Careers

The Ambient Perception Technology team under Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Applied Scientist with a strong deep learning background, to help build industry-leading technology with computer vision and multimodal perception models for cloud and edge applications. Key job responsibilities As an Applied Scientist with the Ambient Perception Technology team under AGI, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art with multimodal models with an emphasis on computer vision. Your work will directly impact our customers in the form of products and services that make use of CV technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in AGI in within perception domain. A day in the life An Applied Scientist with the AGI team will support the science solution design, run experiments, research new algorithms, and find new ways of optimizing the customer experience; while setting examples for the team on good science practice and standards. Besides theoretical analysis and innovation, an Applied Scientist will also work closely with talented engineers and scientists to put algorithms and models into practice. About the team The Ambient Perception Technology team has a mission to deliver best in class CV, Audio and multimodal models in support of various edge and cloud applications. We are open to hiring candidates to work out of one of the following locations: Sunnyvale, CA, USA

The Amazon Artificial General Intelligence (AGI) team is looking for a passionate, highly skilled and inventive Senior Applied Scientist with strong machine learning background to lead the development and implementation of state-of-the-art ML systems for building large-scale, high-quality conversational assistant systems. As a Senior Applied Scientist, you will play a critical role in driving the development of personalization techniques enabling conversational systems, in particular those based on large language models, to be tailored to customer needs. You will handle Amazon-scale use cases with significant impact on our customers' experiences. 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 representation, using language models in combination with other learning techniques, that allows effective grounding in context providers when considering memory, cpu, latency and quality - Collaborate with cross-functional teams of engineers, product managers, and scientists to identify and solve complex problems in personal knowledge aggregation, processing and verification - Design and execute experiments to evaluate the performance of different algorithms and models, and iterate quickly to improve results - Think Big about the arc of development of conversational assistant system personalization over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems - Communicate results and insights to both technical and non-technical audiences, including through presentations and written reports - Mentor and guide junior scientists and engineers, and contribute to the overall growth and development of the team We are open to hiring candidates to work out of one of the following locations: Cambridge, GBR | London, GBR

Amazon.com strives to be Earth's most customer-centric company where people can find and discover virtually anything they want to buy online by giving customers more of what they want - low prices, vast selection, and convenience - Amazon.com continues to grow and evolve as a world-class e-commerce platform. Within Amazon, the Selling Partner Services’s (SPS) goal is to enable third-party Sellers of any size by helping them build the business they want. We are the Core Selling Partner Experience (CSPE) team which defines, implements, and enforces quality standards for all Amazon-built experiences for all SPs worldwide. Key job responsibilities - Lead and manage a team of cross-functional roles of research scientists, researchers, product managers, and program managers - Develop and implement strategies to improve the efficiency and effectiveness of programs delivering survey datasets and correlated behavioral signals - Persuade decision makers at all levels of the organization to take aligned action on research findings – inspire and help them internalize opportunities to delight our customers and differentiate our service. - Mentor and guide team members to achieve their career goals and objectives We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA | Arlington, VA | Sunnyvale, CA We are open to hiring candidates to work out of one of the following locations: Arlington, VA, USA | Seattle, WA, USA | Sunnyvale, CA, USA

Amazon Advertising is one of Amazon's fastest growing and most profitable 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 aims to democratize access to high-quality creatives (image, video, text) by building AI-driven solutions for advertisers. To accomplish this, we are investing in latent-diffusion models, large language models (LLM), computer vision (CV), and related ML methods. You will be part of a close-knit team of applied scientists and machine learning engineers, who are highly collaborative and at the top of their respective fields. We are looking for talented an Applied Scientist who is adept at a variety of skills, especially with latent diffusion models, large language models, 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 and innovative spirit within the team, and bring cutting-edge applied research to raise the bar within the team. As a Generative AI Applied Scientist on this team, you will: - Drive end-to-end Machine Learning 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. - 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 and implement innovative machine learning approaches. - Mentor and help recruit applied scientists and machine learning engineers to the team. - Present findings and insights to senior leadership and at internal and external top scientific venues. - Be the thought leader in cutting-edge AI research and proactively pursue IP submissions. Key job responsibilities This role is focused on generating image/text and building the related foundational models for generative AI. 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 and technical program managers, who will partner with you to productize your work. A day in the life On a day-to-day basis, you will be doing your independent research and work to develop and deploy 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 team The 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. We are open to hiring candidates to work out of one of the following locations: New York, NY, USA | Seattle, WA, USA

Key job responsibilities As a Senior Applied Scientist on this team you will: Act as the technical leader in Machine Learning and drive full life-cycle Machine Learning projects. Develop real-time algorithms to allocate billions of ads per day in advertising auctions. Lead technical efforts within this team and across other teams. Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production. 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. Work closely with software engineers to assist in productionizing your ML models. Research new machine learning approaches. Recruit Applied Scientists to the team and act as a mentor to other Scientists on the team. Key job responsibilities Calling all inventors to work on exciting new opportunities in Sponsored Products. Amazon is building a world class advertising business and defining and delivering a collection of self-service performance advertising products that drive discovery and sales of merchandise. Our products are strategically important to our Retail and Marketplace businesses, driving long-term growth. Sponsored Products (SP) helps merchants, retail vendors, and brand owners grows incremental sales of their products sold on Amazon through native advertising. SP achieves this by using a combination of machine learning, big data analytics, ultra-low latency high-volume engineering systems, and quantitative product focus. We are a highly motivated, collaborative and fun-loving group with an entrepreneurial spirit and bias for action. You will join a newly-founded team with a broad mandate to experiment and innovate, which gives us the flexibility to explore and apply scientific techniques to novel product problems. You will have the satisfaction of seeing your work improve the experience of millions of Amazon shoppers while driving quantifiable revenue impact. More importantly, you will have the opportunity to broaden your technical skills, and be a science leader in an environment that thrives on creativity, experimentation, and product innovation. Key job responsibilities As a Senior Applied Scientist on this team you will: Act as the technical leader in Machine Learning and drive full life-cycle Machine Learning projects. Develop real-time algorithms to allocate billions of ads per day in advertising auctions. Lead technical efforts within this team and across other teams. Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production. 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. Work closely with software engineers to assist in productionizing your ML models. Research new machine learning approaches. Recruit Applied Scientists to the team and act as a mentor to other Scientists on the team. We are open to hiring candidates to work out of one of the following locations: New York, NY, USA

Amazon is looking for a motivated and innovative Applied Scientist with strong analytical skills and practical experience to join our Middle Mile Marketplace Science team, part of our Middle Mile Planning Research and Science (mmPROS) organization. We are hiring specialists with expertise in machine learning, operations research, systems engineering, optimization and modeling applied to logistics planning and optimization, marketplace engineering, pricing and revenue management. Middle Mile Air and Ground represents one of the fastest growing logistics areas within Amazon. Amazon Transportation Services transports millions of packages via air and ground and continues to grow year over year. Our organization, mmPROS, is charged with developing science strategy, models, algorithms, analysis for Amazon Transportation Services. The Middle Mile Marketplace Science team is responsible for the science behind Amazon’s dynamic two-sided marketplace within the transportation space and the underlying algorithms needed to efficiently match available capacity provided by tens of thousands of independent carriers with both internal and external demand, and to manage real-time spot pricing and contract pricing in this setting. These algorithms rely heavily on the latest advances in optimization, machine learning, stochastic modeling, and marketplace engineering. In addition, Amazon often finds existing techniques do not effectively match our unique business needs which necessitates the innovation and development of new approaches and algorithms to find an adequate solution. As an Applied Scientist responsible for middle mile, you will be working in a highly collaborative environment partnering with various science, product management, engineering, operations, finance, business intelligence and analytics teams to develop to design and build scalable products operating across multiple modes. You will create experiments and prototype implementations of new algorithms and prediction techniques. You will have exposure to top level leadership to present findings of your research. You will also work closely with other scientists and also engineers to implement your models within our production system. You will implement solutions that are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility, and make decisions that affect the way we build and integrate algorithms across our product portfolio. An ideal candidate will be an expert in the areas of operations research, machine learning, or and statistics, with expertise in applying theoretical models in an applied environment. Challenges will involve dealing with very large data sets, and developing practical, scaleable models. We are open to hiring candidates to work out of one of the following locations: Bellevue, WA, USA

Are you interested in computational advertising and sponsored products recommendations? Do you thrive in a fast-paced organization with a significant impact on hundreds of millions of customers? Do you love to innovate at the intersection of customer experience, deep learning, and high-scale machine-learning systems? If so, Amazon Sponsored Products organization could be the right place for you. Amazon is building a world class advertising business. We are defining and delivering a collection of self-service performance advertising products that drive discovery and sales of merchandise. Our products are strategically important to Amazon Stores businesses and driving long-term growth. We helps merchants, retail vendors, and brand owners grows incremental sales of their products sold on Amazon through native advertising. We achieve this by using a combination of machine learning, big data analytics, ultra-low latency high-volume engineering systems, and quantitative product focus. We are a highly motivated, collaborative and fun-loving group with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we grow at an unprecedented rate with a seemingly endless range of new opportunities. As a Senior Data Scientist on the team, you will lead building data science solutions end-to-end and mentor other data scientist team members. You can deliver independently on ambiguous and large-scale problems. You will leverage your statistical and machine learning knowledge to address specific business problems. You will retrieve, understand, analyze, and present critical data and insights and communicate (verbal and written) to your partner engineers, scientists, product managers, and leadership to identify business opportunities, support decision making, and drive product innovations. We are open to hiring candidates to work out of one of the following locations: New York, NY, USA

Conversational AI ModEling and Learning (CAMEL) team is part of Amazon Artificial General Intelligence (AGI) organization where our mission is to create a best-in-class Conversational AI that is intuitive, intelligent, and responsive, by developing superior Large Language Models (LLM) solutions and services which increase the capabilities built into the model and which enable utilizing thousands of APIs and external knowledge sources to provide the best experience for each request across millions of customers and endpoints. We are looking for a passionate, talented, and resourceful Applied Scientist in the field of LLM, Artificial Intelligence (AI), Natural Language Processing (NLP) and/or Information Retrieval, to invent and build scalable solutions for a state-of-the-art context-aware conversational AI. A successful candidate will have strong machine learning background and a desire to push the envelope in one or more of the above areas. The ideal candidate would also have hands-on experiences in developing LLM solution, enjoy operating in dynamic environments, be self-motivated to take on challenging problems to deliver big customer impact, moving fast to ship solutions and then iterating on user feedback and interactions. Key job responsibilities As an Applied Scientist, you will leverage your technical expertise and experience to collaborate with other talented applied scientists and engineers to research and develop novel algorithms and modeling techniques to reduce friction and enable natural and contextual conversations. You will analyze, understand and improve user experiences by leveraging Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in artificial intelligence. You will work on core LLM technologies, including developing best-in-class modeling, prompt optimization algorithms to enable Conversation AI use cases. Your work will directly impact our customers in the form of novel products and services . We are open to hiring candidates to work out of one of the following locations: Bellevue, WA, USA | Boston, MA, USA | Seattle, WA, USA | Sunnyvale, CA, USA

Conversational AI ModEling and Learning (CAMEL) team is part of Amazon Artificial General Intelligence (AGI) organization where our mission is to create a best-in-class Conversational AI that is intuitive, intelligent, and responsive, by developing superior Large Language Models (LLM) solutions and services which increase the capabilities built into the model and which enable utilizing thousands of APIs and external knowledge sources to provide the best experience for each request across millions of customers and endpoints. We are looking for a passionate, talented, and resourceful Applied Scientist in the field of LLM, Artificial Intelligence (AI), Natural Language Processing (NLP) and/or Information Retrieval, to invent and build scalable solutions for a state-of-the-art context-aware conversational AI. A successful candidate will have strong machine learning background and a desire to push the envelope in one or more of the above areas. The ideal candidate would also have hands-on experiences in developing LLM solution, enjoy operating in dynamic environments, be self-motivated to take on challenging problems to deliver big customer impact, moving fast to ship solutions and then iterating on user feedback and interactions. Key job responsibilities As an Applied Scientist, you will leverage your technical expertise and experience to collaborate with other talented applied scientists and engineers to research and develop novel algorithms and modeling techniques to reduce friction and enable natural and contextual conversations. You will analyze, understand and improve user experiences by leveraging Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in artificial intelligence. You will work on core LLM technologies, including developing best-in-class modeling, prompt optimization algorithms to enable Conversation AI use cases. Your work will directly impact our customers in the form of novel products and services . We are open to hiring candidates to work out of one of the following locations: Bellevue, WA, USA | Boston, MA, USA | Seattle, WA, USA | Sunnyvale, CA, USA

Brand Stores (such as www.amazon.com/lego) are a core product offering in the Amazon Advertising portfolio. The brand’s store is their dedicated place on Amazon to differentiate, grow sales, and build loyalty with millions of shoppers. Our mission is to empower brands of all sizes to tell their story in their own unique voice to consumers. We help brands create engaging shopping experiences that assist shoppers in discovering and evaluating them as part of purchase decisions. We succeed when we are both useful to shoppers and when brands can attract and retain shopper’s attention using our products. A cool case study on brand stores can be found here: https://advertising.amazon.com/library/case-studies/nespresso-brand-store-increases-shopper-engagement. We are looking for a Senior Applied Scientist to lead the generation of data driven insights that bring long term value to brands, as well as the ideation and creation of ranking models for brand content. In this role you will influence our team’s science and business strategy with your analyses. You will be expected to identify and solve ambiguous problems and science deficiencies, and to provide informed solutions based on state of the art machine learning research. Why you will love this opportunity: Amazon is investing heavily in building a world-class advertising business. This team collaborate closely with other 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 #adpt-brand-shopping-experiences-science Key job responsibilities As a Senior Applied Scientist on this team, you will: - Be the technical leader in Machine Learning; lead efforts within this team and across other teams. - 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. - 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. - 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. About the team The Brand Shopping Experience Team (BSX) develops and deploys into production Machine Learning Algorithms that quantify relevance, select and organize Brands’ pieces of content in different placements in Amazon.com. BSX's goal is to create engaging and enjoyable shopping experiences that incentivize Brand discovery and that foster Brand-Customer relationships. We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA