Careers

Payroll Tech's Sheriff team develops and maintains ML and Generative AI applications that support Payroll Operations and Amazon employees at scale. Our portfolio includes Pay-Input Anomaly Detection, which improves the pay experience by identifying pay input irregularities such as leaves and insurance discrepancies; Percept, which improves ticket resolution by providing intelligent ticket prioritization via sentiment scoring, ticket summarization, defect classification, and categorization; Penny, a Virtual Assistant that enables payroll operations teams to efficiently retrieve information from multiple sources including policies, Percept data, vendor data, and HR data via Xylem through a single browser interface; Pay Ticket Genie, in process of being integrated with Amazon AZA(A to Z Assistant); Niyam, our rule engine; and Policy as Code Extraction (PoCo), a critical component of SPACE (Single Payroll Autonomous and Computation Engine) Amazon's in-house payroll system built to eliminate third-party vendor dependency for payroll processing. PoCo ensures data accuracy by validating that pay instructions are correct and performing calculations when required. It consists of two components: policy-based rule creation, where business owners select a pay code and provide policy links to generate rules for specific business processes, and rule evaluation, where upstream services send real-time validation or calculation requests and receive results along with rationale for any failures. Sheriff team owns policy-based rule creation and powering the rule evaluation system with rules generated. As an Applied Scientist on the Sheriff team, you will own and advance the ML and GenAI capabilities that power these systems: driving model accuracy, scientific innovation, and global scale across the payroll ecosystem. Key Job Responsibilities As an Applied Scientist on the Sheriff team, you will operate across three core dimensions: Invent, Implement, and Influence. Invent You bring deep domain knowledge and fluency with state-of-the-art scientific approaches as well as emerging technologies from the research community. You practice customer-obsessed science : working backwards from the needs of Amazon employees and payroll operations teams to extend or invent new ML approaches, even when no textbook solution exists. You design novel ML and LLM-based methodologies for anomaly detection, sentiment analysis, ticket classification, prescriptive analysis, intelligent virtual assistance, and automated policy extraction. You identify and define the research agenda for expanding Percept's capabilities including prescriptive analysis feature; lead the scientific strategy for the Penny-AZA integration enabling accurate and low-latency responses to Amazon employee payroll queries, and drive the ML strategy for Policy as Code extraction(PoCo), developing models that extract, interpret, and codify payroll policies into structured, executable rules that power real-time pay instruction validation and calculation within SPACE. You author or co-author articles for internal or external peer-reviewed venues that validate the novelty of your work, when appropriate and not precluded by business considerations. Implement The ML components you develop are directly integrated into production systems or directly support large-scale applications serving Amazon's global payroll operations. You make appropriate tradeoffs between model accuracy and latency, innovation and stability, and immediate versus long-term solutions; favoring reuse and established frameworks where appropriate. You make progress semi-autonomously with only occasional guidance, implement at the correct level of complexity the first time, and evaluate emerging technologies including Large Language Models (LLMs) and GenAI frameworks largely on your own. You ensure your models and pipelines integrate robustly with data sources including USC (Unified Central Service), Xylem, SIM-Ticketing, Pay Code Governance system, and PoCo's rule evaluation engine. Influence You contribute to tactical and strategic planning for the Sheriff team, including goals, priorities, and roadmaps for ML and GenAI capabilities. You lead the scientific strategy for the global expansion of Percept, driving both feature growth and country-level launches own the complex AI track for Penny-AZA integration collaborating across partner teams including Reflect and GREF to ensure seamless data integration and robust ML pipeline workflows, and drive the scientific roadmap for PoCo's expansion to 100K US employees, ensuring the ML models powering policy extraction, rule generation and testing scale reliably to meet this growth. You mentor scientists and engineers on the team and across teams, championing best practices for the AI-Driven Development Life Cycle (AIDLC) to rapidly increase developer productivity and delivery velocity. You provide peer feedback on research procedures and results within and across teams, help recruit and develop bar-raising talent through interview drives, and grow the team's organizational knowledge of Sheriff team ML solutions. You are visible in the broader internal and external scientific communities as a subject matter expert and regularly serve as a Program Committee (PC) member at peer-reviewed conferences or review articles for journal publications.

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. ITA stands at a critical juncture where our growth trajectory demands sophisticated analytical capabilities to revolutionize our hiring processes while raising the bar of candidates we hire. We are seeking an L5 Data Scientist to spearhead the next generation of Amazon's hiring practices through advanced scientific methods, focusing on two crucial domains - System Health Monitoring (SHM) and Select In for optimizing candidate quality .The role will be instrumental in driving a projected 60% reduction in defect detection time and contributing to ITA's ambitious 15% efficiency gain with Gen AI based workflow transformation target for 2026. The position will be pivotal in transforming our flagship recruiting system monitoring and extending sophisticated anomaly detection solutions across corporate hiring. By implementing advanced anomaly detection and root cause analysis, this role will directly impact our ability to provide reliable insights to talent acquisition customers while optimizing quality of hire. The role will be leading development of simulation models to identify how to attract and select in talent raising the bar of candidate quality in Amazon. The role will be directly responsible to The integration of cutting-edge Gen AI tools and multi-agent systems will revolutionize our scientific workflows, positioning ITA at the forefront of technological innovation in hiring practices. The criticality of this Data Scientist role cannot be overstated- Without this position, ITA cannot advance its primary objective of enhanced candidate evaluation, risking system downtime across four critical platforms, compromising candidate quality standards, and directly impacting Amazon's Quality of Hire strategy. Key job responsibilities The DS will be : 1. Partnering with senior DS and Applied scientists to identify customer pain points and transform them to measurable goals 2. Iterate rapidly prototypes on anomaly detection, agent based root cause analysis on anomalies detected using scientific approaches 3. Deploy scalable ML/science based models using AWS infrastructure 4. Identifying proactively areas of high value repeated work /product opportunities as candidates for automation using Gen AI 5. Design and run experiments on systems stability pre and post interventions 6. Follow agile workflow for daily project execution 7. Develop in partnership with economists and other DS an integrated framework for developing strategies that attract top tier talent for Amazon.

Amazon Health Services (One Medical) About Us: At Health AI, we're revolutionizing healthcare delivery through innovative AI-enabled solutions. As part of Amazon Health Services and One Medical, we're on a mission to make quality healthcare more accessible while improving patient outcomes. Our work directly impacts millions of lives by empowering patients and enabling healthcare providers to deliver more meaningful care. Role Overview: We're seeking an Applied Scientist to join our dynamic team in building state of the art AI/ML solutions for healthcare. This role offers a unique opportunity to work at the intersection of artificial intelligence and healthcare, developing solutions that will shape the future of medical services delivery. Key job responsibilities • Lead end-to-end development of AI/ML solutions for Amazon Health organization, including Amazon Pharmacy and One Medical • Research, design, and implement state-of-the-art machine learning models, with a focus on Large Language Models (LLMs) and Visual Language Models (VLMs) • Optimize and fine-tune models for production deployment, including model distillation for improved latency • Drive scientific innovation while maintaining a strong focus on practical business outcomes • Collaborate with cross-functional teams to translate complex technical solutions into tangible customer benefits • Contribute to the broader Amazon Health scientific community and help shape our technical roadmap

Have you ever wondered how Amazon launches and maintains a consistent customer experience across hundreds of countries and languages it serves its customers? Are you passionate about data and mathematics, and hope to impact the experience of millions of customers? Are you obsessed with designing simple algorithmic solutions to very challenging problems? If so, we look forward to hearing from you! At Amazon, we strive to be Earth's most customer-centric company, where both internal and external customers can find and discover anything they want in their own language of preference. Our Translations Services (TS) team plays a pivotal role in expanding the reach of our marketplace worldwide and enables thousands of developers and other stakeholders (Product Managers, Program Managers, Linguists) in developing locale specific solutions. Amazon Translations Services (TS) is seeking an Applied Scientist to be based in our Seattle office. As a key member of the Science and Engineering team of TS, this person will be responsible for designing algorithmic solutions based on data and mathematics for translating billions of words annually across 130+ and expanding set of locales. The successful applicant will ensure that there is minimal human touch involved in any language translation and accurate translated text is available to our worldwide customers in a streamlined and optimized manner. With access to vast amounts of data, State-of-the-art 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. Together, we will drive innovation, solve complex problems, and shape the future of e-commerce. Key job responsibilities * Apply your expertise in LLM models to design, develop, and implement scalable machine learning solutions that address complex language translation-related challenges in the eCommerce space. * Collaborate with cross-functional teams, including software engineers, data scientists, and product managers, to define project requirements, establish success metrics, and deliver high-quality solutions. * Conduct thorough data analysis to gain insights, identify patterns, and drive actionable recommendations that enhance seller performance and customer experiences across various international marketplaces. * Continuously explore and evaluate state-of-the-art modeling techniques and methodologies to improve the accuracy and efficiency of language translation-related systems. * Communicate complex technical concepts effectively to both technical and non-technical stakeholders, providing clear explanations and guidance on proposed solutions and their potential impact. About the team We are a start-up mindset team. As the long-term technical strategy is still taking shape, there is a lot of opportunity for this fresh Science team to innovate by leveraging Gen AI technoligies to build scalable solutions from scratch. Our Vision: Language will not stand in the way of anyone on earth using Amazon products and services. Our Mission: We are the enablers and guardians of translation for Amazon's customers. We do this by offering hands-off-the-wheel service to all Amazon teams, optimizing translation quality and speed at the lowest cost possible.

Amazon Advertising is one of Amazon's fastest growing businesses. Amazon's advertising portfolio helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day! The Creative X team within Amazon Advertising time aims to democratize access to high-quality creatives (images, videos) by building AI-driven solutions for advertisers. To accomplish this, we are investing in latent-diffusion models, large language models (LLM), computer vision (CV), reinforced learning (RL), and image + video and audio synthesis. We are looking for a talented Applied Science Manager who can help set the scientific agenda and provide best in class mentoring within the scope of advancing advertiser-facing generative AI. You will help lead scientists within a close-knit team who is highly collaborative and at the top of their respective fields. Our science team is adept at a variety of skills, especially with agentic AI, generative multi-modal models, LLMs, computer vision, latent diffusion and related foundational models. As a Science Manager you will: * Help set the scientific agenda in collaboration with org's leadership, product managers, engineering and relevant stakeholders. * You will guide the team to be world-class at developing large scale generative AI for advertising. * Help mentor scientists towards also contributing with patent submissions, potential peer-reviewed research publications and bar raising hiring. * Contribute and help establish mechanisms for science management, brainstorming, monitoring and validation of outputs. * Hire and develop the best science talent at Amazon. * Present strategy, methods and results to senior leadership. Why you will love this opportunity Amazon is investing heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative team with an entrepreneurial spirit - with a broad mandate to experiment and innovate. Key job responsibilities *Manage and lead science and AI software (/MLE) engineering talent to deliver world-class innovative generative AI for advertising. * Help set the scientific agenda in collaboration with org's leadership, product managers, engineering and relevant stakeholders. * Help mentor scientists & AI software talent towards contributing with patent submissions, potential peer-reviewed research publications and bar raising mentoring and hiring. * Contribute and help establish mechanisms for science and technical management, brainstorming, monitoring and validation of outputs. * Hire and develop the best technical talent at Amazon. * Write strategy and alignment documents for partners within and outside the org. * Present strategy, methods and results to senior leadership. A day in the life On a day-to-day basis, you will lead and mentor technical talent, engage and align with product, engineering and other stakeholders, dive deep on advertiser anecdotes and make sure that what the team delivers and is working on aligns with those needs and best practices. You will define and deliver mechanisms to create innovation at scale and engage with senior leadership to align on priorities and opportunities. About the team The team consists of applied scientists and AI software/machine learning engineers. We reside in the Creative X organization, which focuses on creating products for advertisers that will improve the quality of the creatives within Amazon Ads.

We are looking for a Senior Applied Scientist to join the Robotics Simulation team at Amazon Robotics. This role combines deep traditional robotics expertise (kinematics, dynamics, control, motion planning) with fluency in modern Physical AI approaches (imitation learning, vision-language-action models, world models, diffusion policies). You will be the technical anchor who bridges the gap between what works in simulation and what works on real robots. You will mentor junior scientists building RL and imitation learning pipelines, provide hands-on technical direction on sim-to-real transfer, foresee pitfalls in robot learning workflows before they become blockers, and drive the robotics development methodology for the team. This is not a pure research role: you will work directly with real robot hardware, simulation environments, and production deployment pipelines, ensuring that learned policies transfer reliably from GPU-accelerated simulation to physical robots operating in Amazon fulfillment centers. While this role is expected to engage with the research community and may produce publications, the primary measure of success is deployed robot capability, not paper count. We value scientists who ship. Key job responsibilities * Provide technical robotics direction for the team's Physical AI program, spanning simulation environment design, policy training, sim-to-real transfer, and real-world validation across multiple robotics platforms. * Mentor junior applied scientists and engineers on robot learning best practices, helping them diagnose sim-to-real gaps, debug policy failures on hardware, and iterate toward deployable solutions. * Design and execute sim-to-real transfer strategies, including system identification, domain randomization, physics parameter tuning, and visual domain adaptation, drawing on both classical and learned approaches. * Architect policy training pipelines that combine teleoperation data, synthetic demonstrations, reinforcement learning, and imitation learning (e.g., VLA models, diffusion policies, behavior cloning) for manipulation tasks. * Lead sim-to-real analysis: define metrics and methodologies for evaluating simulation fidelity, identifying where simulation diverges from reality, and prioritizing modeling improvements that impact downstream policy performance. * Collaborate with hardware teams on robot embodiment modeling, ensuring that digital twins accurately capture kinematics, joint dynamics, actuator limits, contact behavior, and sensor characteristics. * Evaluate and integrate state-of-the-art approaches from the Physical AI research community (foundation models for robotics, world models, action-chunking transformers, generalist policies) into the team's simulation and training infrastructure. * Contribute to end-effector modeling and physics tuning, ensuring physically plausible contact interactions and accurate tool behavior in simulation across diverse manipulation hardware. * Drive technical design reviews, author high-level design documents, and set the scientific direction for simulation fidelity and robot learning initiatives. 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 ~30-person 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 infrastructure enables robots to be designed, trained, and validated entirely in simulation before physical hardware exists, compressing development timelines and de-risking hardware programs across Amazon Robotics. The team currently 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, VLA/diffusion policy training and inference pipelines, domain randomization for visual and physics sim-to-real transfer, and model validation in simulation. We partner closely with hardware teams, science organizations, and robotics program leads across Amazon Robotics. This role reports into the Robotics Simulation organization and carries technical influence across broader partner teams (hardware engineering, science organizations, robotics program leads). You will not only shape direction within the simulation team but serve as the technical bridge connecting simulation fidelity decisions to real-world robot performance across multiple programs.

Economists on the Seller Fee Science team design scalable strategies and technology for the fees Amazon charges to third-party sellers, world wide. Our challenge is to facilitate continued improvement in both customer experience (selection, prices, delivery speed) and selling partner growth and innovation, while optimizing for Amazon's long-term profits. Key job responsibilities Design and develop models to assess the causal impact of fees, and fee-related policy on third party sellers’ behavior and business performance. Lead enhancements into existing fee calculation models to maximize the long term health of the Amazon third-party marketplace. Own the scientific vision and direction related to fees worldwide. Collaborate with product managers, data scientists, and software developers to incorporate models into production processes and influence senior leaders. Act as an ambassador of our team in the broader scientific community.

Are you a MS or PhD student interested in a 2024 Applied Science Internship in the fields of Speech, Robotics, Computer Vision, or Machine Learning/Deep Learning? Do you enjoy diving deep into hard technical problems and coming up with solutions that enable successful products that improve the lives of people in a meaningful way? If this describes you, come join our research teams at Amazon. 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.

Amazon's Compliance and Safety Services (CoSS) Team is looking for a smart and creative Applied Scientist to apply and extend state-of-the-art research in NLP, multi-modal modeling, domain adaptation, continuous learning and large language model to join the Applied Science team. At Amazon, we are working to be the most customer-centric company on earth. Millions of customers trust us to ensure a safe shopping experience. This is an exciting and challenging position to drive research that will shape new ML solutions for product compliance and safety around the globe in order to achieve best-in-class, company-wide standards around product assurance. You will research on large amounts of tabular, textual, and product image data from product detail pages, selling partner details and customer feedback, evaluate state-of-the-art algorithms and frameworks, and develop new algorithms to improve safety and compliance mechanisms. You will partner with engineers, technical program managers and product managers to design new ML solutions implemented across the entire Amazon product catalog. Key job responsibilities As an Applied Scientist on our team, you will: - Research and Evaluate state-of-the-art algorithms in NLP, multi-modal modeling, domain adaptation, continuous learning and large language model. - Design new algorithms that improve on the state-of-the-art to drive business impact, such as synthetic data generation, active learning, grounding LLMs for business use cases - Design and plan collection of new labels and audit mechanisms to develop better approaches that will further improve product assurance and customer trust. - Analyze and convey results to stakeholders and contribute to the research and product roadmap. - Collaborate with other scientists, engineers, product managers, and business teams to creatively solve problems, measure and estimate risks, and constructively critique peer research - Consult with engineering teams to design data and modeling pipelines which successfully interface with new and existing software - Publish research publications at internal and external venues. About the team The science team delivers custom state-of-the-art algorithms for image and document understanding. The team specializes in developing machine learning solutions to advance compliance capabilities. Their research contributions span multiple domains including multi-modal modeling, unstructured data matching, text extraction from visual documents, and anomaly detection, with findings regularly published in academic venues.

Have you ever wanted to solve a mystery or be part of solving a case? Are you fascinated by detective stories or crime shows on TV? Do you love to catch bad actors, build ML models and solve complex problems. If so, working on the WWOS Tech team as a Sr Applied Scientist is the place for you! We detect theft, fraud and organized crime happening across our global supply chain and operations for millions of items, for hundreds of product lines worth billions of dollars of inventory world-wide. We foster new game-changing ideas, creating ever more intelligent and self-learning systems to maximize the cost savings of Amazon's inventory losses. The primary role of a Sr Applied 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 all the fraud investigations happening across Amazon operations. Ideal candidates will be a high potential, strategic and analytic graduate with a PhD in ( 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 building fraud detections, detecting organized crime and the ability to use data and research to make changes. 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. Key job responsibilities - Own KPIs that measure theft/fraud management performance and efficiencies. - Detect and automate theft, fraud MOs - Detect organized crime rings and bad actor clusters - Perform end to end evaluation of operational defects, system gaps, and scaling challenges (both system and operational). - Contribute to the overall fraud management and product development strategies. - Present key learnings and vision to stakeholders and leadership. - Integrate ML detection models via software applications About the team We believe that building a culture that is welcoming and inclusive is integral to people doing their best work and is essential to what we can achieve as a company. We actively recruit people from diverse backgrounds to build a supportive and inclusive workplace. Our team puts a high value on work-live balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment.