Seattle

The Applied Scientist in Natural language processing (NLP) within Customer Engagement Tech, Self-Service and Automation team will work on the research, design, and implementation of solutions to key challenges in developing conversational AI systems based on large pretrained language models, that can understand and communicate with customers in a natural and contextually appropriate manner. This involves tackling complex problems in areas such as multi-turn dialogue management, knowledge grounding, and open-ended generation and assessment of dialogue quality and style of the conversational model.Key job responsibilities- Lead the research and development of LLM-based chatbots and conversational AI systems for customer service applications.- Design and implement state-of-the-art NLP and ML models for tasks such as language understanding, dialogue management, and response generation and dialogue quality assessment.- Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to integrate LLM-based solutions into Amazon's customer service platforms.- Develop and implement strategies for data collection, annotation, and model training to ensure high-quality and robust performance of the chatbots.- Conduct experiments and evaluations to measure the performance of the developed models and systems, and identify areas for improvement.- Stay up-to-date with the latest advancements in NLP, LLMs, and conversational AI, and explore opportunities to incorporate new techniques and technologies into Amazon's customer service solutions.- Collaborate with internal and external research communities, participate in conferences and publications, and contribute to the advancement of the field.A day in the lifeWe thrive on solving challenging problems to innovate for our customers. By pushing the boundaries of technology, we create unparalleled experiences that enable us to rapidly adapt in a dynamic environment. Our decisions are guided by data, and we collaborate with engineering, science, and product teams to foster an innovative learning environmentIf you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!Benefits Summary: Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) PlanAbout the teamJoin our team of scientists and engineers who develop and deploy LLM-based Conversational AI systems to enhance Amazon's customer service experience and effectiveness. We work on innovative solutions that help customers solve their issues and get their questions answered efficiently, and associate-facing products that support our customer service associate workforce.BASIC QUALIFICATIONS- 3+ years of building machine learning models or developing algorithms for business application experience- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- Experience in patents or publications at top-tier peer-reviewed conferences or journals- Experience programming in Java, C++, Python or related language- Experience in building speech recognition, machine translation and natural language processing systems (e.g., commercial speech products or government speech projects) ...

Do you want to use your expertise in translating innovative science into impactful products to develop a new business line in emerging stores. If you do, Emerging Stores Payments team would love to talk to you about how to make that a reality.As an applied scientist on our team, you will work with business leaders, scientists, and engineers to translate business and functional requirements into concrete deliverables and define the execution roadmap. You will partner with scientists, and engineers on the design, development, testing, and deployment of scalable ML models. This is a unique, high visibility opportunity for someone who wants to have impact, dive deep into large-scale solutions, enable measurable actions on the employee experience, and work closely with scientists and economists. This role combines science leadership and technical strength.Key job responsibilities- As an Applied Scientist, ML Applications, you will:- Lead applied scientists to deliver machine-learning and AI solutions to production.- Design, develop, and evaluate innovative machine learning solutions to solve diverse challenges and opportunities for Amazon customers- Advance the team's engineering craftsmanship and drive continued scientific innovation as a thought leader and practitioner.- Partner with the engineering team to deploy your models in production.- Partner with scientists from across ML teams within India Consumer Payments to solve complex problems.- Work directly with Amazonians from across the company to understand their business problems and help define and implement scalable ML solutions to solve them.- Mentor and develop junior scientists and developers.BASIC QUALIFICATIONS- 3+ years of building models for business application experience- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- Experience in patents or publications at top-tier peer-reviewed conferences or journals- Experience programming in Java, C++, Python or related language- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing ...

Amazon Advertising is one of Amazon's fastest growing businesses. Amazon's advertising portfolio helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers.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 Creative X team within Amazon Advertising time aims to democratize access to high-quality creatives (images, videos) by building AI-driven solutions for advertisers. To accomplish this, we are investing in latent-diffusion models, large language models (LLM), computer vision (CV), reinforced learning (RL), and image + video and audio synthesis.You will be part of a close-knit team of applied scientists and product managers who are highly collaborative and at the top of their respective fields. We are looking for talented Applied Scientists who are adept at a variety of skills, especially with computer vision, latent diffusion or related foundational models that will accelerate our plans to generate high-quality creatives on behalf of advertisers. Every member of the team is expected to build customer (advertiser) facing features, contribute to the collaborative spirit within the team, publish, patent, and bring cutting edge research to raise the bar within the team. As an Applied Scientist on this team, you will:* Drive end-to-end GenAI projects that have a high degree of ambiguity, scale and complexity.* Build Machine Learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models.* Perform hands-on analysis and modeling of enormous data sets to develop insights that increase traffic monetization and merchandise sales, without compromising the shopper experience.* Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.* Identify and action data collection and labelling in conjunction with team members.* Research new and innovative machine learning approaches.* Present results and explain methods to senior leadership.Why you will love this opportunityAmazon is investing heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate.Key job responsibilitiesThis role is focused on computer vision, latent diffusion models, and the related foundational models to produce generative imagery and videos. You will develop core models that will be the foundational of the core advertising-facing tools that we are launching. You will conduct literature reviews to stay on the cutting edge of the field. You will regularly engage with product managers, who will partner with you to productize your work. A day in the lifeOn a day-to-day basis, you will be doing your independent research and work to develop models, you will participate in sprint planning, collaborative sessions with your peers, and demo new models and share results with peers, other partner teams and leadership.About the teamThe team consists of applied scientists and machine learning engineers. We reside in the Creative X organization, which focuses on creating products for advertisers that will improve the quality of the creatives within Amazon Ads.BASIC QUALIFICATIONS- 3+ years of building ML models- PhD, or Master's degree and 5+ years of CS, CE, ML or related field experience- Experience programming in Python or C++ or a related language- Experience with GenAI model training and tuning ...

Amazon’s builders are able to deliver the magic that gets packages to your front door and safely scale those capabilities to millions of customers because they can find the information they need. Amazon is looking for an Applied Scientist to help drive our discovery strategy for Amazon’s trove of knowledge.Key job responsibilities- Use deep learning, ML and NLP techniques to create scalable solutions for creation and development of language model centric solutions for building personalized assistant systems based on a rich set of structured and unstructured contextual signals- Innovate new methods for contextual knowledge extraction and information retrieval, using language models in combination with other learning techniques, that allows effective grounding in context providers when considering memory, compute, latency and quality- Research in advanced customer understanding and behavior modeling techniques- Collaborate with cross-functional teams of engineers, product managers, and scientists to identify and solve complex problems in personal knowledge aggregation, processing, modeling, and verification- Design and execute experiments to evaluate the performance of state-of-the-art algorithms and models, and iterate quickly to improve results- Communicate results and insights to both technical and non-technical audiences, including through presentations and written reportsA day in the lifeThe Amazon Software Builder Experience (ASBX) organization has a mission of creating the world’s best builder experience across tens of thousands of software engineers, and all Amazon businesses (e.g., AWS, Amazon Stores, etc.). Our Knowledge Tech team in ASBX owns the discovery tools that software developers use to build and innovate on behalf of our customers. This role is for you if you’re passionate about software development, discovery tools, and having world-wide impact across all of Amazon! In addition to delivering results, we also appreciate establishing a work-life-balance, having fun with our co-workers, and supporting an inclusive and collaborative team environment.About the teamAbout AWSDiverse ExperiencesAWS 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 CultureHere 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 GrowthWe’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 BalanceWe 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.BASIC QUALIFICATIONS- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- Experience in patents or publications at top-tier peer-reviewed conferences or journals- Experience programming in Java, C++, Python or related language- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing ...

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 responsibilitiesThe scope of an Applied Scientist II in the 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 project leaders, engineers and business partners to design and implement solutions at scale. The scientist focuses on components of large-scale projects, systems and products and can work independently and with the team to deliver successful solutions with medium to large business impact. The scientist helps our team evolve by actively participating in discussions, team planning, and by staying current on the latest techniques arising from both the scientist community in SPS, the larger Amazon-wide community, and beyond. The scientist develops and introduces tools and practices that streamline the work of the team, and he mentors junior team members and participates in hiring.BASIC QUALIFICATIONS- 3+ years of building models for business application experience- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- Experience programming in Java, C++, Python or related language- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing ...

The AWS Neuron Compiler team is actively seeking applied scientists to join our efforts in developing a state-of-the-art deep learning compiler stack. This stack is designed to optimize application models across diverse domains, including Large Language and Vision, originating from leading frameworks such as PyTorch, TensorFlow, and JAX. Your role will involve working closely with our custom-built Machine Learning accelerators, including Inferentia/Trainium, which represent the forefront of AWS innovation for advanced ML capabilities, powering solutions like Generative AI.The Automated Reasoning Group in the AWS Neuron Compiler team works on the intersection of Artificial Intelligence and program analysis to raise the code quality bar in compiler stack. In this role as an Applied Scientist, you'll be instrumental in designing, developing, and deploying analyzers for ML compiler stages and compiler IRs. You will contribute to the design and semantics of DSLs that our customers love when crafting neural architexctures. You will architect and implement business-critical tooling, publish cutting-edge research, and mentor a brilliant team of experienced scientists and engineers. You will need to be technically capable, credible, and curious in your own right as a trusted AWS Neuron engineer, innovating on behalf of our customers. Your responsibilities will involve tackling crucial challenges alongside a talented engineering team, contributing to leading-edge design and research in compiler technology and deep-learning systems software. Strong experience in programming languages, compilers, program analyzers, and program synthesis engines will be a benefit in this role.A background in machine learning and AI accelerators is preferred but not required. We expect a strong publication record in compilers, IR semantics, static analysis or verification.A day in the lifeAWS 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.Diverse ExperiencesAWS values diverse experiences. Even if you do not meet all of the 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 CultureHere 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 GrowthWe’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 BalanceWe 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. BASIC QUALIFICATIONS- PhD- Experience programming in Java, C++, Python or related language- Experience with neural deep learning methods and machine learning ...

The AWS Core Networking Organization is looking for an Applied Scientist to join our Backbone Enterprise, and Regional Engineering (BERE) team. In this role you will work hand-in-hand with Software Development Engineers, Network Engineering, Finance teams and other partners to drive stability, consistency, and sustainability of the network while never losing sight of the high security bar our customer’s demand. You’ll apply your large-scale understanding of data analysis, computing solutions to develop algorithm, write code and manage services that delight our customers. AWS Global Connectivity and Network Availability (GCNA) is the backbone that connects the global AWS network. Focused on controlling the internet traffic that allows users to access their information and applications regardless of where they are in the world. GCNA is responsible for building and designing a complex backbone network that allows internet traffic to flow efficiently between data centers and customers. Come join us and enjoy the satisfaction that comes from successfully building software to scale and provide insights about one of the world’s biggest networks. 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 CultureHere 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.Diverse ExperiencesAWS 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. 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. Mentorship & Career GrowthWe’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. Key job responsibilitiesApplied Scientist will develop data analysis alogrithm and software that will allow AWS to understand and tailor the network for our internal and external customer needs. The networking teams need detailed information about traffic distribution, performance, infrastructure cost to design, deploy and operate the optimal network.Design, implement, test, deploy and maintain innovative data analysis algorithm.Write supporting software in collaboration with and according to Senior Software Engineer design.Work in an agile, startup-like development environment, where you are always working on the most important stuff. Take ownership and do what it takes to get the job done. Learn from others and help grow those in your team to achieve their bestA day in the lifeEngineers in the Backbone Enterprise and Regional Engineering (BERE) organization have a wide range of responsibilities: we work with internal partners to develop and implement the next gen platforms along with the tooling ecosystems to support with these platforms driving efficiency and scalability through the automation of builds, configuration deployment, and the scaling of capacity. As our network is one of the largest in the world, there is no blue print at our scale allowing our engineers to develop solutions to the complex challenges that we face daily. We encourage durable solutions that look around corners while taking into consideration our customer needs from a cost, performance, and reliability perspective. Our team develops tooling that provides the required visibility and control of traffic across the network, while prioritizing the automatic mitigation of events to minimize the impact to our customers during events. Lead discussion with our partners to investigate integration solution. Work with customer on data information requirements for business workflow. Develop algorithm in collaboration with teammatesManage customers during problem resolution and operating efficiently under pressure. Sit at the computer during scheduled work hours with appropriate breaks while maintaining a high level of alertness and attention to detail. About the teamAWS Infrastructure Services (AIS)AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we’re looking for talented people who want to help. You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion.Within AWS Networking, the Backbone Enterprise, and Regional Engineering (BERE) organization is responsible for the design, implementation, and operations of a wide array of networking infrastructure that provide global connectivity between all AWS Regions and edge locations. BERE provides the massive scale required to support our AWS customers and internal services, via a network that grows by 70% annually. In addition, they have teams that are responsible for the design and operation of our global corporate office and data center network, allowing tens of thousands of Amazonians to perform their daily tasks in support of our customersBASIC QUALIFICATIONS- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- 3+ years of building models for business application experience- Experience programming in Java, C++, Python or related language- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing ...

Are you motivated to explore research in ambiguous spaces? Are you interested in conducting research that will improve associate, employee and manager experiences at Amazon? Do you want to work on an interdisciplinary team of scientists that collaborate rather than compete? Join us at PXT Central Science!The People eXperience and Technology Central Science Team (PXTCS) uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, wellbeing, and the value of work to Amazonians. We are an interdisciplinary team that combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal.Key job responsibilitiesAs an Applied Scientist for People Experience and Technology (PXT) Central Science, you will be working with our science and engineering teams, specifically on re-imagining Generative AI Applications and Generative AI Infrastructure for HR. Applying Generative AI to HR has unique challenges such as privacy, fairness, and seamlessly integrating Enterprise Knowledge and World Knowledge and knowing which to use when. In addition, the team works on some of Amazon’s most strategic technical investments in the people space and support Amazon’s efforts to be Earth’s Best Employer. In this role you will have a significant impact on 1.5 million Amazonians and the communities Amazon serves and ample scope to demonstrate scientific thought leadership and scientific impact in addition to business impact.You will also play a critical role in the organization's business planning, work closely with senior leaders to develop goals and resource requirements, influence our long-term technical and business strategy, and help hire and develop science and engineering talent. You will also provide support to business partners, helping them use the best scientific methods and science-driven tools to solve current and upcoming challenges and deliver efficiency gains in a changing markeAbout the teamThe AI/ML team in PXTCS is working on building Generative AI solutions to reimagine Corp employee and Ops associate experience. Examples of state-of-the-art solutions are Coaching for Amazon employees (available on AZA) and reinventing Employee Recruiting and Employee Listening.BASIC QUALIFICATIONS- 3+ years of building models for business application experience- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- Experience in patents or publications at top-tier peer-reviewed conferences or journals- Experience programming in Java, C++, Python or related language- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing ...

We’re pioneering the development of a cutting-edge Seller Foundation Model designed to capture seller interactions, predict future behaviors, and simulate responses across varied conditions. Our goal is to enhance support for our diverse seller community and foster improved outcomes for both sellers and the broader Amazon ecosystem. We are looking for passionate innovators who are excited about technology, driven by customer experience, and eager to make a lasting impact on the industry.In this role, you'll collaborate with top-tier scientists, engineers, and technical program managers (TPMs) to drive innovation and deliver exceptional results for our customers. You will lead the effort to leverage Amazon's large-scale computing resources to accelerate advances in machine learning and foundation models. If you’re enthusiastic about joining a dynamic and motivated team, this is your chance to be part of an exciting journey. Apply now and help us shape the future of seller support at Amazon!BASIC QUALIFICATIONS- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- Experience in patents or publications at top-tier peer-reviewed conferences or journals- Experience programming in Java, C++, Python or related language- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing ...

Amazon's Pricing & Promotions Science is seeking a driven Applied Scientist to harness planet scale multi-modal datasets, and navigate a continuously evolving competitor landscape, in order to regularly generate fresh customer-relevant prices on billions of Amazon and Third Party Seller products worldwide.We are looking for a talented, organized, and customer-focused applied researchers to join our Pricing and Promotions Optimization science group, with a charter to measure, refine, and launch customer-obsessed improvements to our algorithmic pricing and promotion models across all products listed on Amazon.This role requires an individual with exceptional machine learning and reinforcement learning modeling expertise, excellent cross-functional collaboration skills, outstanding business acumen, and an entrepreneurial spirit. We are looking for an experienced innovator, who is a self-starter, comfortable with ambiguity, demonstrates strong attention to detail, and has the ability to work in a fast-paced and ever-changing environment.Key job responsibilities- See the big picture. Understand and influence the long term vision for Amazon's science-based competitive, perception-preserving pricing techniques- Build strong collaborations. Partner with product, engineering, and science teams within Pricing & Promotions to deploy machine learning price estimation and error correction solutions at Amazon scale- Stay informed. Establish mechanisms to stay up to date on latest scientific advancements in machine learning, neural networks, natural language processing, probabilistic forecasting, and multi-objective optimization techniques. Identify opportunities to apply them to relevant Pricing & Promotions business problems- Keep innovating for our customers. Foster an environment that promotes rapid experimentation, continuous learning, and incremental value delivery.- Successfully execute & deliver. Apply your exceptional technical machine learning expertise to incrementally move the needle on some of our hardest pricing problems.A day in the lifeWe are hiring an applied scientist to drive our pricing optimization initiatives. The Price Optimization science team drives cross-domain and cross-system improvements through:* invent and deliver price optimization, simulation, and competitiveness tools for Sellers. * shape and extend our RL optimization platform - a pricing centric tool that automates the optimization of various system parameters and price inputs. * Promotion optimization initiatives exploring CX, discount amount, and cross-product optimization opportunities.* Identifying opportunities to optimally price across systems and contexts (marketplaces, request types, event periods)Price is a highly relevant input into many partner-team architectures, and is highly relevant to the customer, therefore this role creates the opportunity to drive extremely large impact (measured in Bs not Ms), but demands careful thought and clear communication.About the teamAbout the team: the Pricing Discovery and Optimization team within P2 Science owns price quality, discovery and discount optimization initiatives, including criteria for internal price matching, price discovery into search, p13N and SP, pricing bandits, and Promotion type optimization. We leverage planet scale data on billions of Amazon and external competitor products to build advanced optimization models for pricing, elasticity estimation, product substitutability, and optimization. We preserve long term customer trust by ensuring Amazon's prices are always competitive and error free.BASIC QUALIFICATIONS- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- Experience programming in Java, C++, Python or related language- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing- 2+ years of hands-on predictive modeling and large data analysis experience- Experience in solving business problems through machine learning, data mining and statistical algorithms ...

Interested in helping build Prime's content and offer experimentation system to drive huge business impact on millions of customers? Join our team of Scientists and Engineers developing algorithms to adaptively generate and experiment on new content, personalize, and optimize the customer experience with Amazon Prime. This includes identifying who our customers are and providing them with personalized relevant content. As an ML lead, you will partner directly with product owners to intake, build, and directly apply your modeling solutions.There are numerous scientific and technical challenges you will get to tackle in this role, such as adaptive experimentation, structured multi-armed bandits and its application to various types of experimentation and multi-step optimization leading to reinforcement learning of the customer journey. We employ techniques from LLM's, Gen AI, deep learning, multi-armed bandits, optimization, and RL.As the central science team within Prime, our expertise gets routinely called upon to weigh in on a variety of topics. We also emphasize the need and value of scientific research and have developed a strong publication and patent record (internally/externally) which you will be a part of.You will also utilize and be exposed to the latest in ML technologies and infrastructure: AWS technologies (EMR/Spark, Redshift, Sagemaker, DynamoDB, S3, ...), various ML algorithms and techniques (Random Forests, Neural Networks, supervised/unsupervised/semi-supervised/reinforcement learning, LLM's), and statistical modeling techniques.Major responsibilities - Build and develop machine learning models and supporting infrastructure at TB scale, in coordination with software engineering teams. - Leverage Bandits and Reinforcement Learning for Experimentation and Optimization Systems. - Develop offline policy estimation tools and integrate with reporting systems. - Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation. - Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes. - Work closely with the business to understand their problem space, identify the opportunities and formulate the problems. - Use machine learning, data mining, statistical techniques and others to create actionable, meaningful, and scalable solutions for the business problems. - Design, develop and evaluate highly innovative models and statistical approaches to understand and predict customer behavior and to solve business problems. BASIC QUALIFICATIONS- 3+ years of building models for business application experience- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- Experience programming in Java, C++, Python or related language- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing ...

Interested in helping build Prime's content and offer personalization system to drive huge business impact on millions of customers? Join our team of Scientists and Engineers developing algorithms to adaptively generate, optimize, and personalize the customer experience with Amazon Prime. This includes identifying who our customers are and providing them with personalized relevant content. As an ML scientist, you will partner directly with product owners to intake, build, and directly apply your modeling solutions.There are numerous scientific and technical challenges you will get to tackle in this role, such as deep learning and reinforcement learning, and their application to various types of contextual, multi-step optimization of the customer journey. We employ techniques from supervised learning, multi-armed bandits, optimization, and RL - while this role is focused on the space of discriminative and generative recommender systems.As the central science team within Prime, our expertise gets routinely called upon to weigh in on a variety of topics. We also emphasize the need and value of scientific research and have developed a strong publication and patent record (internally/externally) which you will be a part of.You will also utilize and be exposed to the latest in ML technologies and infrastructure: AWS technologies (EMR/Spark, Redshift, Sagemaker, DynamoDB, S3, ...), various ML algorithms and techniques (Random Forests, Neural Networks, supervised/unsupervised/semi-supervised/reinforcement learning, LLMs), and statistical modeling techniques.Major responsibilities - Build and develop machine learning models and supporting infrastructure at TB scale, in coordination with software engineering teams. - Leverage Bandits, Supervised Learning, and Reinforcement Learning for Contextual Recommendation and Optimization Systems. - Develop offline policy estimation tools and integrate with reporting systems. - Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation. - Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes. - Work closely with the business to understand their problem space, identify the opportunities and formulate the problems. - Use machine learning, data mining, statistical techniques and others to create actionable, meaningful, and scalable solutions for the business problems. - Design, develop and evaluate highly innovative models and statistical approaches to understand and predict customer behavior and to solve business problems. BASIC QUALIFICATIONS- Experience programming in Java, C++, Python or related language- PhD in computer science, mathematics, statistics, machine learning or equivalent quantitative field- Experience applying theoretical models in an applied environment ...

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.BASIC QUALIFICATIONS- PhD, or Master's degree and 2+ years of CS, CE, ML or related field experience- Experience programming in Java, C++, Python or related language- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing ...

We are looking for an Applied Scientist to push the boundaries of machine learning and simulation at scale. As a member of PXT Finance, you will own the development of distributed simulations for population dynamics forecasting and expense planning. This will include the development of state-of-the-art time series and survival models leveraging deep learning techniques such as Graph Neural Networks, Recurrent Neural Networks, and Transformers. Working on a cross functional team, you will collaborate closely with data scientists, software engineers, product managers and finance managers. This is a high-impact role where you will develop applications that will be used by planners and decision makers across Amazon.Key job responsibilities- Lead the development of distributed simulations for population dynamics forecasting and expense planning. - Implement state-of-the-art graph deep learning models for tasks such as node survival analysis and spatio-temporal time series forecasting. - Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to integrate forecasting solutions into Amazon’s cost planning processes.- Leverage big data processing frameworks such as Apache Spark to ingest high volume headcount data into machine learning workflows. - Apply GPU programming frameworks such as PyTorch and CUDA to deploy fast and scalable planning solutions.- Push the boundary of machine learning-based simulation and publish results in peer-reviewed journals. A day in the lifeAs an Applied Scientist in Finance you will focus on data science and machine learning engineering workflows. This means ownership of models from the idea stage all the way to production deployment. In addition to programming and system design you'll also work with customers, partners, and leaders to guide project decisionsAbout the teamWe are a small team of scientists with a focus on forecasting and simulation applications for expense and headcount planning. By keeping pace with the advance of machine learning technology are rapidly scaling our productivity and impact. We strive to deliver efficient and innovative solutions by constantly developing and improving our research and engineering skills. BASIC QUALIFICATIONS- 3+ years of building models for business application experience- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- Experience programming in Java, C++, Python or related language- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing ...

Are you passionate about AI for recommendation systems? Do you want to influence the content that customers see at Amazon.com? Our recommendation services team designs and implements scalable machine learning solutions to personalize and optimize customer experience across Amazon retail pages. We are currently expanding in New York, and are looking for an applied scientist to join us in this exciting journey. As an Applied Scientist, you will: - Push the boundaries of real-world ranking, recommendation, and optimization systems - Support science, engineering and product development on a scale only seen at Amazon. - Champion and define best practices to maximize learnings while mentoring more junior scientists and engineers. - Obsess over customer needs and satisfaction. - Create intellectual property, influence others while demonstrating significant creativity and being vocally self-critical. - Shape product definitions and objective and surface signals on how these objectives meet long term customer needs. - Translate metrics & signals into actionable plans to calibrate individual components. - Operate hands-on and as an implementor of algorithms and models delivered to production systems. - Help define customer focused research initiatives.Please visit https://www.amazon.science for more information. BASIC QUALIFICATIONS- 3+ years of building models for business application experience- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- Experience programming in Java, C++, Python or related language- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing ...

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!SB ResponseModel team's role is to support the prediction of Click Through Rates, View Rates, and Conversion Rates for Sponsored Brands. Our goal is to enhance advertising efficiency, improve the shopper experience, and promote SB product recognition. We collaborate with different teams across the Amazon Ads to build scalable online and offline ML infrastructure systems to accelerate science innovations, facilitate business growth and promote technology innovation.As an Applied Scientist on this team, you will:- Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity.- Perform hands-on analysis and modeling of enormous data sets to develop insights that increase traffic monetization and merchandise sales, without compromising the shopper experience.- Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models.- Run A/B experiments, gather data, and perform statistical analysis.- Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.- Research new and innovative machine learning approaches.- Recruit Applied Scientists to the team and provide mentorship.Impact and Career GrowthYou will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven fundamentally from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding.BASIC QUALIFICATIONS- 3+ years of building models for business application experience- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- Experience programming in Java, C++, Python or related language ...

When customers search for products on the Amazon website, they often see brand advertisements displayed right below the search bar. These ads are part of the Sponsored Brands (SB) program. Our team, the SB Search and Relevance team, works on solving challenges to retrieve the most relevant ads for a customer's search query. A customer's search query is typically a short, free-form text consisting of just a few words. Our algorithm needs to understand the customer's underlying intention from this limited information. At the same time, each advertisement consists of various elements like text descriptions, images, videos, and more. Our algorithm also needs to comprehend the content of these ads and identify the most relevant one from the large pool of ad candidates.As Amazon's advertising business is growing rapidly, we are looking for experienced applied scientists. As an Applied Scientist on this team, you will:Build deep learning models to improve our search relevance for online advertising.- Apply deep learning and natural language processing to improve information retrieval and relevance.- Design and run A/B experiments. Evaluate the impact of your optimizations and communicate your results to various business stakeholders.- Optimize deep learning inference latency by utilizing methods like knowledge distillation.- Work with software development engineers and write code to bring models into production.Impact and Career Growth- You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! - Define a long-term science vision for our advertising business, driven fundamentally from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. - This role combines science leadership, organizational ability, technical strength, product focus, and business understanding.Team video https://youtu.be/zD_6Lzw8raEBASIC QUALIFICATIONS- 3+ years of building models for business application experience- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- Experience programming in Java, C++, Python or related language- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing ...

Amazon Web Services is looking for world class scientists to join the Security Analytics and AI Research team within AWS Security Services. This group is entrusted with researching and developing core data mining and machine learning algorithms for various AWS security services like GuardDuty (https://aws.amazon.com/guardduty/). In this group, you will invent and implement innovative solutions for never-before-solved problems. If you have passion for security and experience with large scale machine learning problems, this will be an exciting opportunity.The AWS Security Services team builds technologies that help customers strengthen their security posture and better meet security requirements in the AWS Cloud. The team interacts with security researchers to codify our own learnings and best practices and make them available for customers. We are building massively scalable and globally distributed security systems to power next generation services.Key job responsibilities* Invent, implement, and deploy state of the art machine learning and deep learning models and systems for information security applications.* Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both quantitative and business judgment.* Collaborate with software engineering teams to integrate successful experiments into large scale, highly complex production services.* Report results in a scientifically rigorous way.* Interact with security engineers, product managers and related domain experts to dive deep into the types of challenges that we need innovative solutions for.About the teamWhy AWSAmazon 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 CultureHere 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 BalanceWe 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 GrowthWe’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 ExperiencesAmazon 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.BASIC QUALIFICATIONS- PhD, or Master's degree and 4+ years of field experience in Computer Science, Machine Learning, Operational Research, Statistics or a related quantitative field.- Working knowledge of natural language processing (NLP) or large language model (LLM).- Experience with unsupervised learning, semi-supervised learning and continual learning.- Hands-on experience in predictive modeling and analysis.- Algorithm development experience.- Proficient in coding with at least one of the following: Java, C++, Python, Scala, Rust or other programming language.- Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning. ...

Our team's mission is to improve Shopping experience for customers interacting with Amazon devices via voice. We research and develop advanced state-of-the-art speech and language modeling technologies. Do you want to be part of the team developing the latest technology that impacts the customer experience of ground-breaking products? Then come join us and make history.Key job responsibilitiesWe are looking for a passionate, talented, and inventive Applied Scientist with a background in Machine Learning to help build industry-leading Speech and Language technology.As an Applied Scientist at Amazon you will work with talented peers to develop novel algorithms and modelling techniques to drive the state of the art in speech synthesis.Position Responsibilities:* Participate in the design, development, evaluation, deployment and updating of data-driven models for Speech and Language applications.* Participate in research activities including the application and evaluation of Speech and Language techniques for novel applications.* Research and implement novel ML and statistical approaches to add value to the business.* Mentor junior engineers and scientists.BASIC QUALIFICATIONS- Experience developing experimental and analytic plans for data modeling processes, use of strong baselines, ability to accurately determine cause and effect relations- PhD- Experience in Python, Perl, or another scripting language ...

The Selling Partner Experience (SPX) organization strives to make Amazon the best place for Selling Partners to do business. The SPX Science team is building an AI-powered conversational assistant to transform the Selling Partner experience. The Selling Assistant is a trusted partner and a seasoned advisor that’s always available to enable our partners to thrive in Amazon’s stores. It takes away the cognitive load of selling on Amazon by providing a single interface to handle a diverse set of selling needs. The assistant always stays by the seller's side, talks to them in their language, enables them to capitalize on opportunities, and helps them accomplish their business goals with ease. It is powered by the cutting edge of Generative AI, going beyond a typical chatbot to provide a powerful, personalized experience to sellers running real businesses, large and small.Do you want to join an innovative team of scientists, engineers, product and program managers who use state-of-the-art Generative AI and Machine Learning technologies to help Amazon create a delightful Selling Partner experience? Do you want to build solutions to real business problems by automatically understanding and addressing sellers’ challenges, needs and opportunities? Are you excited by the prospect of contributing to one of Amazon’s most strategic Generative AI initiatives? If yes, then you may be a great fit to join the Selling Partner Experience Science team (SPeXSci).Key job responsibilities- Use state-of-the-art Machine Learning and Generative AI techniques to create the next generation of the tools that empower Amazon's Selling Partners to succeed.- Design, develop and deploy highly innovative models to interact with Sellers and delight them with solutions.- Work closely with teams of scientists and software engineers to drive real-time model implementations and deliver novel and highly impactful features.- Establish scalable, efficient, automated processes for large scale data analyses, model benchmarking, model validation and model implementation.- Research and implement novel machine learning and statistical approaches.- Participate in strategic initiatives to employ the most recent advances in ML in a fast-paced, experimental environment.About the teamSelling Partner Experience Science (SPeXSci) is a growing team of scientists, engineers and product leaders engaged in the research and development of the next generation of ML-driven technology to empower Amazon's Selling Partners to succeed. We draw from many science domains, from Natural Language Processing to Computer Vision to Optimization to Economics, to create solutions that seamlessly and automatically engage with Sellers, solve their problems, and help them grow. We are focused on building seller facing AI-powered tools using the latest science advancements to empower sellers to drive the growth of their business. We strive to radically simplify the seller experience, lowering the cognitive burden of selling on Amazon by making it easy to accomplish critical tasks such as launching new products, understanding and complying with Amazon’s policies and taking actions to grow their business.BASIC QUALIFICATIONS- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- 3+ years of building machine learning models or developing algorithms for business application experience- Experience programming in Java, C++, Python or related language- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing ...