Careers

RISC's vision is to make Amazon Earth’s most trusted shopping destination for safe and compliant products. We do this by protecting customers from products that are unsafe, illegal, illegally marketed, controversial or otherwise in violation of Amazon's policies while enabling our Selling Partners (SPs) to offer their broadest selection of safe and compliant products. We are seeking an exceptional Applied Scientist to join a team of experts in the field of agentic AI, GenAI, Machine Learning, Software Engineers, and work together to tackle challenging problems across diverse compliance domains. We leverage and train state-of-the-art large-language-models (LLMs), multi-modal model, mixed with elegant harness engineering and SKILL building to 1) detect illegal and unsafe products across the Amazon catalog; 2) automation safety and compliance content authoring; 3) reasoning over enforcement action to provide actionable insights to Amazon sellers. We work on machine learning problems for content generation, multi-modal classification, global product taxonomy, intent detection, information retrieval, anomaly and fraud detection, agentic AI, generative AI and multi-agent system. This is an exciting and challenging position to deliver scientific innovations into production systems at Amazon-scale to make immediate, meaningful customer impacts while also pursuing ambitious, long-term research. You will work in a highly collaborative environment where you can analyze and process large amounts of image, text, unstructured and tabular data. You will work on challenging science problems that have not been solved before, conduct rapid prototyping to validate your hypothesis, and deploy your algorithmic ideas at scale. There will be something new to learn every day as we work in an environment with rapidly evolving regulations and adversarial actors looking to outwit your best ideas. Key job responsibilities • Design and evaluate state-of-the-art algorithms and approaches in content generation, multi-modal classification, global product taxonomy, intent detection, information retrieval, anomaly and fraud detection, agentic AI, generative AI and multi-agent system. • Translate product and CX requirements into measurable science problems and metrics. • Collaborate with product and tech partners and customers to validate hypothesis, drive adoption, and increase business impact • Key author in writing high quality scientific papers in internal and external peer-reviewed conferences. A day in the life • Understanding customer problems, project timelines, and team/project mechanisms • Proposing science formulations and brainstorming ideas with team to solve business problems • Writing code, and running experiments with re-usable science libraries • Reviewing labels and audit results with investigators and operations associates • Sharing science results with science, product and tech partners and customers • Writing science papers for submission to peer-review venues, and reviewing science papers from other scientists in the team. • Contributing to team retrospectives for continuous improvements • Driving science research collaborations and attending study groups with scientists across Amazon

Amazon's Stores-Ads Science team operates at the intersection of Amazon's Stores and advertising businesses. We develop causal measurement systems, optimization algorithms, and machine learning models that inform how advertising affects shopper engagement, driving selling partner growth and marketplace economics. Our science shapes decisions both at the strategic level and in production systems. We are a team of interdisciplinary scientists who combine causal inference, economic modeling, and machine learning to drive measurable business impact. We are looking for an Applied Science Manager to lead our Ads Impact initiative. This team owns the science of understanding and optimizing how advertising creates value for shoppers and selling partners. What makes this role distinctive is its position at the frontier of AI and Economics: as Amazon's shopping experience evolves from traditional search toward LLM-powered, agentic commerce, the fundamental mechanisms through which advertising creates value are changing. This role will partner with leading scientists and academic researchers to measure these effects through large-scale causal experimentation, and develop novel methods to encode causal and economic reasoning into AI systems that optimize the shopping experience. Key job responsibilities In this role, you will lead a team of scientists, setting the technical vision and science roadmap for ads impact measurement and optimization. You will design experiments that identify the causal mechanisms through which advertising drives shopper engagement, advertiser value, and marketplace outcomes. You will develop optimization algorithms that integrate these causal signals into production and business decision-making, in close partnership with engineering and product teams across the organization. You will lead the research and communicate findings and recommendations to senior leadership through written narratives that connect technical science to business strategy. This role requires deep expertise in causal inference and experimental design, combined with strong applied ML skills and the engineering judgment to translate research into production systems. You will hire and develop future science leaders, think strategically, set ambitious roadmaps in highly ambiguous problem spaces, and foster a culture that values both intellectual depth and production impact. You will work cross-functionally, influencing across organizational boundaries to drive alignment on complex, multi-sided tradeoffs.

Amazon Industrial Robotics is seeking exceptional applied science talent to develop AI and machine learning systems that will enable the next generation of advanced manufacturing capabilities at unprecedented scale. We're building revolutionary software infrastructure that combines cutting-edge AI, large-scale optimization, and advanced manufacturing processes to create adaptive production control systems. As a Senior Applied Scientist, you will develop and improve machine learning systems that enable real-time manufacturing flow decisions. You will leverage state-of-the-art optimization and ML techniques, evaluate them against representative manufacturing scenarios, and adapt them to meet the robustness, reliability, and performance needs of production environments. You will invent new algorithms where gaps exist. You'll collaborate closely with software engineering, manufacturing engineering, robotics simulation, and operations teams, and your outputs will directly power the systems that determine what to build next, where to allocate resources, and how to maximize throughput. The ideal candidate brings deep expertise in optimization and machine learning, with a proven track record of delivering scientifically complex solutions into production. You are hands-on, writing significant portions of critical-path scientific code while driving your team's scientific agenda. If you're passionate about inventing the intelligent manufacturing systems of tomorrow rather than optimizing those of today, this role offers the chance to make a lasting impact on the future of automation. Key job responsibilities - Identify and devise new scientific approaches for constraint identification, dispatch optimization, WIP release control, and predictive flow intelligence when the problem is ill-defined and new methodologies need to be invented - Lead the design, implementation, and successful delivery of scientifically complex solutions for real-time manufacturing flow optimization in production - Design and build ML models and optimization algorithms including constraint prediction, starvation risk forecasting, and dispatch optimization - Write a significant portion of critical-path scientific code with solutions that are inventive, maintainable, scalable, and extensible - Execute rapid, rigorous experimentation with reproducible results, closing the gap between simulation and real manufacturing environments - Build evaluation benchmarks that measure model performance against manufacturing outcomes including constraint utilization and throughput rather than traditional ML metrics alone - Influence your team's science and business strategy through insightful contributions to roadmaps, goals, and priorities - Partner with manufacturing engineering, robotics simulation, and applied intelligence teams to ensure scientific approaches are grounded in operational reality - Drive your team's scientific agenda and role model publishing of research results at peer-reviewed venues when appropriate and not precluded by business considerations - Actively participate in hiring and mentor other scientists, improving their skills and ability to deliver - Write clear narratives and documentation describing scientific solutions and design choices

About Sponsored Products and Brands: The Sponsored Products and Brands (SPB) organization 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. About Our Team: The Brand Beacon team is responsible for inventing impressions offerings for brands to increase share of voice via premium experiences, helping brands get discovered, acquire new customers and sustainably grow customer lifetime value. We build end-to-end solutions that enable brands to drive discovery, visibility and share of voice. This includes building advertiser controls, shopper experiences, monetization strategies and optimization features. We succeed when (1) shoppers discover, engage and build affinity with brands and (2) brands can grow their business at scale with our advertising products. About This Role: As a Senior Scientist for the team, you will have the opportunity to apply your deep subject matter expertise in the area of ML, LLM and GenAI models. You will invent new product experiences that enable novel advertiser and shopper experiences. This role will liaise with internal Amazon partners and work on bringing state-of-the-art GenAI models to production, and stay abreast of the latest developments in the space of GenAI and identify opportunities to improve the efficiency and productivity of the team. Additionally, you will define a long-term science vision for our advertising business, driven by our customer’s needs, and translate it into actionable plans for our team of applied scientists and engineers. This role will play a critical role in elevating the team’s scientific and technical rigor, identifying and implementing best-in-class algorithms, methodologies, and infrastructure that enable rapid experimentation and scaling. You will communicate learnings to leadership and mentor and grow Applied AI talent across org. * Develop AI solutions for advertiser and shopper experiences. Build monetization and optimization systems that leverage generative models to value and improve campaign performance. * Define a long-term science vision and roadmap for our 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. * Design and conduct A/B experiments to evaluate proposed solutions based on in-depth data analyses. * Effectively communicate technical and non-technical ideas with teammates and stakeholders. * Stay up-to-date with advancements and the latest modeling techniques in the field. * 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. #GenAI

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 Data Scientist who will be responsible to develop 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. Key job responsibilities - Design and develop mathematical models to optimize inventory placement and product flows. - Design and develop statistical and optimization models for planning Supply Chain under uncertainty. - Manage several, high impact projects simultaneously. - Consult and collaborate with business and technical stakeholders across multiple teams to define new opportunities to optimize our Supply Chain. - Communicate data-driven insights and recommendations to diverse senior stakeholders through technical and/or business papers. - Leverage LLMs to improve explainability of our optimization solutions and drive engagement from supply chain planners across the world.

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

About Sponsored Products and Brands: The Sponsored Products and Brands (SPB) organization 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. About Our Team: The Brand Beacon team is responsible for inventing impressions offerings for brands to increase share of voice via premium experiences, helping brands get discovered, acquire new customers and sustainably grow customer lifetime value. We build end-to-end solutions that enable brands to drive discovery, visibility and share of voice. This includes building advertiser controls, shopper experiences, monetization strategies and optimization features. We succeed when (1) shoppers discover, engage and build affinity with brands and (2) brands can grow their business at scale with our advertising products. About This Role: As an Applied Scientist on our team, you will: * Develop AI solutions for advertiser and shopper experiences. Build monetization and optimization systems that leverage generative models to value and improve campaign performance. * Define a long-term science vision and roadmap for our Brand Beacon 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. * Design and conduct A/B experiments to evaluate proposed solutions based on in-depth data analyses. * Effectively communicate technical and non-technical ideas with teammates and stakeholders; * Stay up-to-date with advancements and the latest modeling techniques in the field. * 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. #GenAI

The AWS Marketplace Science team seeks a talented Applied Scientist. AWS Marketplace is one of the world's largest B2B software and service discovery platforms, generating rich multi-modal signals that create uniquely challenging problems at the intersection of large-scale information retrieval, generative AI, and agentic systems. You'll operate at the frontier of applied science where your models directly shape purchasing decisions for the world's largest cloud ecosystem. The ideal candidate excels in translating complex scientific research into practical, high-impact solutions, demonstrating both technical excellence and a deep understanding of customer needs. They should bring proven depth in numerous domains across information retrieval, recommendations, and agentic systems while remaining committed to mentoring others and fostering a culture of innovation and collaboration. The position offers a unique opportunity to influence how businesses worldwide discover and adopt software solutions. Key job responsibilities - Lead the research, design, and development of advanced AI/ML systems for information retrieval and agentic systems - Identify and evaluate emerging scientific techniques and technologies, translating research into practical, scalable solutions - Drive evaluation and hypothesis testing to continuously improve performance and relevance of search and recommendation systems - Collaborate with cross-functional teams, such as Product and Engineering leaders, to translate scientific innovations into customer value - Mentor Scientists and influence scientific approach across the organization About the team Mentorship and Career Growth We invest in your growth as a scientist. You'll collaborate closely with a community of applied scientists and research engineers tackling problems across search, recommendations, and generative AI. We support conference attendance and publication at top venues (NeurIPS, ICML, KDD, SIGIR), provide mentorship from senior scientists, and encourage the open exchange of ideas through internal science reading groups and seminars. Whether you want to deepen your technical expertise or grow into science leadership, we'll help you build a career defined by scientific impact. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences, inspire us to never stop embracing our uniqueness.

Do you want a role with deep meaning and the ability to make a major impact? As part of Intelligent Talent Acquisition (ITA), you'll have the opportunity to reinvent the hiring process and deliver unprecedented scale, sophistication, and accuracy for Amazon Talent Acquisition operations. ITA is an industry-leading people science and technology organization made up of scientists, engineers, analysts, product professionals and more, all with the shared goal of connecting the right people to the right jobs in a way that is fair and precise. Last year we delivered over 6 million online candidate assessments, and helped Amazon deliver billions of packages around the world by making it possible to hire hundreds of thousands of workers in the right quantity, at the right location and at exactly the right time. You’ll work on state-of-the-art research, advanced software tools, new AI systems, and machine learning algorithms, leveraging Amazon's in-house tech stack to bring innovative solutions to life. Join ITA in using technologies to transform the hiring landscape and make a meaningful difference in people's lives. Together, we can solve the world's toughest hiring problems. Key job responsibilities The Applied Scientist serves as key contributor supporting recruiting program managers, recruiters, and AUTA leadership while providing technical guidance to demand planning, school strategy, and supply forecasting teams. • Own science models that power target school recommendations, talent supply projections, and school-to-requisition matching across Amazon's global campus recruiting footprint. • Create data-driven models that optimize school sourcing strategies and recruiter decision-making while considering diversity requirements, data privacy thresholds, and institution-specific characteristics. • Develop and maintain supply forecasting models, school ranking algorithms, and multi-objective optimization systems using time-series forecasting, machine learning, survival analysis, and causal inference techniques. • Lead development of AI systems to automate school identification, supply-demand gap analysis, and strategy recommendations while ensuring transparency and alignment with recruiting objectives. • Plan and implement controlled experiments to test new recommendation mechanisms, validate supply projection accuracy, and optimize school engagement strategies across different markets and role families. • Partner with recruiting program managers, recruiters, and downstream engineering teams to translate ambiguous talent supply challenges into well-defined scientific formulations with measurable outcomes. About the team Our team focuses on understanding and improving the experience of both job seekers and the recruiters who support them. You'll be at the intersection of people, data, and technology—solving fascinating problems that directly impact how we hire the best talent globally.

Do you want to join an innovative team of scientists who use machine learning and statistical techniques to help Amazon provide the best customer experience by preventing eCommerce fraud? Are you excited by the prospect of analyzing and modeling terabytes of data and creating state-of-the-art algorithms to solve real world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you enjoy collaborating in a diverse team environment? If yes, then you may be a great fit to join the Amazon Selling Partner Trust & Store Integrity Science Team. We are looking for a talented scientist who is passionate to build advanced machine learning systems that help manage the safety of millions of transactions every day and scale up our operation with automation. Key job responsibilities Innovate with the latest GenAI/LLM/VLM technology to build highly automated solutions for efficient risk evaluation and automated operations Design, develop and deploy end-to-end machine learning solutions in the Amazon production environment to create impactful business value Learn, explore and experiment with the latest machine learning advancements to create the best customer experience A day in the life You will be working within a dynamic, diverse, and supportive group of scientists who share your passion for innovation and excellence. You'll be working closely with business partners and engineering teams to create end-to-end scalable machine learning solutions that address real-world problems. You will build scalable, efficient, and automated processes for large-scale data analyses, model development, model validation, and model implementation. You will also be providing clear and compelling reports for your solutions and contributing to the ongoing innovation and knowledge-sharing that are central to the team's success.