation AI applications * Serve as a technical lead on demanding and cross-team projects, and effectively collaborating with multiple cross-organizational teams * Apply technical influence on partner teams, increasing their productivity by sharing your deep knowledge