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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 exclusive access to coverage of live sports. All customers regardless of whether they have a Prime membership or not, can access programming from subscriptions such as Apple TV, Peacock Premium Plus, HBO Max, FOX One, Crunchyroll and MGM+, as well as more than 900 free ad-support (FAST) Channels, rent or buy titles, and 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! Interested in influencing what customers around the world see when they turn on Prime Video? The Prime Video Personalization and Discovery team matches customers with the right content at the right time, at all touch points throughout the content discovery journey. We are looking for a customer-focused, solutions-oriented Senior Data Scientist to build and guide new data-driven frameworks to understand what makes new personalization and content discovery innovations successful for users and the business. You'll be part of an embedded science team on projects that are fast-paced, challenging, and ultimately influence what millions of customers around the world see when the log into Prime Video. The ideal candidate brings strong problem-solving skills, stakeholder communication skills, and the ability to balance technical rigor with delivery speed and customer impact. You will build cross-functional support within Prime Video, assess business problems, define metrics, and support iterative scientific solutions that balance short-term delivery with long-term science roadmaps. Key job responsibilities - Use advanced statistical and machine learning techniques to extract insights from complex, large-scale data sets - Design and implement end-to-end data science workflows, from data acquisition and cleaning to model development, testing, and deployment - Support scalable, self-service data analyses by building datasets for analytics, reporting and ML use cases - Partner with product stakeholders and science peers to identify strategic data-driven opportunities to improve the customer experience - Communicate findings, conclusions, and recommendations to technical and non-technical stakeholders - Stay up-to-date on the latest data science tools, techniques, and best practices and help evangelize them across the organization

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 team member, 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. We are looking for an Applied Scientist to push the envelope of AI content generation. As a scientist at Prime Video, you will contribute directly to productions using innovative tools in computer vision, deep learning, and generative AI to transform entertainment experiences. The ideal candidate has deep knowledge in one of: graphics, deep learning, generative AI and/or reinforcement learning and experience applying them real-world problems. You understand tradeoffs between business needs and model complexity, and you take calculated risks in developing rapid prototypes and iterative model improvements. You are excited to learn from and alongside seasoned scientists, engineers, and business leaders. You are an excellent communicator and effectively translate technical findings into production systems and business action (and customer delight). Key job responsibilities • Build generative AI models that create production-ready content, including movie content, localized assets, and visual marketing materials used across Prime Video's global platform. • 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. • Run 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. • Share knowledge and research outcomes via internal and external conferences and journal publications A day in the life In this role, you will invent science and systems for content localization, generation, including graphics and machine learning-based modeling systems. You will work with a team of scientists and product managers to design customer-facing products, and you will work with technology teams to productize and maintain the associated solutions.

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 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 Generative AI and 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 contribute to 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. You will be part of a team of fellow scientists and engineers taking on 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 shopping experiences; this is your opportunity to work within the fastest growing businesses across all of Amazon! Define a long-term 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 leadership, 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 serving About the team Sales 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.

In this role, you will build scalable solutions and sophisticated models that identify and drive growth opportunities for Amazon Ads teams, specifically within Amazon's Demand Side Platform (ADSP). You will leverage machine learning, simulation, and advanced statistical techniques to explain complex patterns, quantify business impact, predict future trends, and prescribe actionable strategies that inform critical business decisions at the highest levels of the organization. You will work with various stakeholders to align on priorities, with the understanding that scope and direction may evolve based on organizational needs. You will translate business goals into agile, insightful analytics that create tangible value for both stakeholders and customers, and communicate your findings clearly and actionably to managers and senior leaders so they can quickly understand insights and take decisive action. You will set the strategy for ads delivery and quality and establish the measurement and decision frameworks. A core mandate for this role is to identify, instrument, and operationalize the input metrics that most directly drive ads delivery, quality, and performance, ensuring we optimize the levers that move outcomes rather than simply reporting on lagging KPIs. Key job responsibilities * You will define and execute in-depth data analysis that drives data-informed decision making for product, sales, and finance teams who speak on behalf of advertisers. * You will establish and drive data hygiene best practices to ensure coherence and integrity of data feeding into production ML/AI solutions. * You will identify, instrument, and operationalize the input metrics that most directly drive ads delivery, quality, and performance, creating robust measurement frameworks. * You will collaborate with colleagues across science and engineering disciplines for fast turnaround proof-of-concept prototyping at scale. * You will partner with product managers and stakeholders to define forward-looking product visions and prospective business use cases. * You will set the strategy for ads delivery and quality, establishing decision frameworks that enable teams to move from reactive reporting to proactive optimization. * You will drive and lead a culture of data-driven innovations within the Amazon AdTech org.

Do you want to be part of a team that's revolutionizing Amazon's fulfillment and packaging technology? Are you ready to optimize systems that process tens-of-millions of customer packages daily with the lowest cost to serve and a defect-free customer experience? Do you have a passion for solving complex science challenges and building a sustainable e-commerce experience? The Robotics Delivery and Packaging Innovation (RDPI) team is seeking an Applied Scientist who will join a team of experts in the field of Machine Learning (ML), Statistics, Operations Research, Computer Vision and Generative AI to work together to break new ground in the world of automated packaging solutions. The RDPI team owns mission-critical automation and packaging solutions that impact billions of customer shipments annually across Amazon’s WW marketplaces. We manage billions of dollars in material spend and packaging labor costs while driving significant reductions in carbon emissions. Our team is revolutionizing e-commerce through advanced packaging automation, innovative sortation technology, and sustainable solutions. We're dramatically reducing single-use plastics across our network while developing next-generation automated solutions that can handle the majority of our packaging needs. We're also transforming our supply chain through strategic investments in paper manufacturing and innovative materials, driving both substantial cost savings and environmental benefits. This is an exciting opportunity to work on large-scale automation challenges that directly impact customer experience, operational efficiency, and environmental sustainability at one of the world's largest e-commerce companies. You'll work in a collaborative environment where you can pursue ambitious research with many peta-bytes of data, work on problems that haven’t been solved before, quickly implement and deploy your algorithmic ideas at scale, understand whether they succeed via statistically relevant experiments across millions of customers, and publish your research. You'll see the work you do directly improve the packaging experience of Amazon customers in the fulfillment technology space. If you are interested in robotics, computer vision, machine learning, operations research, statistics, big data, and building scalable solutions, this role is for you. Key job responsibilities A successful candidate in this role may perform some or all of the following responsibilities: - Leverage generative AI technologies to develop scalable solutions for automated product compatibility and safety assessments (e.g., evaluating product shipping compatibility, safety requirements, and packaging configurations) - Develop advanced AI models by extracting predictive features from multiple data sources (product/packaging images, product descriptions, sensor data, geospatial data) to forecast package-related damages and optimize packaging decisions based on customer preference prediction - Develop and implement computer vision solutions to automate packaging workflows and detect product/packaging defects in real-time operations - Build causal inference model to capture the downstream impacts of different packaging designs and delivery experience - Design and implement robotic control algorithms to optimize machine efficiency and meet diverse business objectives A day in the life Scientists on our team work daily with dedicated product and engineering partners to bring innovative solutions from concept to production. You'll divide your time between deep technical work—building models, analyzing results, iterating on algorithms—and collaborative activities like design reviews, stakeholder presentations, and cross-functional planning. You'll also have opportunities to support science initiatives across the broader RDPI organization (1500+ people), partnering with diverse teams to solve high-impact problems and scale your solutions across Amazon. About the team We are a team of scientists with diverse technical backgrounds spanning Machine Learning, Operations Research, Causal Inference, and Econometrics. We tackle complex, high-impact problems that directly influence Amazon's strategic decisions and financial performance. Our solutions typically require combining multiple methodologies, and you'll work collaboratively with other scientists while partnering closely with product and engineering teams to bring your innovations into production systems. You'll have the opportunity to grow your expertise across disciplines while delivering measurable business impact at scale.

Do you want to be part of a team that's revolutionizing Amazon's fulfillment and packaging technology? Are you ready to optimize systems that process tens-of-millions of customer packages daily with the lowest cost to serve and a defect-free customer experience? Do you have a passion for solving complex science challenges and building a sustainable e-commerce experience? The Robotics Delivery and Packaging Innovation (RDPI) team is seeking an Applied Scientist who will join a team of experts in the field of Machine Learning (ML), Statistics, Operations Research, Computer Vision and Generative AI to work together to break new ground in the world of automated packaging solutions. The RDPI team owns mission-critical automation and packaging solutions that impact billions of customer shipments annually across Amazon’s WW marketplaces. We manage billions of dollars in material spend and packaging labor costs while driving significant reductions in carbon emissions. Our team is revolutionizing e-commerce through advanced packaging automation, innovative sortation technology, and sustainable solutions. We're dramatically reducing single-use plastics across our network while developing next-generation automated solutions that can handle the majority of our packaging needs. We're also transforming our supply chain through strategic investments in paper manufacturing and innovative materials, driving both substantial cost savings and environmental benefits. This is an exciting opportunity to work on large-scale automation challenges that directly impact customer experience, operational efficiency, and environmental sustainability at one of the world's largest e-commerce companies. You'll work in a collaborative environment where you can pursue ambitious research with many peta-bytes of data, work on problems that haven’t been solved before, quickly implement and deploy your algorithmic ideas at scale, understand whether they succeed via statistically relevant experiments across millions of customers, and publish your research. You'll see the work you do directly improve the packaging experience of Amazon customers in the fulfillment technology space. If you are interested in robotics, computer vision, machine learning, operations research, statistics, big data, and building scalable solutions, this role is for you. Key job responsibilities A successful candidate in this role may perform some or all of the following responsibilities: - Leverage generative AI technologies to develop scalable solutions for automated product compatibility and safety assessments (e.g., evaluating product shipping compatibility, safety requirements, and packaging configurations) - Develop advanced AI models by extracting predictive features from multiple data sources (product/packaging images, product descriptions, sensor data, geospatial data) to forecast package-related damages and optimize packaging decisions based on customer preference prediction - Develop and implement computer vision solutions to automate packaging workflows and detect product/packaging defects in real-time operations - Build causal inference model to capture the downstream impacts of different packaging designs and delivery experience - Design and implement robotic control algorithms to optimize machine efficiency and meet diverse business objectives A day in the life Scientists on our team work daily with dedicated product and engineering partners to bring innovative solutions from concept to production. You'll divide your time between deep technical work—building models, analyzing results, iterating on algorithms—and collaborative activities like design reviews, stakeholder presentations, and cross-functional planning. You'll also have opportunities to support science initiatives across the broader RDPI organization (1500+ people), partnering with diverse teams to solve high-impact problems and scale your solutions across Amazon. About the team We are a team of scientists with diverse technical backgrounds spanning Machine Learning, Operations Research, Causal Inference, and Econometrics. We tackle complex, high-impact problems that directly influence Amazon's strategic decisions and financial performance. Our solutions typically require combining multiple methodologies, and you'll work collaboratively with other scientists while partnering closely with product and engineering teams to bring your innovations into production systems. You'll have the opportunity to grow your expertise across disciplines while delivering measurable business impact at scale.

Sponsored Products and Brands (SPB) is at the heart of Amazon Advertising, helping millions of advertisers—from small businesses to global brands—connect with customers at the moments that matter most. Our advertising solutions enable sellers, vendors, and brand owners to grow their businesses by reaching shoppers with relevant, engaging ads across Amazon's store and beyond. We're obsessed with delivering measurable results for advertisers while creating a delightful shopping experience for customers. Are you interested in defining the science behind the future of advertising? Sponsored Products and Brands science teams are pioneering breakthrough agentic AI systems—pushing the boundaries of large language models, autonomous reasoning, planning, and decision-making to build intelligent agents that fundamentally transform how advertisers succeed on Amazon. As an SPB applied science leader, you'll have end-to-end ownership of the product and scientific vision, research agenda, model architectures, and evaluation frameworks required to deliver state-of-the-art agentic AI solutions for our advertising customers. You'll get to work on problems that are fast-paced, scientifically rich, and deeply consequential. You'll also be able to explore novel research directions, take bold bets, and collaborate with remarkable scientists, engineers, and product leaders. We'll look for you to bring your diverse perspectives, deep technical expertise, and scientific rigor to make Amazon Advertising even better for our advertisers and customers. With global opportunities for talented scientists and science leaders, you can decide where a career in Amazon Ads Science takes you! We are kicking off a new initiative within SPB to leverage agentic AI solutions to revolutionize how advertisers create, manage, and optimize their advertising campaigns. This is a unique opportunity to lead a business-critical applied science initiative from its inception—defining the scientific charter, establishing foundational research pillars, and building a multi-year science roadmap for transformative impact. As the single-threaded applied science leader, you will build and guide a dedicated team of applied scientists, research scientists, and machine learning engineers, working closely with cross-functional engineering and product partners, to research, develop, and deploy agentic AI systems that fundamentally reimagine the advertiser journey. Your charter will begin with advancing the science behind intelligent agents that simplify campaign creation, automate optimization decisions through autonomous reasoning and planning, and deliver personalized advertising strategies at scale. You will pioneer novel approaches in areas such as LLM-based agent architectures, multi-step planning and tool use, retrieval-augmented generation, reinforcement learning from human and business feedback, and robust evaluation methodologies for agentic systems. You will expand to proactively identify and tackle the next generation of AI-powered advertising experiences across the entire SPB portfolio. This high-visibility role places you as the science leader driving our strategy to democratize advertising success—making it effortless for advertisers of all sizes to achieve their business goals while delivering relevant experiences for Amazon customers. Key job responsibilities Build, mentor, and lead a new, high-performing applied science organization of applied scientists, research scientists, and engineers, fostering a culture of scientific excellence, innovation, customer obsession, and ownership. Define, own, and drive the long-term scientific and product vision and research strategy for agentic AI-powered advertising experiences across Sponsored Products and Brands—identifying the highest-impact research problems and charting a path from exploration to production. Lead the research, design, and development of novel agentic AI models and systems—including LLM-based agent architectures, multi-agent orchestration, planning and reasoning frameworks, tool-use mechanisms, and retrieval-augmented generation pipelines—that deliver measurable value for advertisers and create delightful, intuitive experiences. Establish rigorous scientific methodology and evaluation frameworks for assessing agent performance, reliability, safety, and advertiser outcomes, setting a high bar for experimentation, reproducibility, and offline-to-online consistency. Partner closely with senior business, engineering, and product leaders across Amazon Advertising to translate advertiser pain points and business opportunities into well-defined science problems, and deliver cohesive, production-ready solutions that drive advertiser success. Drive execution from research to production at scale, ensuring models and agentic systems meet high standards for quality, robustness, latency, safety, and reliability for mission-critical advertising services operating at Amazon scale. Champion a culture of scientific inquiry and technical depth that encourages bold experimentation, publication of novel research, relentless simplification, and continuous improvement. Communicate your team's scientific vision, research breakthroughs, strategy, and progress to senior leadership and key stakeholders, ensuring alignment with broader Amazon Advertising objectives and contributing to Amazon's position at the forefront of applied AI. Develop a science roadmap directly tied to advertiser outcomes, revenue growth, and business plans, delivering on commitments for high-impact research and modeling initiatives that shape the future of AI-powered digital advertising.

Have you ever wondered what it takes to transform millions of manual network planning decisions into AI-powered precision? Network Planning Solutions is looking for scientific innovators obsessed with building the AI/ML intelligence that makes orchestrating complex global operations feel effortless. Here, you'll do more than just build models; you'll create 'delight' by discovering and deploying the science that delivers exactly what our customers need, right when they need it. If you're ready to transform complex data patterns into breakthrough AI capabilities that power intuitive human experiences, you've found your team. Network Planning Solutions architects and orchestrates Amazon's customer service network of the future. By building AI-native solutions that continuously learn, predict and optimize, we deliver seamless customer experiences and empower associates with high-value work—driving measurable business impact at a global scale. As a Sr. Manager, Applied Science, you will own the scientific innovation and research initiatives that make this vision possible. You will lead a team of applied scientists and collaborate with cross-functional partners to develop and implement breakthrough scientific solutions that redefine our global network. Key job responsibilities Lead AI/ML Innovation for Network Planning Solutions: - Develop and deploy production-ready demand forecasting algorithms that continuously sense and predict customer demand using real-time signals - Build network optimization algorithms that automatically adjust staffing as conditions evolve across the service network - Architect scalable AI/ML infrastructure supporting automated forecasting and network optimization capabilities across the system Drive Scientific Excellence: - Build and mentor a team of applied scientists to deliver breakthrough AI/ML solutions - Design rigorous experiments to validate hypotheses and quantify business impact - Establish scientific excellence mechanisms including evaluation metrics and peer review processes Enable Strategic Transformation: - Drive scientific innovation from research to production - Design and validate next-generation AI-native models while ensuring robust performance, explainability, and seamless integration with existing systems. - Partner with Engineering, Product, and Operations teams to translate AI/ML capabilities into measurable business outcomes - Navigate ambiguity through experimentation while balancing innovation with operational constraints - Influence senior leadership through scientific rigor, translating complex algorithms into clear business value A day in the life Your day will be a dynamic blend of scientific innovation and strategic problem-solving. You'll collaborate with cross-functional teams, design AI algorithms, and translate complex data patterns into intuitive solutions that drive meaningful business impact. About the team We are Network Planning Solutions, a team of scientific innovators dedicated to reshaping how global service networks operate. Our mission is to create AI-native solutions that continuously learn, predict, and optimize customer experiences. We empower our associates to tackle high-value challenges and drive transformative change at a global scale.

The Amazon Fulfillment Technologies (AFT) Science team is seeking an exceptional Applied Scientist with strong operations research and optimization expertise to develop production solutions for one of the most complex systems in the world: Amazon's Fulfillment Network. At AFT Science, we design, build, and deploy optimization, statistics, machine learning, and GenAI/LLM solutions that power production systems running across Amazon Fulfillment Centers worldwide. We tackle a wide range of challenges throughout the network, including labor planning and staffing, pick scheduling, stow guidance, and capacity risk management. Our mission is to develop innovative, scalable, and reliable science-driven production solutions that exceed the published state of the art, enabling systems to run optimally and continuously (from every few minutes to every few hours) across our large-scale network. Key job responsibilities As an Applied Scientist, you will collaborate with scientists, software engineers, product managers, and operations leaders to develop optimization-driven solutions that directly impact process efficiency and associate experience in the fulfillment network. Your key responsibilities include: - Develop deep understanding and domain knowledge of operational processes, system architecture, and business requirements - Dive deep into data and code to identify opportunities for continuous improvement and disruptive new approaches - Design and develop scalable mathematical models for production systems to derive optimal or near-optimal solutions for existing and emerging challenges - Create prototypes and simulations for agile experimentation of proposed solutions - Advocate for technical solutions with business stakeholders, engineering teams, and senior leadership - Partner with software engineers to integrate prototypes into production systems - Design and execute experiments to test new or incremental solutions launched in production - Build and monitor metrics to track solution performance and business impact About the team Amazon Fulfillment Technology (AFT) designs, develops, and operates end-to-end fulfillment technology solutions for all Amazon Fulfillment Centers (FCs). We harmonize the physical and virtual worlds so Amazon customers can get what they want, when they want it. The AFT Science team brings expertise in operations research, optimization, statistics, machine learning, and GenAI/LLM, combined with deep domain knowledge of operational processes within FCs and their unique challenges. We prioritize advancements that support AFT tech teams and focus areas rather than specific fields of research or individual business partners. We influence each stage of innovation from inception to deployment, which includes both developing novel solutions and improving existing approaches. Our production systems rely on a diverse set of technologies, and our teams invest in multiple specialties as the needs of each focus area evolve.

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 (audio, images, videos, text) by building AI-driven solutions for advertisers. To accomplish this, we are investing in understanding how best users can leverage Generative AI methods such as latent-diffusion models, large language models (LLM), generative audio (music and speech synthesis), computer vision (CV), reinforced learning (RL) and related. As an Applied Scientist you will be part of a close-knit team of other applied scientists and product managers, UX and engineers 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 at the development and use of multi-modal Generative AI and can use state-of-the-art generative music and audio, 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 SOTA research to raise the bar within the team. As an Applied Scientist on this team, you will: - Drive the invention and development of novel multi-modal agentic architectures and models for the use of Generative AI methods in advertising. - Work closely and integrate end-to-end proof-of-concept Machine Learning projects that have a high degree of ambiguity, scale and complexity. - Build interface-oriented systems that use 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. - Curate relevant multi-modal datasets. - Perform hands-on analysis and modeling of experiments with human-in-the-loop that eg 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. - Mentor and help recruit Applied Scientists to the team. - Present results and explain methods to senior leadership. - Willingness to publish research at internal and external top scientific venues. - Write and pursue IP submissions. Key job responsibilities This role is focused on developing new multi-modal Generative AI methods to augment generative imagery and videos. You will develop new multi-modal paradigms, models, datasets and agentic architectures that will be at the core of advertising-facing tools that we are launching. You may also work on development of ML and GenAI models suitable for advertising. You will conduct literature reviews to stay on the SOTA of the field. You will regularly engage with product managers, UX designers and engineers who will partner with you to productize your work. For reference see our products: Enhanced Video Generator, Creative Agent and Creative Studio. A day in the life On 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 team The team is a dynamic team of applied scientists, UX researchers, engineers and product leaders. 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: UK (London), USA (Seattle).