Seattle

We are seeking an entrepreneurial, innovative and self-driven Senior Applied Scientist to join our team, and help build a brand new Advertising product together. Your mission will be to leverage science and technology to help hundreds of thousands of independent sellers grow their business on WW Amazon marketplaces attracting new customers while also building customer loyalty. You will use ML modeling to build predictive modeling solutions to help brand owners connect with potential shoppers on Amazon websites and video channels (IMDB, FireTV, Twitch, Amazon.com etc). You can change the life of local business owners while taking ownership to solve technical challenge from delivering millions of global advertising campaigns and generating brand insights and recommendations for all our advertisers with superfast response time. The Sponsored Brands Advertiser Control team is a versatile environment, with a wide variety of challenges. We guide advertisers to make informed decisions by recommendations, sharing insights, and forecasts. We help advertisers deliver effective campaigns automatically by optimizing campaign settings on behalf of them. We enable advertisers to achieve brand advertising goals with maximum efficiency. We have the opportunity to deliver social impact, own technical problems, thought diversity, and business impact. 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.Why you will love this opportunity: Amazon 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.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 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_6Lzw8raE BASIC QUALIFICATIONS- 3+ years of building machine learning models for business application experience- PhD, or Master's degree and 6+ years of applied research experience- Experience programming in Java, C++, Python or related language- Experience with neural deep learning methods and machine learning ...

As a Senior Applied Scientist at Amazon, you will be at the forefront of a pioneering initiative to revolutionize customer experiences using Large Language Models (LLMs) and recommender systems. Your expertise will drive the personalization of every interaction across Amazon’s vast ecosystem, ensuring that each message and recommendation resonates personally with our customers.Your mission will be to harness the latest in LLM and machine learning innovations to craft recommender systems that are not just smart, but seem intuitively human. This is more than a technical role—it’s a chance to shape the future of e-commerce by making every user feel like Amazon’s most important customer.If you’re a visionary in the field of applied science, passionate about leveraging LLMs to create impactful, individualized user experiences, we want you. Help us set a new standard for personalization at Amazon, where every interaction is a step towards a more personalized future.Key job responsibilities- 3+ years of building machine learning models for business application experience- PhD, or Master's degree and 4+ years of applied research experience- Experience programming in Java, C++, Python or related language- Experience with neural deep learning methods and machine learningA day in the lifeYou are an Applied Scientist with an interest in machine learning, data science, search, or recommendation systems. You have great problem solving skills. You love keeping abreast of the latest technology and use it to help you innovate. You have strong leadership qualities, great judgment, clear communication skills, and a track record of delivering great products. You enjoy working hard, having fun, and making history!About the teamOur team has the autonomy to decide where we can have the most impact and get down to experimenting. We love metrics and the fast pace. We analyze data to uncover potential opportunities, generate hypotheses, and test them. We refuse to accept constraints, internal or external, and have a strong bias for action. We imagine, build prototypes, validate ideas, and launch follow-up experiments from the successful ones. BASIC QUALIFICATIONS- 3+ years of building machine learning models for business application experience- PhD, or Master's degree and 6+ years of applied research experience- Experience programming in Java, C++, Python or related language- Experience with neural deep learning methods and machine learning ...

The Amazon Q Developer Science team is looking for an Applied Scientist who is passionate about building services and tools for developers that leverage artificial intelligence (AI) agents and machine learning (ML). You will be part of a team building AI-based services for Amazon Q Developer with the focus on redefining the way developer work. The team works in close collaboration with other AWS AI services such as AWS Bedrock, the AWS IDE Toolkit, and Amazon Sagemaker. If you are excited about working in cloud computing and building new AWS services, then we'd love to talk to you.Key job responsibilitiesAs a senior Applied Scientist, you are recognized for your expertise, advise team members on a range of machine learning topics, and work closely with software engineers to drive the delivery of end-to-end modeling solutions. Your work focuses on ambiguous problem areas where the business problem or opportunity may not yet be defined. The problems that you take on require scientific breakthroughs.You take a long-term view of the business objectives, product roadmaps, technologies, and how they should evolve. You drive mindful discussions with customers, engineers, and scientist peers. You bring perspective and provide context for current technology choices, and make recommendations on the right modeling and component design approach to achieve the desired customer experience and business outcome.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- 3+ years of building machine learning models for business application experience- PhD, or Master's degree and 6+ years of applied research experience- Experience programming in Java, C++, Python or related language- Experience with neural deep learning methods and machine learning ...

The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Senior Applied Scientist with a strong deep learning background, to lead the development of industry-leading technology with multimodal systems. Key job responsibilitiesAs a Senior Applied Scientist with the AGI team, you will lead the development of novel algorithms and modeling techniques to advance the state of the art with multimodal systems. Your work will directly impact our customers in the form of products and services that make use of vision and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate development with multimodal Large Language Models (LLMs) and Generative Artificial Intelligence (GenAI) in Computer Vision.About the teamThe AGI team has a mission to push the envelope with multimodal LLMs and GenAI in Computer Vision, in order to provide the best-possible experience for our customers.BASIC QUALIFICATIONS- PhD, or Master's degree and 5+ years of applied research experience- 3+ years of building machine learning models for business application experience- Experience programming in Java, C++, Python or related language ...

The Campaign Measurement & Optimization (CMO) organization is looking for a Senior Applied Scientist interested in solving one of the most challenging business problems in marketing measurement and optimization, a thought leader with deep expertise in ML modeling, and scaling measurement science. Working with our team of data / research / applied scientists, economists, engineers, and product managers, this leader will help redefine marketing investment decision making at Amazon and its subsidiaries.The Campaign Measurement & Optimization (CMO) organization’s mission is to be the most trusted source of measurement science solutions to drive marketing investment decisions across Amazon. The CMO team provides incrementality and efficiency measurement services to the marketing stakeholders across Amazon’s lines of business, including Stores, Prime Video, Amazon Devices, Alexa, Amazon Business, Amazon Music, Amazon Fresh, as well as subsidiaries including Audible, Ring, Whole Foods, and more. CMO applies industry leading deep learning based causal inference models to measure omni-channel effectiveness of marketing campaigns from these businesses worldwide. The impact and influence of the organization is tremendous, helping optimize spend decisions on a scale that exceeds many countries’ GDP. Our outputs shape Amazon product and marketing teams’ decisions and therefore how Amazon customers see, use, and value their experience with Amazon.This is a high-impact role with opportunities to develop systems and analyze marketing effectiveness that contributes billions of dollars to the business. As a Senior Scientist in the team, you will be responsible for designing and developing cutting edge measurement and optimization models, while collaborating with businesses, marketers, and software teams to solve key challenges facing the teams. Such challenges include measuring the incremental impact of multi-billion $$ multi-channel marketing portfolios, developing Deep Learning models for estimating the impact on sparse customer actions, and scaling measurement solutions for WW marketplaces. Unlike many companies who buy existing off-the-shelf marketing measurement systems, we are responsible for studying, designing, and building systems to serve Amazon’s suite of businesses. Our team members have an opportunity to be on the forefront of marketing measurement thought leadership by working on some of the most difficult problems in the industry with some of the best product managers, research scientists, economists and software developers in the business.In this role, you will be a technical leader in Marketing science research with significant scope, impact, and high visibility. You will champion cutting edge ML models using the latest methods in causal estimation and portfolio optimization. You will lead strategic measurement science initiatives in CMO and across various marketing teams, scaling experimentation and measurement science models, real-time inference, and cross-channel orchestration. As a successful scientist, you are an analytical problem solver who enjoys diving into data, leads development of new models, is excited about investigations and algorithms, and can credibly interface between technical teams and business stakeholders. You are an expert in employing deep learning models to solve business problems, preferably in causal inference. You are a hands-on innovator who can contribute to advancing Marketing measurement technology in a B2C and B2B environment, and push the limits on what’s scientifically possible with a razor sharp focus on measurable customer and business impact. You will coach and guide junior scientists to grow the team’s talent and scale the impact of your work.BASIC QUALIFICATIONS- 3+ years of building machine learning models for business application experience- PhD, or Master's degree and 6+ years of applied research experience- Experience programming in Java, C++, Python or related language- Experience with neural deep learning methods and machine learning ...

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 Senior Applied Scientist to build the future of long term value measurement and optimization for Amazon Devices.About you:We are looking for a talented Senior Applied Scientist to partner with a highly-talented team. You will 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- 3+ years of building machine learning models for business application experience- PhD, or Master's degree and 6+ years of applied research experience- Experience programming in Java, C++, Python or related language- Experience with neural deep learning methods and machine learning ...

Have you ever wondered how Amazon selects the offer(s) for a given product from potentially hundreds of sellers selling the same item? It is one of the most critical models in Amazon and one of the most visible ones on the web. Whenever you see price, anywhere on Amazon, in any locale, it is calling this model at the backend. This is an opportunity to work with the team, Featured Merchant Algorithm, that develops and maintains this model. It drives one of the most coveted real estate in the e-commerce industry, the “Offer Display” across all surfaces (mobile app, mobile web, desktop, Alexa shopping) worldwide. The team's vision is to simplify Amazon shopping experience by helping customers discover and evaluate offers to find the right option for their shopping journey. We use Machine Learning models to select, rank and feature the most relevant offers to customers. Our model serves hundreds of millions of Amazon customers, handles millions of requests per second for hundreds of millions of products and billions of offers across the world.We are looking for an Applied Scientist to join this high impact, high visibility team. You will lead the development and expansion of the next generation of the featured offer selection models. These new models will incorporate the continually changing preferences of our customers and continue to scale with numerous new programs that Amazon is introducing for our customers. You will work with multiple Amazon businesses and programs to identify big business opportunities and propose new business features and technical systems to improve customer experience. As a team, we own the end-to-end life cycle of models – estimation, simulation and experimentation. We work in the interface of Artificial Intelligence, Statistics and Econometrics. Your work will cut across various sub-disciplines like Causal Inference, Bayesian Modeling, Deep Learning, Counterfactual Estimation and Evaluation, Multi-armed Bandits, and High-dimensional Multivariate Experiments. You will be responsible for the quality of the model and will get the opportunity to present your ideas and share results of your deliverables with Amazon executives and Amazon scholars on a regular basis. As a senior scientist, you will be collaborating with junior scientists to define and enforce broad, company-wide technical standards in statistical modeling, optimization and simulation techniques.Why is this a great opportunity?- We impact the global Amazon retail business: We are at the center of Amazon's retail universe. As a part of the broader Buying Experience org, we work closely with other Retail teams like Search, Pricing, Cart, Checkout, Delivery Experience, Ultra Fast Grocery, Subscribe-n-Save, etc. We build systems that are used every time a customer sees any item on the Amazon website (globally) and help them in making purchase decisions. As a result, we constantly strive to earn and preserve the customer trust. Our impact is typically measured in hundreds of millions of dollars.- We are diverse: Our team is diverse in terms of expertise (SDE/Scientists/Economists/Data Engineer/Product Manager), nationality (10 countries), experience (college graduate to industry veteran), tech-stacks (AWS, Datapath), and office locations (Seattle, Bangalore, Berlin, Vancouver).- We prioritize learning: Work alongside some of Amazon’s smartest engineers, scientists, economists, and product managers. We have one Principal Economist and two Principal SDE in the team to learn from. We regularly take ML courses and present/teach at internal and external forums. We innovate, publish, and file patents. We regularly review our models with academics like Michael Jordan, Guido Imbens, and Alberto Abadie.- We ensure work-life balance: Our team works together to provide work-life harmony for all team members. We recognize that the circumstances of our team members vary, and we balance work across the team so that we are all able to maintain high standards on behalf of our customers, while at the same time allowing for rich and happy personal lives.- We have fun: We find ways to relax and unwind with team events and group lunches.If you are ready to truly make an impact on a product that is used by hundreds of millions of people around the world, including your own friends and family, then we would love to talk to you.Key job responsibilities- Influence: Drive the scientific vision of the team. Present ideas to the senior leadership, build consensus, lead cross-org collaborations, and mentor junior engineers and scientists.- Execution: Deliver tactical solutions with strategic thinking to create reusable scientific components, resolving immediate challenges while building for future scalability.- Knowledge: Keep abreast of the trends in academia and industry – know the state-of-the-art. Publish papers and file patents to contribute to the broader scientific community inside and outside the company.- Scientific complexity: Innovate and extend scientific methods to address customers’ needs or business problems.- Engineering complexity: Partner with engineering to transform complex technical requirements into production solutions while optimizing performance tradeoffs.- Technical judgement: Be a pragmatic problem solver, applying judgment and experience to balance the technical trade-offs and how the applied scientific solution is positioned with respect to the state-of-the-art.BASIC QUALIFICATIONS- PhD, or Master's degree and 6+ years of applied research experience- 3+ years of building machine learning models for business application experience- Experience with neural deep learning methods and machine learning- Experience programming in Java, C++, Python or related language ...

Are you interested in the world's largest Cloud Network? Are you interested in applying new methods to extremely hard problems such as anomaly detection to have a lasting impact on business? Do you want to play a key role in the future of AWS's infrastructure? Come and join us! The Fleet Orchestration and Release Automation team is looking for an Applied Scientist Scientists to join our team. Our team owns multiple services that drive the decision-making behind the world's largest Network, and we are looking for excellent Scientists that can help us answer tough and ambiguous questions. Working collaboratively, you will improve and develop solutions to complex problems, such as identifying anomalies in the Network performance across Data-Centers worldwide, or automating the monitoring process of production network after OS or configuration deployments. You will work with a team of Engineers among others to test your solutions and push them into production so the business can meet its goals. You will be the POC for Science based innovation in the org.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.A day in the lifeYou must ensure our solutions meet the needs of our most important customers. You will work with customers to gather requirements, understand the space and impact, generate and test end-to-end proposals to carry the project through all the development stages. You’ll develop algorithms that enable Network Engineers to develop, monitor and operate robust, high-quality networks safely, securely, and reliably deploy it. You will have an opportunity to work directly with complex and high volume data and models to analyze network performance intelligently. You will use your strong leadership and communication skills to educate other team members, provide training and support for our products/models/technologies. You will have access to senior leadership and engineering staff.About the teamWe have created a new team that will own several new highly-visible initiatives and goals that will impact the whole organization as well as benefit across orgs. This includes developing and integrating various science based software solutions and collaborating with multiple teams and customers in order to achieve the goal of building software systems to deploy OS and config changes to the AWS datacenter network reliably. Our goal is to automate the process of identifying regressions in the network allowing teams to take action on it immediately with the long-term goal of providing specific root cause for regressions observed in network performance.Why 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.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.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.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 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.Working at AWS in the Core Networking Team • Meet Matt, Director, Core Networking --- https://youtu.be/DqTStjRtjX4 BASIC QUALIFICATIONS- 3+ years of building machine learning models for business application experience- PhD, or Master's degree and 6+ years of applied research experience- Experience programming in Java, C++, Python or related language- Experience with neural deep learning methods and machine learning ...

Futures Design is the advanced concept design and incubation team within Amazon’s Device and Services Design Group (DDG). We are responsible for exploring and defining think (very) big opportunities globally and locally — so that we can better understand how new products and services might enrich the lives of our customers and so that product teams and leaders can align on where we're going and why we're going there. We focus on a 3–10+ year time frame, with the runway to invent and design category-defining products and transformational customer experiences. Working with Amazon business and technology partners, we use research, design, and prototyping to guide early product development, bring greater clarity to engineering goals, and develop a UX-grounded point of view.Our team is dedicated to unlocking new foundational capabilities in generative AI, guided by the thesis that embedding understanding through human factors, cognitive science, and socioeconomics is crucial to building AI systems that align with human needs. We place particular emphasis on the capabilities of simulacra through agentic systems and experiential/evolutionary learning, which we believe are vital to accelerating the development of AI as an aligned partner. Joining our team will give you the chance to drive key decisions that will impact the lives of millions of Amazon customers. Key job responsibilitiesYou will be responsible for defining key research directions, adopting or inventing new machine learning techniques, conducting rigorous experiments, publishing results, and ensuring that research is translated into practice. You will develop long-term strategies, persuade teams to adopt those strategies, propose goals and deliver on them. You will also participate in organizational planning, hiring, mentorship and leadership development. You will be technically fearless and with a passion for building scalable science and engineering solutions. You will serve as a key scientific resource in full-cycle development (conception, design, implementation, testing to documentation, delivery, and maintenance).A day in the lifeWe're looking for a Senior Applied Scientist to join the growing DDG Futures Design team.You thrive in ambiguity and paradigm shifts – remaking assumptions of how customers engage, devices operate, and builders create. You apply deep expertise that spans design, technology, and product, grounding state-of-the-art emerging technologies through storytelling and a maker's mindset. You learn and adapt technology trends to enduring customer problems through customer empathy, code, and iterative experimentation.You will wear multiple hats to quickly assimilate customer problems, convert them to hypotheses, and test them using efficient technologies and design methods to build stakeholder buy-in. You’ll help your peers unlock challenging scenarios and mature the design studio’s ability to deliver design at scale across a breadth of devices and interaction modalities. You will work around limitations and push capabilities through your work. Your curiosity will inspire those around you and facilitate team growth, while your hands-on, collaborative nature will build trust with your peers and studio partners.BASIC QUALIFICATIONS- 3+ years of building machine learning models for business application experience- PhD, or Master's degree and 6+ years of applied research experience- Experience programming in Java, C++, Python or related language- Experience with neural deep learning methods and machine learning ...

Amazon’s global talent management and compensation (GTMC) organization is looking for a Senior Applied Scientist to join our interdisciplinary science team. The role will lead our strategic science investments to develop and refine Generative AI solutions in our experiences that help more than 1.5 million employees build rewarding careers and shape how we manage Amazon's talent.GTMC is responsible for managing all aspects of Amazon employees' careers, from onboarding to exit. We build intelligent products that are used by employees, their managers and senior leadership to grow, develop and reward Amazon’s talent. The domains we cover include career development, talent evaluation, employee-role matching, promotions, organizational design and succession planning, and new areas that address the evolving needs of our diverse employee base.We are looking for an experienced applied scientist who has experience building, applying and customizing GenAI solutions to solve customer problems. As a senior applied scientist on the team, you will play a critical role in driving the development of GenAI technologies that handle Amazon-scale use cases and have a significant impact on our employees' lives. You will have the opportunity to lead exciting problems, publish and patent your work in one of the most high impact, innovative and unconventional applications of science in the People Experience and Technology space.If this kind of work excites you, reach out to us to find out more!Key job responsibilities- Provide scientific thought leadership in GenAI solution development for our science and engineering teams- Prototype and iterate on GenAI solutions for capabilities across writing feedback, summarization, information retrieval, content generation and orchestration.- Participate in scoping feature and business planning roadmap of GTMC’s science investments- Design and execute science-based product ideas and features, project plans and communicate with stakeholders- Partner with engineers to productionize GenAI and other science models at the scale of Amazon- Mentor and guide junior scientists and engineers, and contribute to the overall growth and development of the teamAbout the teamGTMC's science team is an experienced central interdisciplinary organization of scientists spanning machine learning, economics and research that builds science models for Amazon's worldwide employee-facing talent management products, designs and supports experiments for product features, and measures impact of product and program initiatives across the broader organization. Examples of our work include GenAI-powered summarization and writing assistants, content and people recommendation systems, scalable experimentation products and measuring organizational north star metrics.BASIC QUALIFICATIONS- 3+ years of building machine learning models for business application experience- PhD, or Master's degree and 6+ years of applied research experience- Experience with neural deep learning methods and machine learning- Experience programming in Java, C++, Python or related language- Experience with developing Generative AI solutions for business applications ...

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 III in the Selling Partner Services (SPS) Machine Learning Accelerator (MLA) team is to research and prototype Machine Learning applications that solve strategic business problems across SPS domains. Additionally, the scientist collaborates with engineers and business partners to design and implement solutions at scale when they are determined to be of broad benefit to SPS organizations. They develop large-scale solutions for high impact projects, introduce tools and other techniques that can be used to solve problems from various perspectives, and show depth and competence in more than one area. They influence the team’s technical strategy by making insightful contributions to the team’s priorities, approach and planning. They develop and introduce tools and practices that streamline the work of the team, and they mentor junior team members and participate in hiring.BASIC QUALIFICATIONS- 4+ years of applied research experience- 3+ years of building machine learning models for business application experience- PhD, or Master's degree and 6+ years of applied research experience- Experience programming in Java, C++, Python or related language- Experience with neural deep learning methods and machine learning ...

Are you interested in LLM, foundation model and big data? 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- 3+ years of building machine learning models for business application experience- PhD, or Master's degree and 6+ years of applied research experience- Experience programming in Java, C++, Python or related language- Experience with neural deep learning methods and machine learning ...

At AWS, we use Artificial Intelligence to be able to identify every need of a customer across all AWS services before they have to tell us about it, and then find and seamlessly connect them to the most appropriate resolution for their need, eventually fulfilling the vision of a self-healing cloud. We are looking for Machine Learning Scientists / Applied Scientists / ML Scientists with unfettered curiosity and drive to help build “best in the world” support (contact center) experience that customers will love!You will have an opportunity to lead, invent, and design tech that will directly impact every customer across all AWS services. We are building industry-leading technology that cuts across a wide range of ML techniques from Natural Language Processing to Deep Learning and Generative Artificial Intelligence. You will be a key driver in taking something from an idea to an experiment to a prototype and finally to a live production system.Our team packs a punch with principal level engineering, science, product, and leadership talent. We are a results focused team and you have the opportunity to lead and establish a culture for the big things to come. We combine the culture of a startup, the innovation and creativity of a R&D Lab, the work-life balance of a mature organization, and technical challenges at the scale of AWS. We offer a playground of opportunities for builders to build, have fun, and make history!Key job responsibilities- Deliver real world production systems at AWS scale.- Work closely with the business to understand the problem space, identify the opportunities and formulate the problems.- Use machine learning, data mining, statistical techniques, Generative AI and others to create actionable, meaningful, and scalable solutions for the business problems.- Analyze and extract relevant information from large amounts of data and derive useful insights.- Work with software engineering teams to deliver production systems with your ML models- Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementationAbout the teamWe are working to achieve our business goals by deriving insights from a wealth of datasets like the AWS service metrics and logs, chat and call audio logs, email transcripts, support agent and support case data, customers context and sentiment, and AWS knowledge articles, tools and workflows.BASIC QUALIFICATIONS- 4+ years of building machine learning models for business application experience- PhD, or Master's degree and 6+ years of applied research experience- Experience programming in Java, C++, Python or related language- Experience with neural deep learning methods and machine learning ...

Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads.Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience.As a Prime Video technologist, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people.We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you!We are looking for a self-motivated, passionate and resourceful Applied Scientist to bring diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. You will spend your time as a hands-on machine learning practitioner and a research leader. You will play a key role on the team, building and guiding machine learning models from the ground up. At the end of the day, you will have the reward of seeing your contributions benefit millions of Amazon.com customers worldwide.Key job responsibilities- Develop AI solutions for various Prime Video Search systems using Deep learning, GenAI, Reinforcement Learning, and optimization methods;- Understand problem space, identify gaps and opportunity for improvement, create roadmap and plans for delivering business goals;- Lead cross-team collaboration and work closely with engineers and product managers to deliver AI solutions end-to-end;- Design and conduct offline and online (A/B) experiments to evaluate proposed solutions based on in-depth data analyses;- Effectively communicate technical and non-technical ideas with teammates and stakeholders;- Stay up-to-date with advancements and the latest modeling techniques in the field;- Mentor and grow junior scientists and interns;- Publish your research findings in top conferences and journals.About the teamPrime Video Personalization and Discovery science team owns different aspects of personalization algorithms, from user-item relevance, item-item relevance, and page composition, to name a few. We work closely with the engineering teams to put our models in production.BASIC QUALIFICATIONS- PhD, or Master's degree and 6+ years of applied research experience- 3+ years of building machine learning models for business application experience- Experience programming in Java, C++, Python or related language- Experience with neural deep learning methods and machine learning ...

Lead the development of cutting-edge AI models to power Amazon's eCommerce ontology - the authoritative 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- 4+ years of applied research experience- 3+ years of building machine learning models for business application experience- PhD, or Master's degree and 6+ years of applied research experience- Experience programming in Java, C++, Python or related language- Experience with neural deep learning methods and machine learning ...

Amazon continues to invest in its Advertising business to tap into the growing online advertising market. The Publisher Technologies team builds and operates extensible services that empower 1P Publishers to optimize their customer experiences and improve monetization. We focus on creating flexible, standards-based solutions that allow Publishers to innovate while seamlessly interacting with other advertising technology providers—both internal and external.The Publisher Technology Data, Insights, and Analytics team accelerates data-driven decision-making by providing near real-time data, data management tools, actionable insights. Our machine learning models inform dynamic floor prices, and yield optimization in first and second price auction environments to optimize publisher revenue. Our data products equip Publishers and Monetization teams with the tools needed to understand advertising performance and support scalable machine learning initiatives.In this role, you will 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 auctions. We are looking for a passionate Applied Scientist with technical expertise in information retrieval, Natural Language Processing (NLP), Large Language Models (LLM), and recommender systems (RecSys) In addition to hands-on experience building ML-based solutions, an ideal candidate should be able to create and articulate a customer-centric science vision, show a willingness to continuously learn about new scientific approaches, and thrive in a startup-like environment.Key job responsibilities* Conduct deep data analysis to derive insights for the business, identify gaps, and uncover 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 to optimize Publisher and advertiser experiences.* Collaborate closely with software engineers to deliver end-to-end solutions into production.* Enhance the scalability, efficiency, and automation of large-scale data analytics, model training, deployment, and serving.* Research and implement new machine learning models and techniques to improve advertising performance.BASIC QUALIFICATIONS- 3+ years of building machine learning models for business application experience- PhD, or Master's degree and 6+ years of applied research experience- Experience programming in Java, C++, Python or related language- Experience with neural deep learning methods and machine learning- Proficiency in solving business problems through machine learning, data mining, and statistical algorithms.- Expertise in designing and optimizing deep learning models, model pruning, and related optimization techniques. ...

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. Amazon Advertising is at the forefront of shaping the future of advertising technology, and our Auction team in Sponsored Brands is pivotal in driving this innovation. SB Auction team's role is to develop optimized and fair auction systems for sponsored brands that deliver value for advertisers while enhancing the shopping experience for customers. 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.Key job responsibilitiesAs a Senior Applied Scientist on this team, you typically play a key role in optimizing ad delivery, improving targeting accuracy, and maximizing revenue generation for advertisers, all while maintaining a seamless user experience, you will:- Develop optimization techniques (e.g., multi-objective optimization) to balance multiple goals, such as maximizing revenue for advertisers, increasing user engagement, and maintaining fair ad distribution.- 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, fine-tune the models for real-world effectiveness, ensuring that the ad auction system works optimally in production environments.- Run large-scale experiments to test different auction strategies, bidding algorithms, and ad targeting techniques, using methodologies like multi-arm bandit or reinforcement learning.- Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving- Communicate results and insights clearly to non-technical stakeholders, including product managers, advertisers, and executives, helping them understand the impact of data-driven decisions.- Research new and innovative machine learning approaches.- Recruit Applied Scientists to the team and provide mentorship.BASIC QUALIFICATIONS- 6+ years of building machine learning models for business application experience- PhD, or Master's degree and 6+ years of applied research experience- Experience programming in Java, C++, Python or related language- Experience in building machine learning models for business application- Understanding of digital advertising ecosystems.- Familiarity with statistical hypothesis testing, AB testing, and causal inference to ensure robust evaluation of models and experiments.- Ability to translate business goals (e.g., maximizing ad revenue, improving user experience) into measurable model outputs and performance metrics. ...

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 machine learning models for business application experience- PhD, or Master's degree and 6+ years of applied research experience- Experience programming in Java, C++, Python or related language- Experience with neural deep learning methods and machine learning ...

Amazon is investing heavily in building a world class advertising business and developing a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses for driving long-term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities. Sponsored Products DP Experience and Marketplace Intelligence is looking for a strong Senior Applied Scientist who has a track-record of performing deep analysis and is passionate about applying advanced ML and statistical techniques to solve real-world, ambiguous and complex challenges to optimize and improve the product performance, and who is motivated to achieve results in a fast-paced environment. The position offers an exceptional opportunity to grow your technical and non-technical skills and make a real difference to the Amazon Advertising business.As a Senior Applied Scientist on this team, you will:* Be the technical leader in Machine Learning; lead efforts within this team and collaborate across teams* Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, perform hands-on analysis and modeling of enormous data sets to develop insights that improve shopper experiences and merchandise sales* Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, 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.* 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.* Promote the culture of experimentation and applied science at AmazonAbout the teamSponsored Products (SP) is Amazon's largest and fastest growing business. Over the last few years we grown to a multi-billion dollar business. SP ads are shown prominently throughout search and detail pages, allowing shoppers to seamlessly discover products sold on Amazon. Ad experience and market place is one of the highest impact decisions we make. This role has unparalleled opportunity to grow our marketplace and deliver value for advertisers and shoppers. You will invent new experiences and influence customer-facing shopping experiences; this is your opportunity to work within the fastest-growing businesses across all of Amazon!BASIC QUALIFICATIONS- 3+ years of building machine learning models for business application experience- PhD, or Master's degree and 6+ years of applied research experience- Experience programming in Java, C++, Python or related language- Experience with neural deep learning methods and machine learning ...

Have you ever wondered how Amazon launches and maintains a consistent customer experience across hundreds of countries and languages it serves its customers? Are you passionate about data and mathematics, and hope to impact the experience of millions of customers? Are you obsessed with designing simple algorithmic solutions to very challenging problems? If so, we look forward to hearing from you!At Amazon, we strive to be Earth's most customer-centric company, where both internal and external customers can find and discover anything they want in their own language of preference. Our Translations Services (TS) team plays a pivotal role in expanding the reach of our marketplace worldwide and enables thousands of developers and other stakeholders (Product Managers, Program Managers, Linguists) in developing locale specific solutions.Amazon Translations Services (TS) is seeking a Senior Applied Scientist to be based in our Seattle office. As a key member of the Science and Engineering team of TS, this person will be responsible for designing algorithmic solutions based on data and mathematics for translating billions of words annually across 130+ and expanding set of locales. The successful applicant will ensure that there is minimal human touch involved in any language translation and accurate translated text is available to our worldwide customers in a streamlined and optimized manner. With access to vast amounts of data, cutting-edge technology, and a diverse community of talented individuals, you will have the opportunity to make a meaningful impact on the way customers and stakeholders engage with Amazon and our platform worldwide. Together, we will drive innovation, solve complex problems, and shape the future of e-commerce.Key job responsibilities* Lead and innovate in applying advanced NLP and LLM techniques to solve complex language translation challenges in e-commerce, driving product-level improvements for our international marketplaces.* Architect and implement novel, scalable machine learning solutions that enhance translation quality evaluation and improve translation pipeline efficiency across multiple teams and systems.* Spearhead cross-functional collaborations to define strategic project requirements, establish organization-wide success metrics, and deliver high-impact solutions aligning with broader business objectives.* Drive comprehensive data analysis to uncover non-obvious insights in multilingual data, relaying findings into actionable strategies that influence product roadmaps and capabilities for language technologies.* Pioneer and implement cutting-edge modeling techniques for machine translation quality assessment and pipeline optimization, leading the team's scientific agenda. Invent new methodologies when existing approaches fall short, advancing the state-of-the-art.* Serve as a recognized expert in LLM applications for e-commerce translation, communicating complex concepts to diverse stakeholders including senior leadership. Influence organization-wide adoption of innovative approaches in language translation technologies.* Actively mentor team members, elevating scientific capabilities and fostering a culture of innovation and rigorous inquiry in machine translation and evaluation.About the teamWe are a start-up mindset team. As the long-term technical strategy is still taking shape, there is a lot of opportunity for this fresh Science team to innovate by leveraging Gen AI technoligies to build scalable solutions from scratch.Our Vision: Language will not stand in the way of anyone on earth using Amazon products and services.Our Mission: We are the enablers and guardians of translation for Amazon's customers. We do this by offering hands-off-the-wheel service to all Amazon teams, optimizing translation quality and speed at the lowest cost possible.BASIC QUALIFICATIONS- 3+ years of building machine learning models for business application experience- PhD, or Master's degree and 6+ years of applied research experience- Experience programming in Java, C++, Python or related language- Experience with neural deep learning methods and machine learning ...