Careers

The Sponsored Products and Brands (SPB) team at Amazon Ads is re-imagining the advertising landscape through industry leading generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you are energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. About our team The Sponsored Products and Brands -- Offsite team builds solutions that extend campaigns beyond the Amazon store, reaching shoppers across third-party environments where they discover and shop. We combine large-scale, low-latency systems with advanced machine learning and AI to deliver high-quality sponsored experiences in high-intent surfaces. Key job responsibilities We are looking for an Applied Science Manager with a strong background in ML and GenAI solutions. You will contribute to goals carried by Amazon’s leadership team (S-Team). As an Applied Science Manager, you will: - Lead Applied Scientists, Machine Learning Engineers, and Software Development Engineers. - Surface qualitative and quantitative insights as the voice of the advertisers to shape product direction and ensure product-market fit. - Develop science and engineering roadmaps to increase advertiser outcomes with ML and GenAI solutions, run annual planning, and foster cross-team collaboration on model development. - Hire and develop top talent, provide technical and career development guidance to scientists and engineers within and across the organization. - Stay informed about recent scientific publications, industry trends, and system designs. - Work with off-Amazon publishers to launch new high-impact placements that increase advertiser outcomes. - Develop and own mechanisms to track and improve advertiser performance. - Distill complex ideas complex thoughts, succinctly, adapting to the medium of communication.

The AURORA: Alexa Understanding, Runtime, ORchestration, and Applied sciences org is looking for an Applied Science Manager with a background in Natural Language Processing, Machine/Deep Learning, and Large Language Models (LLMs). You will be working with a team of Applied Scientists to enhance existing features and explore new possibilities with LLM empowerment. You will own high visibility programs with broad visibility and global impact. You will interact with a cross-functional team of Science, Product, and Engineering leaders. We are looking for an Applied Science Manager who will play a key role in the next generation of AI powered Conversational Assistants. Core Leadership & Team Management * Lead and manage applied scientists working on conversational AI capabilities across the full Alexa+ agent execution path * Build and develop high-performing science teams focused on understanding, reasoning, evaluation, and runtime systems * Foster cross-functional collaboration between science and engineering teams to deliver both customer-facing (CX) and developer-facing (DX) experiences Platform & Innovation * Develop modular, reusable platforms that enable 1P and 3P engineers and scientists to accelerate innovation * Transform how builders create conversational AI solutions at scale * Drive evaluation tooling and assessment frameworks to measure conversational experience quality Cross-Organizational Collaboration * Partner with teams across the organization to align goals and accelerate delivery * Navigate organizational changes and simplify interactions between components and teams * Establish clear communication channels and workflows across reporting lines Strategic Impact * Contribute to the team's mission of being the "AI runtime backbone and horizontal intelligence team" for Alexa * Balance advancing research with delivering robust, scalable production solutions * Drive both innovation velocity and operational excellence simultaneously Key job responsibilities * Lead and manage a team of Applied and Data scientists responsible for building and enhancing capabilities for Alexa+ * Collaborate with cross-functional teams to build methods to align Amazon’s LLMs with human preferences. * Identify and prioritize research opportunities that have the potential to significantly impact our AI systems. * Mentor and guide team members to achieve their career goals and objectives. * Communicate research findings and progress to senior leadership and stakeholders. * Rapidly experiment and drive productisation to deliver customer impact. * Drive academic partnership with top tier Indian university as part of the org’s AI/ML Center initiative. * Participate in and drive science publications in peer-reviewed venues of repute. About the team Aurora is the AI runtime backbone and horizontal intelligence team that powers Alexa's core infrastructure, AI capabilities, and specialized conversational models. We revolutionize conversational AI through three core pillars: architecting mission-critical AI runtime systems, advancing science solutions that connect key conversational capabilities, and transforming how builders create at scale. We empower 1P and 3P engineers and scientists worldwide with modular, reusable platforms that accelerate innovation—while delivering accurate, responsive, and reliable conversational experiences to millions of end-users through operational excellence at scale.

You will be working with a unique and gifted team developing exciting products for consumers. The team is a multidisciplinary group of engineers and scientists engaged in a fast paced mission to deliver new products. The team faces a challenging task of balancing cost, schedule, and performance requirements. You should be comfortable collaborating in a fast-paced and often uncertain environment, and contributing to innovative solutions, while demonstrating leadership, technical competence, and meticulousness. Your deliverables will include development of thermal solutions, concept design, feature development, product architecture and system validation through to manufacturing release. You will support creative developments through application of analysis and testing of complex electronic assemblies using advanced simulation and experimentation tools and techniques. Key job responsibilities * Evaluate and optimize thermal solution requirements of consumer electronic products * Use simulation tools like Star-CCM+ or FloTherm XT/EFD for analysis and design of products * Validate design modifications for thermal concerns using simulation and actual prototypes * Establish temperature thresholds for user comfort level and component level considering reliability requirements * Have intimate knowledge of various materials and heat spreaders solutions to resolve thermal issues * Use of programming languages like Python and Matlab for analytical/statistical analyses and automation * Collaborate as part of device team to iterate and optimize design parameters of enclosures and structural parts to establish and deliver project performance objectives * Design and execute of tests using statistical tools to validate analytical models, identify risks and assess design margins * Create and present analytical and experimental results * Develop and apply design guidelines based on project learnings

The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through novel generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace ecosystem. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. Key job responsibilities As an Applied Scientist on our team, you will * Develop AI solutions for Sponsored Brands advertiser and shopper experiences. Build recommendation systems that leverage generative models to develop and improve campaigns. * You invent and design new solutions for scientifically-complex problem areas and/or opportunities in new business initiatives. * You drive or heavily influence the design of scientifically-complex software solutions or systems, for which you personally write significant parts of the critical scientific novelty. You take ownership of these components, providing a system-wide view and design guidance. These systems or solutions can be brand new or evolve from existing ones. * Define a long-term science vision and roadmap for our Sponsored Brands advertising business, driven from our customers' needs, translating that direction into specific plans for applied scientists and engineering teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. * Work closely with engineers and product managers to design, implement and launch AI solutions end-to-end; * Design and conduct A/B experiments to evaluate proposed solutions based on in-depth data analyses; * Think big about the arc of development of Gen AI over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems * Effectively communicate technical and non-technical ideas with teammates and stakeholders; * Translate complex scientific challenges into clear and impactful solutions for business stakeholders. * Mentor and guide junior scientists, fostering a collaborative and high-performing team culture. * Stay up-to-date with advancements and the latest modeling techniques in the field About the team We are on a mission to make Amazon the best in class destination for shoppers to discover, engage, and purchase relevant products, from brands that are relevant to them. In this role, you will design and implement Gen AI solutions that help millions of advertisers create more effective ad campaigns with intelligent recommendations, while improving the overall experience at Amazon's global scale.

Do you want to shape the next generation of AI-driven customer experiences for Amazon’s most ground-breaking products? Join us and help invent the future of shopping. We are seeking a passionate, innovative, and highly skilled Applied Scientist with expertise in AI, Agentic LLMs, Generative AI, Machine Learning, and NLP to help build LLM-powered solutions for Amazon’s BuyForMe product, which enables Amazon customers to discover and purchase products from any merchants. Our team develops science and agentic AI capabilities that power a seamless, end-to-end shopping experience for Amazon customers. We build and advance technologies such as agentic frameworks, LLM fine-tuning, reinforcement learning, prompt engineering, RAG, MCP, and automated benchmarking to improve pre-purchase, in-purchase, and post-purchase workflows. Key job responsibilities As an Applied Scientist on our team, you will: Invent, implement, and evaluate state-of-the-art models and agentic systems that directly impact customer experience. Conduct research that may lead to publications, patents, or cross-Amazon technical influence. Collaborate with engineers, product managers, and other scientists to translate business challenges into scalable science solutions. Run experiments with real customer data and validate hypotheses in a high-impact product environment. Drive excellence in model performance, safety, reliability, and evaluation frameworks.

This role leads the science function in WW Stores Finance as part of the IPAT organization (Insights, Planning, Analytics and Technology), driving transformative innovations in financial analytics through AI and machine learning across the global Stores finance organization. The successful candidate builds and directs a multidisciplinary team of data scientists, applied scientists, economists, and product managers to deliver scalable solutions that fundamentally change how finance teams generate insights, automate workflows, and make decisions. As part of the WW Stores Finance leadership team, this leader partners with engineering, product, and finance stakeholders to translate emerging AI capabilities into production systems that deliver measurable improvements in speed, accuracy, and efficiency. The role's outputs directly inform VP/SVP/CFO/CEO leadership decisions and drive impact across the entire Stores P&L. Success requires translating complex technical concepts for finance domain experts and business leaders while maintaining deep technical credibility with science and engineering teams. The role demands both strategic vision—identifying high-impact opportunities where AI can transform finance operations—and execution excellence in coordinating project planning, resource allocation, and delivery across multiple concurrent initiatives. This leader establishes methodologies and models that enable Amazon finance to achieve step-change improvements in both the speed and quality of business insights, directly supporting critical processes including month-end reporting, quarterly guidance, annual planning cycles, and financial controllership. Key job responsibilities Transformation of Finance Workflows — Lead development of agentic AI solutions that automate routine finance tasks and transform how teams communicate business insights. Deploy these solutions across financial analysis, narrative generation, and dynamic table creation for month-end reporting and planning cycles. Partner with engineering and product teams to integrate these capabilities into production systems that directly support Stores Finance and FGBS automation goals, delivering measurable reductions in manual effort and cycle time. Science-Based Forecasting — Develop and deploy machine learning forecasts that integrate into existing planning processes including OP1, OP2, and quarterly guidance cycles. Partner with finance teams across WW Stores to iterate on forecast accuracy, applying these models either as alternative viewpoints to complement bottoms-up forecasts or as hands-off replacements for manual forecasting processes. Establish evaluation frameworks that demonstrate forecast performance against business benchmarks and drive adoption across critical planning workflows. Financial Controllership — Scale AI capabilities across controllership workstreams to improve reporting accuracy and automate manual processes. Leverage generative AI to identify financial risk through systematic pattern recognition in transaction data, account reconciliations, and variance analysis. Develop production systems that enhance decision-making speed and quality in financial close, audit preparation, and compliance reporting, delivering quantifiable improvements in error detection rates and process efficiency. About the team IPAT (Insights, Planning, Analytics, and Technology) is a team in the Worldwide Amazon Stores Finance organization composed of leaders across engineering, finance, product, and science. Our mission is to reimagine finance using technology and science to provide fast, efficient, and accurate insights that drive business decisions and strengthen governance. We are dedicated to improving financial operations through innovative applications of technology and science. Our work focuses on developing adaptive solutions for diverse financial use cases, applying AI to solve complex financial challenges, and conducting financial data analysis. Operating globally, we strive to develop adaptable solutions for diverse markets. We aim to advance financial science, continually improving accuracy, efficiency, and insight generation in support of Amazon's mission to be Earth's most customer-centric company.

The Measurement Intelligence Science Team (MIST) in the Measurement, Ad Tech, and Data Science (MADS) organization of Amazon Ads serves a centralized role developing solutions for a multitude of performance measurement products. We create solutions which measure the comprehensive impact of their ad spend, including sales impacts both online and offline and across timescales, and provide actionable insights that enable our advertisers to optimize their media portfolios. We leverage a host of scientific technologies to accomplish this mission, including Generative AI, classical ML, Causal Inference, Natural Language Processing, and Computer Vision. As an Applied Science Manager on the team, you will lead a team of scientists to define and execute a transformative vision for holistic measurement and reporting insights for ad effectiveness. Your team will own the science solutions for foundational experimentation platforms, foundational customer journey understanding technologies, state of the art attribution algorithms to measure the role of advertising in driving observed retail outcomes, and/or agentic AI solutions that help advertisers get quick access to custom insights that inform how to get the most out of their ad spend. Key job responsibilities You independently manage a team of scientists. You identify the needs of your team and effectively grow, hire, and promote scientists to maintain a high-performing team. You have a broad understanding of scientific techniques, several of which may fall out of your specific job function. You define the strategic vision for your team. You establish a roadmap and successfully deliver scientific solutions that execute that vision. You define clear goals for your team and effectively prioritize, balancing short-term needs and long-term value. You establish clear and effective metrics and scientific process to enforce consistent, high-quality artifact delivery. You proactively identify risks and bring them to the attention of your manager, customers, and stakeholders with plans for mitigation before they become roadblocks. You know when to escalate. You communicate ideas effectively, both verbally and in writing, to all types of audiences. You author strategic documentation for your team. You communicate issues and options with leaders in such a way that facilitates understanding and that leads to a decision. You work successfully with customers, leaders, and engineering teams. You foster a constructive dialogue, harmonize discordant views, and lead the resolution of contentious issues. About the team We are a team of scientists across Applied, Research, Data Science and Economist disciplines. You will work with colleagues with deep expertise in ML, NLP, CV, Gen AI, and Causal Inference with a diverse range of backgrounds. We partner closely with top-notch engineers, product managers, sales leaders, and other scientists with expertise in the ads industry and on building scalable modeling and software solutions.

The Measurement Intelligence Science Team (MIST) in the Measurement, Ad Tech, and Data Science (MADS) organization of Amazon Ads serves a centralized role developing solutions for a multitude of performance measurement products. We create solutions which measure the comprehensive impact of their ad spend, including sales impacts both online and offline and across timescales, and provide actionable insights that enable our advertisers to optimize their media portfolios. We leverage a host of scientific technologies to accomplish this mission, including Generative AI, classical ML, Causal Inference, Natural Language Processing, and Computer Vision. As an Applied Science Manager on the team, you will lead a team of scientists to define and execute a transformative vision for holistic measurement and reporting insights for ad effectiveness. Your team will own the science solutions for foundational experimentation platforms, foundational customer journey understanding technologies, state of the art attribution algorithms to measure the role of advertising in driving observed retail outcomes, and/or agentic AI solutions that help advertisers get quick access to custom insights that inform how to get the most out of their ad spend. Key job responsibilities You independently manage a team of scientists. You identify the needs of your team and effectively grow, hire, and promote scientists to maintain a high-performing team. You have a broad understanding of scientific techniques, several of which may fall out of your specific job function. You define the strategic vision for your team. You establish a roadmap and successfully deliver scientific solutions that execute that vision. You define clear goals for your team and effectively prioritize, balancing short-term needs and long-term value. You establish clear and effective metrics and scientific process to enforce consistent, high-quality artifact delivery. You proactively identify risks and bring them to the attention of your manager, customers, and stakeholders with plans for mitigation before they become roadblocks. You know when to escalate. You communicate ideas effectively, both verbally and in writing, to all types of audiences. You author strategic documentation for your team. You communicate issues and options with leaders in such a way that facilitates understanding and that leads to a decision. You work successfully with customers, leaders, and engineering teams. You foster a constructive dialogue, harmonize discordant views, and lead the resolution of contentious issues. About the team We are a team of scientists across Applied, Research, Data Science and Economist disciplines. You will work with colleagues with deep expertise in ML, NLP, CV, Gen AI, and Causal Inference with a diverse range of backgrounds. We partner closely with top-notch engineers, product managers, sales leaders, and other scientists with expertise in the ads industry and on building scalable modeling and software solutions.

Do you want to lead the Ads industry and redefine how we measure the effectiveness of Amazon Ads business? Are you passionate about causal inference, Deep Learning/DNN, raising the science bar, and connecting leading-edge science research to Amazon-scale implementation? If so, come join Amazon Ads to be an Economist leader within our Advertising Incrementality Measurement science team! Our work builds the foundations for providing customer-facing experimentation tools, furthering internal research & development on Econometrics, and building out Amazon's advertising measurement offerings. Incrementality is a lynchpin for the next generation of Amazon Advertising measurement solutions and this role will play a key role in the release and expansion of these offerings. Key job responsibilities As an Economist leader within the Advertising Incrementality Measurement (AIM) science team, you are responsible for defining and executing on key workstreams within our overall causal measurement science vision. In particular, you can lead the development of experimental methodologies to measure ad effectiveness, and also build observational models that lay the foundations for understanding the impact of individual ad touchpoints for billions of daily ad interactions. You will work on a team of Applied Scientists, Economists, and Data Scientists, alongside a dedicated Engineering team, to work backwards from customer needs and translate product ideas into concrete science deliverables. You will be a thought leader for inventing scalable causal measurement solutions that support highly accurate and actionable insights--from defining and executing hundreds of thousands of RCTs, to developing an exciting science R&D agenda. You will be working with massive data and industry-leading partner scientists, while also interfacing with leadership to define our future vision. Your work will help shape the future of Amazon Advertising. About the team AIM is a cross disciplinary team of engineers, product managers, economists, data scientists, and applied scientists with a charter to build scientifically-rigorous causal inference methodologies at scale. Our job is to help customers cut through the noise of the modern advertising landscape and understand what actions, behaviors, and strategies actually have a real, measurable impact on key outcomes. The data we produce becomes the effective ground truth for advertisers and partners making decisions affecting millions in advertising spend.

AWS GameTech Cortex is seeking an experienced Applied Scientist to join our team that specializes in full stack data solutions for games. In this role, you will drive the development and deployment of machine learning solutions that directly impact how game developers build, operate, and optimize their games on AWS. You will work at the intersection of gaming, data science, and cloud infrastructure to solve complex problems in areas such as player behavior prediction, game performance optimization, content recommendation, and anti-cheat systems. As a senior member of the team, you will lead the design and implementation of ML models and algorithms that process massive-scale gaming data. You will collaborate with game studios, AWS service teams, and product managers to identify high-impact opportunities and translate them into scalable ML solutions. Your work will influence the gaming experiences of millions of players worldwide while helping game developers make data-driven decisions. The ideal candidate combines deep expertise in machine learning with a passion for gaming and the ability to deliver production-ready solutions. You will mentor junior scientists, establish best practices for ML development, and contribute to the technical direction of the team. Key job responsibilities Design, develop, and deploy machine learning models and algorithms that solve critical problems for game developers, including player analytics, game performance optimization, content personalization, and fraud detection Lead end-to-end ML projects from problem definition through production deployment, ensuring solutions are scalable, maintainable, and deliver measurable business impact Analyze large-scale gaming datasets to identify patterns, extract insights, and develop predictive models that improve game operations and player experience Collaborate with game studios and AWS service teams to understand their challenges, define requirements, and deliver ML solutions that integrate seamlessly with their workflows Establish and promote best practices for ML development, experimentation, and deployment within the team, including model evaluation, A/B testing, and monitoring Mentor and provide technical guidance to junior applied scientists and engineers, fostering a culture of innovation and technical excellence Stay current with the latest research in machine learning, gaming analytics, and related fields, and apply relevant advances to solve customer problems Communicate complex technical concepts and results to both technical and non-technical audiences, including senior leadership Contribute to the technical strategy and roadmap for ML capabilities in AWS GameTech About the team AWS GameTech Cortex is an applied science & ML team, that specializes in full stack data solutions for games.