Social

Amazon Ads call for proposals — Spring 2025

Advancing customer protections in the era of artificial intelligence in digital advertising.

3 min read
Share

About this CFP

Amazon Ads is committed to protect customers from fraud, abuse, illegal and harmful content. We prioritize customer protection through a comprehensive approach of strict policies, thorough review processes, and safety measures to ensure digital advertising content meet high standards. We maintain robust reporting systems, allowing for swift action against policy violations. These multilayered safeguards work in tandem to shield customers from exposure to abusive and harmful content, fostering a secure advertising environment for both consumers and advertisers.

We welcome proposals in the context of digital advertising in the following research tracks:

  1. Fraud, Abuse, and financial scams
  2. Behavioral foundational models to distinguish human and bot behavior
  3. Multi-modal classification of online content and websites
  4. Device and website identification
  5. Detection of plagiarized content
  6. Cyber threat activity, malicious and adversarial misuse of AI and LLMs
  7. Decentralized identifiers, verifiable credentials, data lineage and transparency
  8. Large language models for labeling, annotation and auditing of model performance
  9. Detection and mitigation of hallucination in LLMs for content analysis
  10. Protection of vulnerable individuals, specially child and teen safety

Timeline

Submission period: March 19 to May 7, 2025 (11:59PM Pacific Time).
Decision letters will be sent out in August 2025.

Award details

Selected Principal Investigators (PIs) may receive the following:

  1. Unrestricted funds, no more than $80,000 USD on average
  2. AWS Promotional Credits, no more than $40,000 USD on average
  3. Training resources, including AWS tutorials and hands-on sessions with Amazon scientists and engineers

Awards are structured as one-time unrestricted gifts. The budget should include a list of expected costs specified in USD, and should not include administrative overhead costs. The final award amount will be determined by the awards panel.

Eligibility requirements

Please refer to the ARA Program rules on the Rules and Eligibility page.

Proposal requirements

Proposals should be prepared according to the proposal template. In addition, to submit a proposal for this CFP, please also include the following information:

  1. Description of the proposed solution and its innovative aspects
  2. Explanation of how the project addresses the specified challenges
  3. Plan for the development and implementation of the methodology or dataset
  4. Potential impact on customer protections
  5. List of open-source tools, datasets or methodologies you plan to contribute to
  6. List of AWS tools you will use

Selection criteria

Proposals will be reviewed by a panel of experts. Proposals will be evaluated on the following:

  1. Immediate and sizeable impact on customer protections
  2. Practicality and scalability of the solutions
  3. Feasibility and clarity of the proposed approach
  4. Potential for widespread adoption and implementation
  5. Feasibility to open source
  6. Generation of publicly available benchmarks (metrics and data sets)

Expectations from recipients

To the extent deemed reasonable, Award recipients should acknowledge the support from ARA. Award recipients will inform ARA of publications, presentations, code and data releases, blogs/social media posts, and other speaking engagements referencing the results of the supported research or the Award. Award recipients are expected to provide updates and feedback to ARA via surveys or reports on the status of their research. Award recipients will have an opportunity to work with ARA on an informational statement about the awarded project that may be used to generate visibility for their institutions and ARA.

Related content

Work with us

See more jobs See more jobs
Applied Scientist II, Alexa International
IN, KA, Bengaluru
Alexa International is looking for passionate, talented, and inventive Senior Applied Scientists to help build industry-leading technology with Large Language Models (LLMs) and multimodal systems, requiring strong deep learning and generative models knowledge. Senior applied scientists will drive cross-team scientific strategy, influence partner teams, and deliver solutions that have broad impact across Alexa's international products and services. Key job responsibilities As a Applied Scientist with II the Alexa International team, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art with LLMs, particularly delivering industry-leading scientific research and applied AI for multi-lingual applications — a challenging area for the industry globally. Your work will directly impact our global customers in the form of products and services that support Alexa+. You will leverage Amazon's heterogeneous data sources and large-scale computing resources to accelerate advances in text, speech, and vision domains. The ideal candidate possesses a solid understanding of machine learning, speech and/or natural language processing, modern LLM architectures, LLM evaluation & tooling, and a passion for pushing boundaries in this vast and quickly evolving field. They thrive in fast-paced environment, like to tackle complex challenges, excel at swiftly delivering impactful solutions while iterating based on user feedback, and are able to influence and align multiple teams around a shared scientific vision. A day in the life * Analyze, understand, and model customer behavior and the customer experience based on large-scale data. * Build novel online & offline evaluation metrics and methodologies for multimodal personal digital assistants. * Fine-tune/post-train LLMs using advanced and innovative techniques like SFT, DPO, Reinforcement Learning (RLHF and RLAIF) for supporting model performance specific to a customer’s location and language. * Quickly experiment and set up experimentation framework for agile model and data analysis or A/B testing. * Contribute through industry-first research to drive innovation forward. * Drive cross-team scientific strategy and influence partner teams on LLM evaluation frameworks, post-training methodologies, and best practices for international speech and language systems. * Lead end-to-end delivery of scientifically complex solutions from research to production, including reusable science components and services that resolve architecture deficiencies across teams. * Serve as a scientific thought leader, communicating solutions clearly to partners, stakeholders, and senior leadership. * Actively mentor junior scientists and contribute to the broader internal and external scientific community through publications and community engagement.
Principal Applied Scientist, PXT
US, NY, New York
About the Role In this role, you will own the science strategy and technical vision for this intelligence layer, leading a team of applied scientists working across GenAI and predictive modeling. You will shape how heterogeneous signals — text, behavioral, network, temporal — come together to power talent applications at Amazon scale, from workforce forecasting to personalized development to compensation strategy. You will identify opportunities where science investment can have material impact on long-term objectives or annual goals and build consensus around needed investments, working comfortably across different modeling paradigms and data modalities to guide principal and senior scientists in their most challenging and strategic decisions while serving as the strategic science advisor to PXT leaders operating at the Director, VP, and SVP levels. As a hands-on leader, you will personally own development and delivery of the most complex science problems at the intersection of multiple ML disciplines, stay current with emergent AI/ML science and engineering trends to influence focus areas in a rapidly evolving landscape, and participate in organizational planning, hiring, mentorship, and leadership development. Key job responsibilities • Lead technical initiatives in people science models, driving breakthrough approaches through hands-on research and development in areas like foundation models for predictive modeling, efficient multi-modal LLMs, and zero-shot learning • Design and implement novel ML architectures that push the boundaries of how workforce signals are represented, fused, and predicted at scale • Guide technical direction for research initiatives across the team, ensuring robust performance in production environments serving hundreds of thousands of employees • Mentor and develop senior scientists while maintaining strong individual technical contributions on the most complex cross-domain problems • Collaborate with engineering teams to optimize and scale models for real-world talent applications • Influence technical decisions and implementation strategies across teams, shaping the long-term platform architecture About the team The People eXperience and Technology (PXT) Core Science Team uses science, engineering, and customer-obsessed problem solving to proactively identify mechanisms, process improvements, and products that simultaneously improve Amazon and Amazonians' lives, wellbeing, and value of work. As an interdisciplinary team combining talents from machine learning, statistics, economics, behavioral science, engineering, and product development, the Core Science team develops and delivers measurable solutions through innovation and rapid prototyping to accelerate informed, accurate, and reliable decision-making backed by science and data.
Applied Scientist II, Reinforcement Learning
US, MA, N.reading
Amazon is seeking exceptional talent to help develop the next generation of advanced robotics systems that will transform automation at Amazon's scale. We're building revolutionary robotic systems that combine cutting-edge AI, sophisticated control systems, and advanced mechanical design to create adaptable automation solutions capable of working safely alongside humans in dynamic environments. This is a unique opportunity to shape the future of robotics and automation at an unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic dexterous manipulation, locomotion, and human-robot interaction. This role presents an opportunity to shape the future of robotics through innovative applications of deep learning and large language models. At Amazon we leverage advanced robotics, machine learning, and artificial intelligence to solve complex operational challenges at an unprecedented scale. Our fleet of robots operates across hundreds of facilities worldwide, working in sophisticated coordination to fulfill our mission of customer excellence. The ideal candidate will contribute to research that bridges the gap between theoretical advancement and practical implementation in robotics. You will be part of a team that's revolutionizing how robots learn, adapt, and interact with their environment. Join us in building the next generation of intelligent robotics systems that will transform the future of automation and human-robot collaboration. Key job responsibilities - Design and implement whole body control methods for balance, locomotion, and dexterous manipulation - Utilize state-of-the-art in methods in learned and model-based control - Create robust and safe behaviors for different terrains and tasks - Implement real-time controllers with stability guarantees - Collaborate effectively with multi-disciplinary teams to co-design hardware and algorithms for loco-manipulation - Mentor junior engineer and scientists
Applied Scientist II, Last Mile Science
IN, KA, Bengaluru
Have you ever ordered a product on Amazon and when that box with the smile arrived you wondered how it got to you so fast? Have you wondered where it came from and how much it cost Amazon to deliver it to you? If so, the WW Amazon Logistics, Business Analytics team is for you. We manage the delivery of tens of millions of products every week to Amazon’s customers, achieving on-time delivery in a cost-effective manner. We are looking for an enthusiastic, customer obsessed, Applied Scientist with good analytical skills to help manage projects and operations, implement scheduling solutions, improve metrics, and develop scalable processes and tools. The primary role of an Operations Research Scientist within Amazon is to address business challenges through building a compelling case, and using data to influence change across the organization. This individual will be given responsibility on their first day to own those business challenges and the autonomy to think strategically and make data driven decisions. Decisions and tools made in this role will have significant impact to the customer experience, as it will have a major impact on how the final phase of delivery is done at Amazon. Ideal candidates will be a high potential, strategic and analytic graduate with a PhD in (Operations Research, Statistics, Engineering, and Supply Chain) ready for challenging opportunities in the core of our world class operations space. Great candidates have a history of operations research, and the ability to use data and research to make changes. This role requires robust program management skills and research science skills in order to act on research outcomes. This individual will need to be able to work with a team, but also be comfortable making decisions independently, in what is often times an ambiguous environment. Responsibilities may include: - Develop input and assumptions based preexisting models to estimate the costs and savings opportunities associated with varying levels of network growth and operations - Creating metrics to measure business performance, identify root causes and trends, and prescribe action plans - Managing multiple projects simultaneously - Working with technology teams and product managers to develop new tools and systems to support the growth of the business - Communicating with and supporting various internal stakeholders and external audiences
Senior Applied Scientist, Insights, Prime Video
GB, London
Come build the future of entertainment with us. Are you interested in shaping the future of movies and television? Do you want to define the next generation of how and what Amazon customers are watching? Prime Video is a premium streaming service that offers customers a vast collection of TV shows and movies - all with the ease of finding what they love to watch in one place. We offer customers thousands of popular movies and TV shows including Amazon Originals and exclusive licensed content to exciting live sports events. We also offer our members the opportunity to subscribe to add-on channels which they can cancel at anytime and to rent or buy new release movies and TV box sets on the Prime Video Store. Prime Video is a fast-paced, growth business - available in over 200 countries and territories worldwide. The team works in a dynamic environment where innovating on behalf of our customers is at the heart of everything we do. If this sounds exciting to you, please read on. The Insights team is looking for an Applied Scientist for our London office experienced in generative AI and large models. This is a wide impact role working with development teams across the UK, India, and the US. This greenfield project will deliver features that reduce the operational load for internal Prime Video builders and for this, you will need to develop personalized recommendations for their services. You will have strong technical ability, excellent teamwork and communication skills, and a strong motivation to deliver customer value from your research. Our position offers opportunities to grow your technical and non-technical skills and make a global impact immediately. Key job responsibilities - Develop machine learning algorithms for high-scale recommendations problems - Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both quantitative analysis and business judgement - Collaborate with software engineers to integrate successful experimental results into Prime Video wide processes - Communicate results and insights to both technical and non-technical audiences, including through presentations and written reports A day in the life You will lead the design of machine learning models that scale to very large quantities of data across multiple dimensions. You will embody scientific rigor, designing and executing experiments to demonstrate the technical effectiveness and business value of your methods. You will work alongside other scientists and engineering teams to deliver your research into production systems. About the team Our team owns Prime Video observability features for development teams. We consume PBs of data daily which feed into multiple observability features focussed on reducing the customer impact time.
Sr. Thermal Scientist, Hardware - Product Integrity
CN, 31, Shanghai
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
Research Scientist II - AMZ9674001
US, CA, San Francisco
MULTIPLE POSITIONS AVAILABLE Employer: AMAZON DEVELOPMENT CENTER U.S., INC., Offered Position: Research Scientist II Job Location: San Francisco, California Job Number: AMZ9674001 Position Responsibilities: Design research studies to obtain scientific information. Develop theories or models of physical phenomena encountered in quantum computing, superconducting qubit device physics, materials or process development and characterization. Collaborate with others to determine design specifications, including of superconducting quantum processor chips, microwave chip packages, and associated electrical and mechanical components. Develop scientific or mathematical models to predict physical device behavior and performance, and verify the implementation of computational models. Apply mathematical principles or statistical approaches to solve problems, for example to validate modeling predictions under experimental uncertainty using statistical methods. Operate laboratory or field equipment and scientific instrumentation for device fabrication, device characterization, or advanced materials research. Develop new algorithms or methods for designing, simulating, or measuring quantum computers. Develop performance metrics or standards related to quantum information technology. Recommend technical design or process changes to improve quality or performance of superconducting quantum processors and efficiency of their design, manufacture, and testing. Collaborate on research activities with scientists or technical specialists. Prepare scientific or technical reports or presentations and present research results to others. 40 hours / week, 8:00am-5:00pm, Salary Range $168,126/year to $212,800/year. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, visit: https://www.aboutamazon.com/workplace/employee-benefits. Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation.#0000
Senior Manager, Research Science, WW Stores Finance, WW Stores Finance
US, WA, Seattle
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.
Sr. Economist, Advertising Incrementality Measurement
US, NY, New York
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.
Applied Science Manager, Ads Measurement Science
US, NY, New York
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.
See more jobs

Work with us

See more jobs See more jobs
Applied Science Manager, Ads Measurement Science
US, NY, New York
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.
Applied Scientist, Prime Video - Title Lifecycle Presentation
US, WA, Seattle
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! The Prime Video Title Lifecycle Presentation team sits at the intersection of science, experimentation, and customer experience. We leverage data signals and rigorous testing to present the most engaging information about our content to customers at precisely the right moment. Our mission is to ensure every customer interaction with Prime Video content is informed, relevant, and compelling in order to drive discovery and engagement across our vast catalog. We're seeking an Applied Scientist who excels at building sophisticated machine learning systems for content presentation and discovery. The ideal candidate brings deep expertise in: - Multi-modal embeddings for rich metadata representation, enabling nuanced understanding of content attributes and customer preferences - Contextualized ranking systems that adapt to customer intent, viewing context, and real-time signals - Reinforcement learning frameworks that create continuous improvement loops, allowing our systems to learn and optimize from customer interactions over time - General modeling techniques with strong fundamentals in machine learning and statistical methods - Recommender systems experience, with proven ability to build and scale personalization solutions You'll work with cutting-edge technology to solve complex problems in content discovery, leveraging large-scale data to create experiences that delight millions of Prime Video customers worldwide. Key job responsibilities As an Applied Scientist, you will have access to large datasets with billions of images and video to build large-scale machine learning systems. Additionally, you will analyze and model terabytes of text, images, and other types of data to solve real-world problems and translate business and functional requirements into quick prototypes or proofs of concept. We are looking for smart scientists capable of using a variety of domain expertise combined with machine learning and statistical techniques to invent, design, evangelize, and implement state-of-the-art solutions for never-before-solved problems.
Applied Scientist, Sponsored Products Off-Search Homepage Team
US, CA, Palo Alto
The Sponsored Products and Brands (SPB) team at Amazon Ads is re-imagining advertising through generative AI, transforming how millions of customers discover products and engage with brands across Amazon.com and beyond. We bridge human creativity with artificial intelligence across the full advertising lifecycle—from ad creation and optimization to performance analysis and customer insights. Within SPB, the Off-Search team builds ad experiences across surfaces beyond Search—product detail pages, the homepage, and store-in-store pages. Our team is specifically focused on ad and experience expansion on Homepage: growing the number of ad placements, introducing new widget formats, and delivering richer, more personalized ad experiences that integrate naturally with the shopping journey. We partner with Amazon Stores to ensure ads complement organic recommendations—new arrivals, deals, basket-building content, and fast-delivery options—while adapting to shopper preferences, seasonal moments, and diverse page layouts. We operate full stack, from backend retrieval and auction systems to the shopper-facing experience layer. If you're energized by solving complex challenges at the intersection of ads, personalization, and customer experience, join us in shaping the future of advertising on Amazon's most visited surface. Key job responsibilities This role will be pivotal in redesigning how ads contribute to a personalized, relevant, and inspirational shopping experience, with the customer value proposition at the forefront. Key responsibilities include, but are not limited to: - Contribute to the design and development of GenAI, deep learning, multi-objective optimization and/or reinforcement learning empowered solutions to transform ad retrieval, auctions, whole-page relevance, and/or bespoke shopping experiences. - Collaborate cross-functionally with other scientists, engineers, and product managers to bring scalable, production-ready science solutions to life. - Stay abreast of industry trends in GenAI, LLMs, and related disciplines, bringing fresh and innovative concepts, ideas, and prototypes to the organization. - Contribute to the enhancement of team’s scientific and technical rigor by identifying and implementing best-in-class algorithms, methodologies, and infrastructure that enable rapid experimentation and scaling. - Mentor and grow junior scientists and engineers, cultivating a high-performing, collaborative, and intellectually curious team. A day in the life As an Applied Scientist on the Sponsored Products and Brands Off-Search team, you will contribute to the development in Generative AI (GenAI) and Large Language Models (LLMs) to revolutionize our advertising flow, backend optimization, and frontend shopping experiences. This is a rare opportunity to redefine how ads are retrieved, allocated, and/or experienced—elevating them into personalized, contextually aware, and inspiring components of the customer journey. You will have the opportunity to fundamentally transform areas such as ad retrieval, ad allocation, whole-page relevance, and differentiated recommendations through the lens of GenAI. By building novel generative models grounded in both Amazon’s rich data and the world’s collective knowledge, your work will shape how customers engage with ads, discover products, and make purchasing decisions. If you are passionate about applying frontier AI to real-world problems with massive scale and impact, this is your opportunity to define the next chapter of advertising science. About the team The Off-Search team within Sponsored Products and Brands (SPB) is focused on building delightful ad experiences across surfaces beyond Search on Amazon—such as product detail pages, the homepage, and store-in-store pages—to drive monetization. Our Homepage team is at the center of this mission, leveraging large language models (LLMs) to build a new generation of personalized ad experiences that understand shopper intent, adapt to individual preferences, and deliver contextually relevant creatives in real time. Beyond Homepage, we are designing these experiences as reusable building blocks that can scale across other pages on Amazon—detail pages, browse, store-in-store, and emerging surfaces—so that innovation on one page accelerates growth everywhere. We operate full stack, from backend ads-retail edge services, ads retrieval, and ad auctions to shopper-facing experiences, working in close partnership with Amazon Stores to integrate advertising seamlessly alongside organic content like new arrivals, basket-building recommendations, and fast-delivery options. Curious about our advertising solutions? Discover more about Sponsored Products and Sponsored Brands to see how we're helping businesses grow on Amazon.com and beyond!
Applied Scientist, Selection Monitoring
IN, KA, Bengaluru
Selection Monitoring team is responsible for making the biggest catalog on the planet even bigger. In order to drive expansion of the Amazon catalog, we develop advanced ML/AI technologies to process billions of products and algorithmically find products not already sold on Amazon. We work with structured, semi-structured and Visually Rich Documents using deep learning, NLP and image processing. The role demands a high-performing and flexible candidate who can take responsibility for success of the system and drive solutions from research, prototype, design, coding and deployment. We are looking for Applied Scientists to tackle challenging problems in the areas of Information Extraction, Efficient crawling at internet scale, developing ML models for website comprehension and agents to take multi-step decisions. You should have depth and breadth of knowledge in text mining, information extraction from Visually Rich Documents, semi structured data (HTML) and advanced machine learning. You should also have programming and design skills to manipulate Semi-Structured and unstructured data and systems that work at internet scale. You will encounter many challenges, including: - Scale (build models to handle billions of pages), - Accuracy (requirements for precision and recall) - Speed (generate predictions for millions of new or changed pages with low latency) - Diversity (models need to work across different languages, market places and data sources) You will help us to - Build a scalable system which can algorithmically extract information from world wide web. - Intelligently cluster web pages, segment and classify regions, extract relevant information and structure the data available on semi-structured web. - Build systems that will use existing Knowledge Base to perform open information extraction at scale from visually rich documents. Key job responsibilities - Use AI, NLP and advances in LLMs/SLMs and agentic systems to create scalable solutions for business problems. - Efficiently Crawl web, Automate extraction of relevant information from large amounts of Visually Rich Documents and optimize key processes. - Design, develop, evaluate and deploy, innovative and highly scalable ML models, esp. leveraging latest advances in RL-based fine tuning methods like DPO, GRPO etc. - Work closely with software engineering teams to drive real-time model implementations. - Establish scalable, efficient, automated processes for large scale model development, model validation and model maintenance. - Lead projects and mentor other scientists, engineers in the use of ML techniques. - Publish innovation in research forums.
Applied Scientist, Business Data Technologies
IN, KA, Bengaluru
RBS (Retail Business Services) Tech team works towards enhancing the customer experience (CX) and their trust in product data by providing technologies to find and fix Amazon CX defects at scale. Our platforms help in improving the CX in all phases of customer journey, including selection, discoverability & fulfilment, buying experience and post-buying experience (product quality and customer returns). The team also develops GenAI platforms for automation of Amazon Stores Operations. As a Sciences team in RBS Tech, we focus on foundational ML research and develop scalable state-of-the-art ML solutions to solve the problems covering customer experience (CX) and Selling partner experience (SPX). We work to solve problems related to multi-modal understanding (text and images), task automation through multi-modal LLM Agents, supervised and unsupervised techniques, multi-task learning, multi-label classification, aspect and topic extraction for Customer Anecdote Mining, image and text similarity and retrieval using NLP and Computer Vision for product groupings and identifying duplicate listings in product search results. Key job responsibilities As an Applied Scientist, you will be responsible to design and deploy scalable GenAI, NLP and Computer Vision solutions that will impact the content visible to millions of customer and solve key customer experience issues. You will develop novel LLM, deep learning and statistical techniques for task automation, text processing, image processing, pattern recognition, and anomaly detection problems. You will define the research and experiments strategy with an iterative execution approach to develop AI/ML models and progressively improve the results over time. You will partner with business and engineering teams to identify and solve large and significantly complex problems that require scientific innovation. You will independently file for patents and/or publish research work where opportunities arise. The RBS org deals with problems that are directly related to the selling partners and end customers and the ML team drives resolution to organization level problems. Therefore, the Applied Scientist role will impact the large product strategy, identifies new business opportunities and provides strategic direction which is very exciting.
Applied Science Manager, Sponsored Products and Brands
US, WA, Seattle
The Sponsored Products and Brands 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'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 We are looking for an Applied Science Manager to lead the Amazon Sponsored Agent (ASA) team within Sponsored Products and Brands (SPB). ASA is new agentic service that enables publishers and apps to monetize their AI experiences with conversational and agentic ads. This team owns the core ASA platform that serves contextual ads across 1P surfaces (Alexa+, Amazon.com) and 3P publisher integrations, delivering AI-native ad formats including Sponsored Collections, Sponsored Brand Agents, and Commercial Insights that seamlessly integrate into conversational experiences. As an Applied Science Manager, you will innovate and design new conversational ad experiences that transform how customers discover and engage with products on conversational surfaces. You will lead a team of applied scientists and engineers to build and scale ASA's multi-agent system architecture for conversational commerce. You will own the science roadmap for contextual ad serving, conversation understanding, and commercial insights generation that help publishers monetize their AI chat experiences and unlock opportunities to scale Amazon's advertising business into new conversational surfaces. This role requires strong technical depth in NLP, LLMs, multi-agent systems, and information retrieval, combined with product innovation skills to envision and prototype new advertising experiences for conversational AI. You will manage and grow a science team, set research direction, and influence product strategy. You will work across organizational boundaries with engineering, product, and business teams to translate science investments and innovative product concepts into measurable business impact.
Applied Science Manager, AWS Generative AI Innovation Center
DE, BE, Berlin
Amazon launched the Generative AI Innovation Center (GenAIIC) in June 2023 to help AWS customers accelerate the use of Generative AI to solve business and operational problems and promote innovation in their organization (https://press.aboutamazon.com/2023/6/aws-announces- generative-ai-innovation-center). GenAIIC provides opportunities to innovate in a fast-paced organization that contributes to game-changing projects and technologies that get deployed on devices and in the cloud. As an Applied Science Manager in GenAIIC, you'll partner with technology and business teams to build new generative AI solutions that delight our customers. You will be responsible for directing a team of data/research/applied scientists, deep learning architects, and ML engineers to build generative AI models and pipelines, and deliver state-of-the-art solutions to customer’s business and mission problems. The successful candidate will possess both technical and customer-facing skills that will allow you to be the technical “face” of AWS within our solution providers’ ecosystem/environment as well as directly to end customers. The candidate must ne be able to drive discussions with senior technical and management personnel within customers and partners while hacing technical background that enables them to interact with and give guidance to AI scientists/engineers and software developers. The ideal candidate will also have a demonstrated ability to think strategically about business, product, and technical issues. Of critical importance, the candidate will be an excellent technical team manager, someone who knows how to hire, develop, and retain high quality technical talent. Key job responsibilities You will work directly with customers to drive adoption and shape the future of the most exciting emerging technology by understanding the business problem and guiding our customers in implementation of generative AI solutions, and developing long-term strategic relationships with key accounts You will help develop the industry’s best generative AI delivery team by enabling and coaching your specialist team on best practices and how to create and present value-driven architectures of widely varying size and complexity. You will grow an existing team by hiring, on-boarding, training, and developing new Scientists, Architects, and Engineers from internal and external sources. You will identify opportunities for building reusable technical assets/solutions/products based on recurring patterns of customer needs You will provide customer and market feedback to Product and Engineering teams to help define product direction You will drive revenue growth across a broad set of customers You will be a thought leader and drive value creation for our customers, shaping technical solutions, growing the team, and leading specific customer engagements You will deliver briefing and deep dive sessions to customers and guide customers on adoption patterns and paths to production About the team The GenAI Innovation Center helps customers define and execute AI Strategy, scope and develop use cases that will create the greatest value for their businesses, select/develop/customise/fine-tune the right models, define paths to navigate technical or business challenges, and make plans for launching solutions at scale, responsibly and cost efficiently
Senior Applied Scientist, Measurement, Ad Tech, and Data Science (MADS)
CA, ON, Toronto
The Measurement, Ad Tech, and Data Science (MADS) team at Amazon Ads is at the forefront of developing innovative solutions that help tens of millions of advertisers understand the value of their ad spend while prioritizing customer privacy and measurement quality. The Media Planning Science team, part of broader MADS team, develops and implements models that deliver insights and recommendations for strategic media planning and measurement across Amazon Advertising's product portfolio. Our mission is to help advertisers create and execute plans that meet their objectives while providing accurate measurement tools. We work on a multitude of problem statements that encompass Reach and Frequency, Budget Planning Optimization, and Recommendations. Our models leverage both heuristic and machine learning approaches including deep learning techniques, with insights delivered through agent-based tools and APIs that integrate seamlessly into user interfaces and programmatic systems to ensure optimal advertising outcomes. As a Senior Applied Scientist on the team, you will be at the forefront of innovation, developing media planning solutions end-to-end from inception to production. You will set the technical vision and innovate on behalf of our customers. You will propose, design, analyze, and productionize models to provide novel measurement insights to our customers. You will partner with engineering to deploy these solutions into production. You will work with key stakeholders from various business teams to enable advertisers to act upon those metrics. Key job responsibilities * Lead the development of media planning models and solutions that address the full spectrum of an advertiser's investment, focusing on scalable and efficient methodologies. * Collaborate closely with cross-functional teams including engineering, product management, and business teams to define and implement measurement solutions. * Use state-of-the-art scientific technologies including Generative AI, Classical Machine Learning, Causal Inference, Natural Language Processing, and Computer Vision to develop state of the art models that measure the impact of media plans across different metrics. * Drive experimentation and the continuous improvement of ML models through iterative development, testing, and optimization. * 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. * Foster collaborations between scientists to move faster, with broader impact. * Regularly engage with the broader scientific community with presentations, publications, and patents. A day in the life You will solve real-world problems by analyzing large amounts of data, generate business insights and opportunities, design simulations and experiments, and develop ML/DL models. The team is driven by business needs, which requires collaboration with other Scientists, Engineers, and Product Managers across the advertising organization. You will prepare written and verbal documents to share insights to audiences of varying levels of technical sophistication. About the team We are a team of scientists across Applied, Research, and Data Science disciplines. You will work with colleagues with deep expertise in ML, DL, NLP, 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.
Sr. Applied Scientist, Special Projects
US, NY, New York
Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the extreme. We focus on creating entirely new products and services with a goal of positively impacting the lives of our customers. No industries or subject areas are out of bounds. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have thirteen employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We are constantly learning through programs that are local, regional, and global. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. Our team highly values work-life balance, mentorship and career growth. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We care about your career growth and strive to assign projects and offer training that will challenge you to become your best. Key job responsibilities - Lead and execute complex, ambiguous research projects from ideation to production deployment - Drive technical strategy and roadmap decisions for ML/AI initiatives - Collaborate cross-functionally with product, engineering, and business teams to translate research into scalable products - Publish research findings at top-tier conferences and contribute to the broader scientific community - Establish best practices for ML experimentation, evaluation, and deployment
Senior Applied Scientist , Sponsored Products and Brands Ads Response Prediction
US, CA, Palo Alto
About Sponsored Products and Brands The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through 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'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 a Machine Learning Applied Scientist, you will: * Conduct deep data analysis to derive insights to the business, and identify gaps and new opportunities * Develop scalable and effective machine-learning models and optimization strategies to solve business problems * Run regular A/B experiments, gather data, and perform statistical analysis * Work closely with software engineers to deliver end-to-end solutions into production * Improve the scalability, efficiency and automation of large-scale data analytics, model training, deployment and serving * Conduct research on new machine-learning modeling and Generative AI solutions to optimize all aspects of Sponsored Products and Brands business About the team The Ad Response Prediction team within Sponsored Products and Brands (SPB) drives personalized shopping experiences for SPB Ads across placements, pages, and devices worldwide. We achieve this through ML and GenAI solutions that include customized shopper response prediction and session-level understanding to optimize every stage of the ad-serving process, from sourcing and bidding to widget discovery and auctions. Our responsibilities include advancing response prediction through model and feature innovations and extending prediction beyond the auction stage to areas such as targeting, sourcing, and bidding.
See more jobs
Amazon Research Awards.jpg

Amazon Research Awards

Collaborating with scientists around the world to fund research, share knowledge and encourage innovation.
Learn more
View from space of a connected network around planet Earth representing the Internet of Things.
Get more from Amazon Science
Subscribe to our newsletter

Amazon.com | Conditions of Use | Privacy | © 1996-2026 Amazon.com, Inc. or its affiliates

Social