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Amazon Ads call for proposals — Spring 2025

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

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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.

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Sr. Applied Scientist , Grocery, Retail & In-Store Experience (GRAISE)
IN, KA, Bengaluru
We are looking for a Senior Applied Scientist who will own the science strategy and technical direction for computer vision and machine learning within the Amazon grocery ecosystem. You will identify the highest-impact problems in ambiguous, rapidly evolving domains, frame them rigorously, and drive solutions from research through production at scale. You will lead cross-functional technical decisions with engineering, product, and business partners, shaping not just what we build but also how we invest. This is a role where your scientific judgment, architectural choices, and ability to create clarity from ambiguity will directly define the intelligence layer powering millions of grocery shopping experiences. Key job responsibilities * Own the end-to-end science strategy for computer vision and machine learning solutions in the grocery domain, navigating ambiguity to identify the highest-impact opportunities * Develop novel approaches to complex, unsolved perception and identification challenges where off-the-shelf methods are insufficient; publish findings internally or externally to advance the state of the art * Define the evaluation framework and success criteria for model performance, establishing metrics that connect scientific outcomes to measurable business impact and using these to influence roadmap prioritization * Lead cross-functional technical design with engineering, product, and operations partners, driving architecture decisions for model serving, data pipelines, and system reliability at scale rather than solely handing off models for productionization * Identify and resolve ambiguous, cross-team technical dependencies (e.g., upstream data quality, annotation infrastructure, model interoperability) that block progress across multiple workstreams; propose and drive solutions proactively * Influence technical direction beyond the immediate team mentor scientists, raise the bar in hiring, establish best practices for experimentation and model development, and represent the team's science strategy to senior leadership * Communicate complex technical trade-offs and recommendations to VP-level stakeholders, shaping investment decisions and aligning cross-org partners on science-informed product direction A day in the life As a Senior Applied Scientist on the GRAISE team, you'll own the technical strategy for how computer vision and multimodal learning come together to solve perception problems in grocery stores — many of which no one has cleanly formulated yet. On any given day, you might diagnose a surprising failure mode from overnight experiments and decide whether to pivot your approach entirely, co-architect a serving system with engineers while defining confidence thresholds and graceful degradation paths, present a precision-recall trade-off to senior leaders in terms that shape launch decisions and investment priorities, or unblock a cross-team dependency on annotation infrastructure — all while mentoring junior scientists and carving out time for deep technical work on problems the team hasn't cracked. Your scientific judgment and architectural choices will directly shape the shopping experience for millions of customers across Amazon's grocery stores. About the team The GRAISE team (Grocery, Retail & In-Store Experience) within World Wide Grocery Store Tech (WWGST) builds foundational AI and machine learning systems that power Amazon's in-store grocery technologies. We develop domain-specific models that solve uniquely complex challenges in grocery — from smart shopping carts and inventory intelligence to personalization and store operations. Our mission is to create technology which makes grocery shopping more convenient, economical, personalized, and enjoyable for customers while empowering retailers with operational efficiency
Applied Science Manager, Translation Services
US, WA, Seattle
Have you ever wondered how Amazon launches and maintains a consistent customer experience across hundreds of countries and languages it serves its customers? If so, we have an exciting opportunity for you! Translation Services is seeking an Applied Science Manager to own the technical vision and multi-year science roadmap spanning machine translation, multimodal content (image translation, video subtitling), and automated quality evaluation. This leader will manage scientists and MLEs, define research direction for novel problem spaces with limited industry precedent, and bridge science breakthroughs into production-ready systems operating at Amazon scale. As a leader of the Science team of TS, this person will be responsible for leading their team in designing algorithmic solutions based on data and mathematics for translating billions of words annually across 130+ and expanding set of locales. The goal is to build solutions with minimal human touch involved in any language translation and ensure accurate translated text is available to our worldwide customers in a streamlined and optimized manner. With access to vast amounts of data, technology, and a diverse community of talented individuals, you will have the opportunity to make a meaningful impact on the way customers and stakeholders engage with Amazon and our platform worldwide. This role requires strong technical skills, a deep understanding of machine learning approaches, and a solid grasp on NLP and LLM techniques to solve complex language translation challenges. You must have a demonstrated ability for optimizing, developing, launching, and maintaining large-scale production systems. As a key member of the team, you will oversee all aspects of the software lifecycle: design, experimentation, implementation, and testing. You should be willing to dive deep when needed, move rapidly with a bias for action, and get things done. You should have an entrepreneurial spirit, know how to deliver, and long for the opportunity to build pioneering solutions to challenging problems. This role will demand resourcefulness and willingness to learn on both the technical and business side. Key job responsibilities In this role, you will work closely with business partners, applied scientists, software development engineers, and product managers to accelerate building solutions to expand translation capabilities. You will have significant influence on our overall strategy by helping define science and engineering strategy, define product features, drive system architecture, and spearhead the best-practices that enable a quality product. You will also influence the development processes, and develop well-rounded skills such as leadership, and effective project management. Building a strong development team and developing career plans for the scientists and engineers reporting to you will be a key responsibility. Throughout, you should possess creativity, curiosity, and excellent judgment to thrive in an environment of ambiguity. A day in the life You will spend your days collaborating with scientists, developers, customers, stakeholders, and converting the business needs into a data-driven solution. You will support a team to design and execute science products. You will dive deep into the data and balance technical execution with longer term strategy. You will grow and develop your team. About the team Translation Services is entering a phase where the problems ahead are fundamentally different from the problems we've solved. Our text translation stack is production-grade and serving 30+ language pairs across Retail. But the next frontier — image translation, video subtitle localization, long form text and automated quality evaluation — represents novel research problems at Amazon scale with limited industry precedent.
Data Scientist
US, CA, San Francisco
If you are interested in this position, please apply on Twitch's Career site https://www.twitch.tv/jobs/en/ About Us: Twitch is the world’s biggest live streaming service, with global communities built around gaming, entertainment, music, sports, cooking, and more. It is where thousands of communities come together for whatever, every day. We’re about community, inside and out. You’ll find coworkers who are eager to team up, collaborate, and smash (or elegantly solve) problems together. We’re on a quest to empower live communities, so if this sounds good to you, see what we’re up to on LinkedIn and X, and discover the projects we’re solving on our Blog. Be sure to explore our Interviewing Guide to learn how to ace our interview process. About the Role Join the Monetization team at Twitch, where we build the products that help creators make a living on the platform. You'll work on products like Subscriptions, Bits, and Gifting, and the pricing and packaging decisions behind them. You'll partner closely with product, engineering, finance, and data teams to measure the impact of new features, design and analyze experiments, and apply causal inference methods to inform decisions where A/B testing isn't possible. The work ranges from high-velocity experimentation on consumer-facing products to deeper pricing, policy, and segmentation analyses where causal identification is the central challenge. This role is well-suited for someone with a strong economics or causal ML foundation who wants to apply rigorous statistical thinking to real product decisions at scale. You'll need to be comfortable writing SQL, working with imperfect data, and partnering with stakeholders to turn analysis into product impact. Our team is based at Twitch HQ in San Francisco, CA. You can work in San Francisco, CA; New York, NY; or Seattle, WA You Will - Apply causal inference methods where experimentation isn't feasible - Develop models and analyses that inform pricing, segmentation, and revenue optimization - Design, run, and analyze A/B experiments - Partner with product, engineering, and finance to translate ambiguous business questions into measurement frameworks - Build and maintain dashboards, reporting, and analytical tooling that support ongoing decision-making Perks - Medical, Dental, Vision & Disability Insurance - 401(k) - Maternity & Parental Leave - Flexible PTO - Amazon Employee Discount
Senior Applied Scientist, International Seller Services
IN, TS, Hyderabad
At Amazon, we strive to be Earth's most customer-centric company, where customers can find and discover anything they want to buy online. Our mission in International Seller Services (ISS) is to provide technology solutions for improving the seller and customer experience, drive seller compliance, maximize seller success, and improve internal workforce productivity. Team's main focus is to build products that are scalable across different regions of the world, while working in partnership with ISS regional stakeholders and multiple partner teams across Amazon. As an Applied Scientist, you will be responsible for modeling complex problems, discovering insights, and building risk algorithms that identify opportunities through statistical models, machine learning, and visualization techniques to improve operational efficiency. As an Applied Scientist, you will leverage your expertise in Machine Learning, Natural Language Processing (NLP), and Large Language Models (LLM) to develop innovative solutions for Amazon's ISS team. You'll be responsible for modeling complex problems, building innovative algorithms, and discovering actionable insights through statistical models and visualization techniques to enhance operational efficiency in the e-commerce space. The role combines usage of latest AI technology with practical business applications, requiring someone passionate about transforming the way we interact with technology while delivering measurable impact through advanced analytics and machine learning solutions. You will need to collaborate effectively with business and product leaders within ISS and cross-functional teams to build scalable solutions against high organizational standards. The candidate should be able to apply a breadth of tools, data sources, and Data Science techniques to answer a wide range of high-impact business questions and proactively present new insights in concise and effective manner. The candidate should be an effective communicator capable of independently driving issues to resolution and communicating insights to non-technical audiences. This is a high impact role with goals that directly impacts the bottom line of the business. Responsibilities: - Analyze terabytes of data to define and deliver on complex analytical deep dives to unlock insights and build scalable solutions through science to ensure security of Amazon’s platform and transactions Build Machine Learning and/or statistical models that evaluate the transaction legitimacy and track impact over time Ensure data quality throughout all stages of acquisition and processing, including data sourcing/collection, ground truth generation, normalization, transformation, and cross-lingual alignment/mapping Define and conduct experiments to validate/reject hypotheses, and communicate insights and recommendations to Product and Tech teams Develop efficient data querying infrastructure for both offline and online use cases Collaborate with cross-functional teams from multidisciplinary science, engineering and business backgrounds to enhance current automation processes Learn and understand a broad range of Amazon’s data resources and know when, how, and which to use and which not to use. Maintain technical document and communicate results to diverse audiences with effective writing, visualizations, and presentations Key job responsibilities • You will extract huge volumes of data from various sources and construct complex analyses. • You should be detail-oriented and must have an aptitude for solving unstructured problems. You should work in a self-directed environment, own tasks and drive them to completion • You should have excellent business and communication skills to be able to work with business owners to develop and define key business questions and to build data sets that answer those questions. You own customer relationship about data and execute tasks that are manifestations of such ownership, like ensuring high data availability, low latency, documenting data details and transformations and handling user notifications and training • You will work with distributed machine learning and statistical algorithms upon a large Hadoop cluster to harness enormous volumes at scale to serve our customers
Research Scientist, network planning optimization world wide, Supply Chain Optimization Technology
LU, Luxembourg
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? We are looking for a Research Scientist who will be responsible to develop cutting-edge scientific solutions to optimize our fulfillment strategy across multiple regions of the world (EU, JP, IN and more), to maximize our Customer Experience and minimize our cost and carbon footprint. You will partner with the worldwide scientific community to help design the optimal fulfillment strategy for Amazon. You will also collaborate with technical teams to develop optimization tools for network flow planning and execution systems. Finally, you will also work with business and operational stakeholders to influence their strategy and gather inputs to solve problems. To be successful in the role, you will need deep analytical skills and a strong scientific background. The role also requires excellent communication skills, and an ability to influence across business functions at different levels. You will work in a fast-paced environment that requires you to be detail-oriented and comfortable in working with technical, business and technical teams.
Applied Scientist II - Robotics Simulation, Amazon Robotics R&D
US, MA, Boston
We are looking for an Applied Scientist to join the Robotics Simulation team at Amazon Robotics. In this role you will design, build, and validate the simulation environments and policy training pipelines that enable robots to learn manipulation and mobility skills in simulation and transfer them to real hardware. You will work at the intersection of robotics simulation science and modern Physical AI: building GPU-accelerated RL environments, implementing imitation learning workflows, characterizing sim-to-real gaps, tuning physics parameters against real-world data, and evaluating learned policies both in simulation and on physical robots. You will collaborate closely with SDEs who build platform infrastructure, Technical Artists who create simulation assets, and partner science teams who consume your environments and pipelines for their model development. This is a hands-on, execution-focused role. You will own specific simulation science deliverables end-to-end, from environment design through policy evaluation, with increasing scope and independence over time. You will contribute to technical design discussions, propose improvements to the team's simulation fidelity and training methodology, and help establish best practices for robot learning in simulation. Key job responsibilities * Design and implement GPU-accelerated reinforcement learning and imitation learning environments in NVIDIA Isaac Lab for manipulation and mobility tasks. * Build and maintain policy training pipelines supporting diverse model architectures (diffusion policies, VLAs, behavior cloning, actor-critic RL) and evaluate trained policies in simulation. * Characterize and reduce sim-to-real gaps through systematic validation: compare simulated sensor outputs, kinematics, and dynamics against real-world robot data, then implement targeted improvements. * Implement domain randomization strategies (visual, physics, geometric) to improve policy robustness and transfer to real hardware. * Develop sim-to-real transfer techniques including system identification, physics parameter calibration, and visual domain adaptation. * Create robot embodiment validation tests (joint kinematics, actuator response, contact behavior) to ensure digital twins are faithful to real hardware. * Build data pipelines for recording, replaying, and augmenting demonstration data (from teleoperation or automated trajectory generation) to scale training data volume. * Contribute to end-effector modeling and contact dynamics tuning, ensuring physically plausible gripper and tool interactions in simulation. * Author design documents for new simulation science capabilities and contribute to technical reviews. * Collaborate with partner science teams to understand their model architectures and ensure simulation environments meet their training requirements. A day in the life Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply! About the team The Robotics Simulation team is a multidisciplinary organization of SDEs, Applied Scientists, and Technical Artists at Amazon Robotics. We build the simulation infrastructure that powers Physical AI development, from photorealistic synthetic data to GPU-accelerated training environments. Our simulation stack enables robots to be designed, trained, and validated entirely in simulation before physical hardware exists, compressing development timelines and de-risking robotics programs across Amazon. The team delivers end-to-end simulation stacks for Amazon's robotics programs, including high-fidelity robot digital twins, teleoperation data collection infrastructure, scalable synthetic demonstration generation, policy training and inference pipelines (RL, imitation learning, VLAs), domain randomization for sim-to-real transfer, and model validation in simulation. We partner closely with hardware teams, science organizations, and robotics program leads across Amazon Robotics.
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