Seattle

Amazon's Devices Economic Value team enables measurement and optimization of Amazon Devices long-term value to help Amazon build better products for their customers. Delivering lasting value to customers is in Amazon's DNA and we are at the core of how the Devices business prioritizes its investments in innovation and optimization on behalf of customers. Join us to be a part of the team that is at the core of understanding how Amazon Devices drive deeper customer engagement and helps the business make decisions about how to optimize and balance between short term monetization and long term value creation for Amazon Device users. We are seeking a skilled Applied Scientist to build the future of long term value measurement and optimization for Amazon Devices.About you:We are looking for a talented Applied Scientist to work closely with engineering and multiple partner teams to continuously identify opportunities to enable and accelerate impactful business initiatives related to measurement and optimization of Devices long-term value. Strong technical skills, judgment and communication skills, and continuous focus on the actionability of our models and insights for our customers are essential for the success in this role.About us together:We're going to help Amazon make better decisions in our Devices business by measuring the long-term value generated via purchase and engagement with devices and integrating it into decision making across the whole business ranging from high level strategic decisions to production level optimizations in promotions, pricing and marketing. Our work will inform some of the biggest decisions in the Devices business. We have decades of combined experience in many areas of science, product and engineering so it's a great environment in which to learn and grow. Optimization for long-term value is one of the most challenging areas of research and development today and this is a chance to learn and enhance how it works in a company that keeps this focus at its core. The candidate's responsibilities will include:- Build Machine Learning models, conduct statistical/machine learning analyses, or design experiments to measure the value of the business and its many features- Partner closely with Business, Finance, Science, and Tech partners to implement production solutions- Independently identify new opportunities for leveraging science insights and models in the Devices business- Write both technical science papers and business-facing documents to clearly explain complex technical conceptsBASIC QUALIFICATIONS- 2+ 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 ...

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 ...

This is a unique opportunity to join a small, high-impact team working on AI agents for health initiatives. You will collaborate with experts across domains to develop AI solutions to customers. You'll have the chance to work on projects that could significantly impact how individuals manage their daily health and long-term wellness goals.If you're passionate about solving meaningful problems in healthcare through AI, this role is for you. Technically, you'll work on large-scale data processing, algorithm development, and AI agent implementation. You'll have the chance to learn and innovate alongside healthcare experts.In this early-stage initiative, you'll have significant influence on what we build and how we build it. This is an excellent opportunity for high-judgment scientists to demonstrate impact and make key decisions.Key job responsibilitiesImplement state-of-the-art techniques for LLMs and AI agents in health contexts.Develop personalization features for AI agents and invent new methods to tailor health recommendations, interpret individual health data, and provide context-aware wellness guidance.Analyze and experiment with LLM architectures.Contribute to internal knowledge sharing and research papersCollaborate with other teams on Amazon AI health projectsA day in the lifeYou'll work with a cross-disciplinary team to plan and deliver AI-driven health and wellness experiences. You'll shape product features, user experience, and team processes for rapid iteration. Expect to challenge conventional approaches and dive deep into customer problems in this evolving field.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’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 ...

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 ...

Amazon's Pricing & Promotions Optimization Science is seeking a motivated 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 and promotions on billions of Amazon and Third Party Seller products worldwide.We are looking for a talented, organized, and customer-focused applied scientists to define, measure, and launch customer-obsessed solutions across all products listed on Amazon.This role requires an individual with exceptional AI and data science expertise, excellent cross-functional collaboration skills, strong 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/promotion techniques- Build strong collaborations. Partner with product, engineering, and science teams within and outside Pricing & Promotions org to deploy AI/ML 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, reinforcement learning, 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 science and tech problemsAbout the teamAbout the team: the Pricing and Promotion Optimization team within P2 Science leads the definition, measurement, and implementation of the state-of-the-art AI and data science solutions to improve price/promotion quality across the site and bring value to customers, sellers and Amazon. 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 ...

Here at Amazon, we embrace our differences. We are committed to furthering our culture of diversity and inclusion of our teams within the organization.We’re working on the future. If you are seeking an iterative fast-paced environment where you can drive innovation, apply state-of-the-art technologies to solve extreme-scale real world challenges, and provide visible benefit to end-users, this is your opportunity.Come work on the Prime Air team! We're looking for an outstanding applied scientist who combines superb technical, research and analytical capabilities with a demonstrated ability to get the right things done quickly and effectively. This person must be comfortable working with a team of top-notch scientists and engineers. We’re looking for people who innovate and love solving hard problems. You will work hard, have fun, and of course, make history!BASIC QUALIFICATIONS- PhD, or Master's degree and 5+ years of deep learning, computer vision, human robotic interaction, algorithms implementation experience- Experience developing and implementing deep learning algorithms, particularly with respect to computer vision algorithms- Experience building machine learning models or developing algorithms for business application- Experience programming in Java, C++, Python or related language- Experience working with data captured from sensors and associated signal processing- Experience with hardware/ integration and real-time systems ...

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 ...

Lead the development of AI models to power Amazon's eCommerce ontology - a key source of product knowledge driving exceptional customer experiences. Applied Scientists in this role solve problems related to product classification, attribute extraction, ontology modeling, data integration and enrichment, and scalable knowledge services. It's challenging due to the vast scale, heterogeneous data sources, and evolving domains, but exciting for pushing boundaries in ML, NLP, and knowledge representation research.If you're passionate about driving innovation at scale, we want to hear from you!Key job responsibilities- Lead the research and development of novel AI solutions to enrich and curate Amazon's product ontology (Product Knowledge) at scale- Develop scalable data processing pipelines and architectures to ingest, transform, and enrich product data from various sources (seller listings, customer reviews, etc.)- Collaborate with engineers to design and implement robust services- Work closely with product managers, stakeholders, and subject matter experts to identify opportunities for innovation and drive the roadmap for Product Knowledge- Mentor and upskill junior scientists and engineers, fostering a culture of continuous learning and knowledge sharing- Communicate complex technical concepts and research findings effectively to diverse audiences, including leadership, cross-functional teams, and the wider scientific community- Stay up-to-date with the latest advancements in machine learning, natural language processing, knowledge representation, and related fields, and identify opportunities to apply them to Product KnowledgeA day in the lifeThe Amazon product ontology is a structured knowledge base representing product types, attributes, classes, and relationships. It standardizes product data, enabling enhanced customer experiences through improved search and recommendations, streamlined selling processes, and internal data enrichment across Amazon's eCommerce ecosystem.You will work with following stakeholders:- Product Managers represent customer experiences and selling partner experiences- Category Leaders (e.g., apparel, electronics) provide domain knowledge and guidance as subject matter experts- Engineers build and maintain data pipelines and services in production- Ontologists design data models and define guidelines - Other Applied Scientists collaborate on research and innovationAbout the teamThe Product Knowledge team at Amazon is dedicated to creating the industry-standard eCommerce product and services ontology. Our diverse team of applied scientists, engineers, ontologists and subject matter experts build a comprehensive ontology enabling exceptional customer and selling partner experiences through high-quality, contextual product knowledge at scale.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 ...

Are you interested in shaping the future of Advertising and B2B Sales? We are a growing science and engineering team with an exciting charter and need your passion, innovative thinking, and creativity to help take our products to new heights.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 are strategically important to our businesses driving long term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day!Within the Advertising Sales organization, we are building a central AI/ML team and are seeking top science talent to build new, science-backed services to drive success for our customers. Our goal is to transform the way account teams operate by creating actionable insights and recommendations they can share with their advertising accounts, and ingesting Generative AI throughout their end-to-end workflows to improve their work efficiency.As a part of our team, you will bring deep expertise in quantitative modeling (forecasting, recommender systems, reinforcement learning, causal inferencing or generative artificial intelligence) to build and refine models that can be implemented in production. You will be a key contributor as we chart new courses with our ad sales support technologies, and you have the communication skills necessary to explain complex technical approaches to a variety of stakeholders and customers. As a core team member, you will have the excitement to take iterative approaches to tackle big, long-term problems.Why you will love this opportunity: Amazon has invested 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 ads 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.Impact and Career Growth: You will invent new experiences and influence customer-facing experiences; this is your opportunity to work within the fastest growing businesses across all of Amazon! Define a scientific vision for our advertising sales business, driven from our customers' needs, translating that direction into specific plans for scientists, engineers and product teams. This role combines scientific innovation, organizational ability, technical strength, product focus, and business understanding.Key job responsibilities- Conceptualize and lead state-of-the-art research on new Machine Learning and Generative Artificial Intelligence solutions to optimize all aspects of the Ad Sales business- Guide the technical approach for the design and implementation of successful models and algorithms in support of expert cross-functional teams delivering on demanding projects- Conduct deep data analysis to derive insights to the business, and identify gaps and new opportunities- Run regular A/B experiments, gather data, and perform statistical analysis- Work closely with software engineers to deliver end-to-end solutions into production- Improve the scalability, efficiency and automation of large-scale data analytics, model training, deployment and servingAbout the teamSales AI is a central science and engineering organization within Amazon Advertising Sales that powers selling motions and account team workflows via state-of-the-art of AI/ML services. Sales AI is investing in a range of sales intelligence models, including the development of advertiser insights, recommendations and Generative AI-powered applications throughout account team workflows.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 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 ...

The Seller Fees team owns the end-to-end fees experience for two million active third party sellers worldwide. We own the fee technology, fee strategy, seller experience, fee integrity, fee science and data engineering to provide scalable technology to monetize all services available to third-party sellers. We are looking for an Applied Scientist with strong engineering background to join us on improving accuracy in billion-scale fee transactions worldwide and enhancing models to provide better Seller experience with fee services. In this role you will develop large scale deep learning systems to drive the fee calculations that impact hundreds of millions of products from third-party sellers in the Amazon product catalog. You will leverage sophisticated statistical methods, supervised and unsupervised learning models, as well as generative AI that can scale to production requirements worldwide. You will participate in developing models at the intersection of deep learning and causal inference. You will collaborate with other Applied Scientists, Research Scientists, Data Scientists, Economists, Software Developers, and Product Managers. If big and rich data, large scale deep learning and building intelligent systems excites you, we would like you to be on our team!Key job responsibilitiesResponsibilities:. Design measurable and scalable science solutions that can be adopted across stores worldwide with different languages, policy and requirements.· Integrate AI (both generative and symbolic) into compound agentic workflows to transform complex business systems into intelligent ones for both internal and external customers. · Develop large scale classification and prediction models using the rich features of text, image and customer interactions and state-of-the-art techniques.· Research and implement novel machine learning, statistical and econometrics approaches.· Write high quality code and implement scalable models within the production systems.· Stay up to date with relevant scientific publications.· Collaborate with business and software teams both within and outside of the fees organization.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- 2+ years of deep learning, computer vision, human robotic interaction, algorithms implementation 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 solving business problems through machine learning, data mining and statistical algorithms experience ...

At Amazon, we strive every day to be Earth’s most customer centric company. Selling Partner Support Engagement (SPSE) Science delivers on this by building AI-enhanced experiences and automation that help to provide world class support to our global network of selling partners. We building at the cutting edge of Gen AI applications, working to tackle the many challenges that we confront caused by the volume, diversity, and complexity of our selling partner's needs… and we are always striving to do better.Do you want to join an innovative team who creatively applies techniques ranging from statistics and traditional machine learning to deep learning, natural language processing, and generative models? A team that drives our flywheel of improvement by hunting down opportunities to do better that are buried in tens of millions of solved cases? Are you interested in helping us redefine what world class support can be in an age of automation and AI, while prizing human empathy and ingenuity?The SPSE Science Team is looking for an Applied Scientist to build statistical and machine learning solutions that help us understand and solve our most challenging problems. We need to better understand our Sellers and the problems they face, to augment our human workforce with smarter tools, to anticipate problems so that we are prepared to deal with them, to automatically diagnose and resolve issues, and to identify opportunities to grow and improve.In this role, you will have ownership of the end-to-end development of solutions to complex problems and you will play an integral role in strategic decision-making. You will also work closely with engineers, operations teams, product owners to build ML pipelines, platforms and solutions that solve problems of defect detection, automation, and workforce optimization.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 ...

Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the limits. We focus on creating entirely new products and services with a goal of positively impacting the lives of our customers. No industries or subject areas are out of bounds. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have thirteen employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We are constantly learning through programs that are local, regional, and global. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. As a Applied Scientist at the intersection of machine learning and the life sciences, you will participate in developing exciting products for customers. Our team rewards curiosity while maintaining a laser-focus in bringing products to market. Competitive candidates are responsive, flexible, and able to succeed within an open, collaborative, entrepreneurial, startup-like environment. At the forefront of both academic and applied research in this product area, you have the opportunity to work together with a diverse and talented team of scientists, engineers, and product managers and collaborate with others teams.BASIC QUALIFICATIONS- PhD in computer science, machine learning, engineering, or related fields- Experience with programming languages such as Python, Java, C++- Expert knowledge of machine learning and deep learning; solid understanding of large language models. ...

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. As a core product offering within our advertising portfolio, Sponsored Products (SP) helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The SP organization's 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!Our team, Off-Search Sourcing and Relevance, has a mission to deliver relevant and useful shopping experience at non-Search pages at Amazon.com. We innovate technology solutions, develop machine learning models that incorporate deep product and shopper understanding, and conduct A/B tests to ensure that we identify all useful and relevant advertisements and provide them to downstream systems for click through prediction and ad auction.We are looking for a passionate Applied Scientist who has technical expertise in information retrieval, Natural Language Processing (NLP), and Large Language Models (LLM). In addition to having hands-on experience in building ML-based solutions, an ideal candidate should be able to create and articulate a customer-centric science vision, show willingness to continuously learn about new scientific approaches, and enjoy operating in startup-like environment. Key job responsibilities* Conduct deep data analysis to derive insights to the business, and identify gaps and new opportunities* Develop scalable and effective machine-learning models and optimization strategies to solve business problems* Run regular A/B experiments, gather data, and perform statistical analysis* Work closely with software engineers to deliver end-to-end solutions into production* Improve the scalability, efficiency and automation of large-scale data analytics, model training, deployment and serving* Conduct research on new machine-learning modeling to optimize all aspects of Sponsored Products businessBASIC 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 solving business problems through machine learning, data mining and statistical algorithms- Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning ...