Careers

Are you passionate about working with Amazon-scale data, advanced analytics, and data science? Do you love bringing data together from diverse systems and sources and working on innovative advanced analytics problems for creating deep understanding of customer behavior and generating actionable business insights? Does the idea of working closely with a team of highly experience machine-learning scientists and engineers excite you? We looking for an experienced, self-driven Data Scientist to help us synthesise data into knowledge for our Kindle Direct Publishing business. If you like working with data and want to harness the power of it to develop a deeper understanding of customer behaviour, identify opportunities, impact publishing workflow and influence the business strategy to develop products and features that have a direct impact on the creator and reader experience, this is the role for you! Key job responsibilities As Data Scientist, you will connect with world leaders in your field working on similar problems. You will be working with massive-scale data and providing analytic leadership to scientists, product managers, engineers using these data. You will leverage your knowledge in machine learning, advanced analytics, metrics, reporting, and analytic tooling/languages to analyze and translate the data into meaningful insights. You will closely collaborate with business, scientists, and engineers. You will have end-to-end ownership of operational and technical aspects of the insights you are building for the business, and will play an integral role in strategic decision-making. Further, you will build solutions leveraging advanced analytics that enable stakeholders to manage the business and make effective decisions, partner with internal teams to identify process and system improvement opportunities. About the team Minerva is a cross-functional science, analytics, and ML org of highly experienced scientists, BI/data engineers, and software engineers with a critical business mission making revolutionary leaps forward using massive-scale data with advanced analytics and machine learning and helping democratize the publishing industry. We build science-based systems for marketing and content-discovery for indie authors, fraud/abuse, and content risk for our publishing businesses. We also use science to optimize manufacturing, fulfillment, and quality processes.

We are seeking Applied and Research Scientists to join the Safe Autonomy Frontiers (SAF) Lab. In this role, you will develop and deploy the science of safe autonomy on highly dynamic robots, advancing the frontier through both foundational research and realization on hardware. You will contribute to achieving safe autonomy across three key areas: control barrier function (CBF) theory for robust and performant safety on hardware; safe reinforcement learning for agile whole-body control; and layered safety filters that interface with learning, perception, and semantic reasoning systems. You will validate your work experimentally on state-of-the-art robotic platforms — removing bottlenecks to deployment and enabling robots to safely operate around humans. You will work with the inventor of CBFs, as well as top scientists and engineers at Amazon developing the next generation of safe autonomy. Key job responsibilities -Advance the science of safe autonomy from formal foundations to the integration with learning and perception to validation on hardware — with particular emphasis on methods that bridge these domains. -Test and validate hardware, with a focus on next generation robotic systems. Including locomotion, manipulation and loco-manipulation. -Leverage the deployments on hardware to validate the underlying science, identifying gaps between theory and practice that drive the next cycle of research. hardware to validate the underlying science, identifying gaps between theory and practice that drive the next cycle of research. -Publish research at top-tier robotics, control, and ML venues, and contribute to Amazon’s scientific reputation in advanced robotics. -Collaborate with SAF Lab and Amazon production teams to move research into robots deployed at Amazon scale. 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: -Medical, Dental, and Vision Coverage -Maternity and Parental Leave Options -Paid Time Off (PTO) -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 Safe Autonomy Frontiers (SAF) Lab is the first industry research lab dedicated to safe autonomy, founded by the inventor of control barrier functions. We are developing a universal safety layer for the next generation of robotic systems: mobile robots, manipulators, quadrupeds, and humanoids. Here you will advance performant safety for highly dynamic robots — CBF theory integrated with perception and learning, evaluated on next-generation platforms — and your work will underpin robots operating alongside people at Amazon’s unprecedented scale.

We're building systems that turn research into real-world impact — developing AI-driven detection systems that identify and remediate security access violations across Amazon's global operations, and building ML solutions that leverage product images, text, and tabular data to improve safety and compliance mechanisms across Amazon's entire product catalog. If this sounds interesting to you then we have a range of opportunities for you to explore. We're looking for PhD students across multiple research domains to invent, design, and implement state-of-the-art solutions for never-before-solved problems. Your work here won't just stay in a notebook — it ships to production and reaches customers worldwide. Check out the details below including the job responsibilities, team details, and basic qualifications before submitting your application. You can find more information about the Amazon Science community as well as interview preparation tips via the links below; - https://www.amazon.science/ - https://amazon.jobs/content/en/career-programs/university/science - https://amazon.jobs/content/en/how-we-hire/university-roles/applied-science Key job responsibilities As an Applied Science Intern, you will own the design and development of end-to-end systems. You'll have the opportunity to write technical white papers, create roadmaps and drive production level projects that will support Amazon Science. You will work closely with Amazon scientists and other science interns to develop solutions and deploy them into production. You will have the opportunity to design new algorithms, models, or other technical solutions whilst experiencing Amazon's customer focused culture. The ideal intern should have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. A day in the life You'll spend your first weeks scoping your project with your mentor, then own the research and implementation end-to-end. Your work could involve building graph-based ML models and knowledge graphs that detect and remediate access violations at global scale, developing behavioral pattern clustering and automated reasoning systems for security operations, or researching multimodal and computer vision approaches on product catalog data to improve safety and compliance mechanisms — depending on the team you're matched with. Many interns publish at top-tier conferences or see their work deployed to production before the internship ends. Interns may also be considered for a return offer at the end of their internship, subject to performance evaluation and headcount availability. Further benefits of an Amazon Science internship include; - All of our internships offer a competitive salary - Interns are paired with an experienced manager and mentor(s) - Interns get invited to different intern program or office events - Interns can build their professional and personal network with other Amazon Scientists - Interns can potentially publish work at top tier conferences About the team We generally hire interns for multiple teams in Romania, including but not limited to; • CoSS — Research and develop ML solutions that improve safety and compliance across Amazon's entire product catalog working with tabular, textual, and product image data using deep learning, computer vision, LLMs, and multimodal models • Monitored Access Detection — Build AI-driven detection and remediation systems that identify global access violations across Amazon — leveraging knowledge graphs, graph modeling, behavioral pattern clustering, generative AI, and reinforcement learning to create a self-improving, closed-loop security system. You'll submit a single application and we'll match you with science teams best aligned with your research interests. Applications are reviewed on a rolling basis, and your application stays active until we find a team match or confirm there are no matches available. Start dates are available throughout the year for durations of between 3–6 months. Please note, each team has different start date and duration preferences — your recruiter will confirm the preferences of the team you're matched with prior to interviewing. We offer science internships in multiple locations across the EMEA region and you can indicate your interest in all these locations by applying here (Austria, Estonia, France, Germany, Ireland, Israel, Italy, Jordan, Luxembourg, Netherlands, Poland, Romania, South Africa, Spain, Sweden, UAE, and UK). Please note we do not offer remote internships.

We're building systems that turn research into real-world impact — powering sports experiences for millions of Prime Video customers, pioneering multimodal document intelligence, building autonomous AI agents that reason, plan, and act, and transforming how customers discover products they love. If this sounds interesting to you then we have a range of opportunities for you to explore. We're looking for Masters students across multiple research domains to invent, design, and implement state-of-the-art solutions for never-before-solved problems. Your work here won't just stay in a notebook — it ships to production and reaches customers worldwide. Check out the details below including the job responsibilities, team details, and basic qualifications before submitting your application. You can find more information about the Amazon Science community as well as interview preparation tips via the links below; - https://www.amazon.science/ - https://amazon.jobs/content/en/career-programs/university/science - https://amazon.jobs/content/en/how-we-hire/university-roles/applied-science Key job responsibilities As an Applied Science Intern, you will own the design and development of end-to-end systems. You'll have the opportunity to write technical white papers, create roadmaps and drive production level projects that will support Amazon Science. You will work closely with Amazon scientists and other science interns to develop solutions and deploy them into production. You will have the opportunity to design new algorithms, models, or other technical solutions whilst experiencing Amazon's customer focused culture. The ideal intern should have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. A day in the life You'll spend your first weeks scoping your project with your mentor, then own the research and implementation end-to-end. Your work could involve building computer vision models that power live sports experiences for Prime Video, developing multimodal GenAI solutions for AWS document intelligence, creating agentic AI systems that reason and act autonomously, or advancing recommendation models that transform how customers discover content — depending on the team you're matched with. Many interns publish at top-tier conferences or see their work deployed to production before the internship ends. Interns may also be considered for a return offer at the end of their internship, subject to performance evaluation and headcount availability. Further benefits of an Amazon Science internship include; - All of our internships offer a competitive salary - Interns are paired with an experienced manager and mentor(s) - Interns get invited to different intern program or office events - Interns can build their professional and personal network with other Amazon Scientists About the team We're hiring interns for multiple teams in Israel, including but not limited to; • Prime Video Sports — Build innovative sports experiences for Prime Video, spanning computer vision, 3D simulation, and personalized content recommendations. • Personalization — Leverage LLMs, NLP, and recommender systems to match customers with products that align with their passions and shopping preferences. • Agentic AI — Build next-generation agentic AI systems that automate real-world knowledge work, spanning retrieval-augmented generation, multi-agent workflows, long-term memory and personalization, knowledge-graph construction, and agent evaluation. • DS3 Textract — Develop multimodal generative AI algorithms that pioneer state-of-the-art document understanding solutions impacting millions of customers. You'll submit a single application and we'll match you with science teams best aligned with your research interests. Applications are reviewed on a rolling basis, and your application stays active until we find a team match or confirm there are no matches available. Start dates are available throughout the year. Some teams offer full-time internships (3–6 months) while others offer part-time positions (50–60%, 8–12 months) — your recruiter will confirm the format during team matching. We offer science internships in multiple locations across the EMEA region and you can indicate your interest in all these locations by applying here (Austria, Estonia, France, Germany, Ireland, Israel, Italy, Jordan, Luxembourg, Netherlands, Poland, Romania, South Africa, Spain, Sweden, UAE, and UK). Please note we do not offer remote internships.

We are seeking a Robotics/AI Motor Control Scientist to develop cutting-edge machine learning algorithms for motor control systems in robots. In this role, you will focus on creating and optimizing intelligent motor control strategies to enable robots to perform complex, whole-body tasks. Your contributions will be essential in advancing robotics by enabling fluid, reliable, and safe interactions between robots and their environments. Key job responsibilities - Develop controllers that leverage reinforcement learning, imitation learning, or other advanced AI techniques to achieve natural, robust, and adaptive motor behaviors - Collaborate with multi-disciplinary teams to integrate motor control systems with robotic hardware, ensuring alignment with real-world constraints such as actuator dynamics and energy efficiency - Use simulation and real-world testing to refine and validate control algorithms - Stay updated on advancements in robotics, AI, and control systems to apply advanced techniques to robotic motion challenges - Lead technical projects from conception through production deployment - Mentor junior scientists and engineers - Bridge research initiatives with practical engineering implementation About the team Fauna Robotics, an Amazon company, is building capable, safe, and genuinely delightful robots for everyday life. Our goal is simple: make robots people actually want to live and interact with in everyday human spaces. We believe that future won’t arrive until building for robotics becomes far more accessible. Today, too much effort is spent reinventing the fundamentals. We’re changing that by developing tightly integrated hardware and software systems that make it faster, safer, and more intuitive to create real-world robotic products. Our work spans the full stack: mechanical design, control systems, dynamic modeling, and intelligent software. The focus is not just functionality, but experience. We’re building robots that feel responsive, expressive, and genuinely useful. At Fauna, you’ll work at the frontier of this space, helping define how robots move, manipulate, and interact with people in natural environments. It’s an opportunity to solve hard problems across hardware and software with a team focused on making robotics accessible and joyful to build. If you care about making robotics real for everyone and building systems that are as delightful as they are capable, we’re interested in hearing from you. an opportunity to solve hard problems across hardware and software with a team focused on making robotics accessible and joyful to build. If you care about making robotics real for everyone and building systems that are as delightful as they are capable, we’re interested in hearing from you.

We are looking for Applied Scientists to advance how Minerva detects and responds to risk across KDP and Kindle Unlimited, building new models and raising the bar on the ones in production. You will own a problem end to end, from framing and modeling through evaluation and production launch, working with scientists and engineers in Bengaluru and the US. Key job responsibilities - Monitor production risk models and push their quality higher: track performance and drift, improve how performance is measured, and lead the deep-dive science that turns model behavior into better detection. - Design, train, and evaluate improved detection models, and take them to production with engineering partners. - Build datasets, labels, evaluation sets, and metrics, and strengthen them as abuse patterns change. - Write clear readouts with recommendations for scientists, engineers, and policy partners. About the team Kindle Direct Publishing (KDP) has empowered a new wave of self-motivated creators, tearing down barriers that once blocked writers from reaching readers. Minerva is the science and analytics organization for Amazon's Books business. We build systems for content understanding, author marketing and discovery, fraud and abuse prevention, and content risk, and we optimize manufacturing, fulfillment, and quality for Print On Demand (POD). We have mature areas and green-field opportunities, with engineering, business intelligence, and data engineering support across our areas. We are now building science teams in Bengaluru that work closely with our scientists in the US. Risk Science, a team within Minerva, keeps fraud, abuse, copyright infringement, and harmful content out of the Books catalog and programs such as Kindle Unlimited, using text, image, and behavioral data.

We’re working to improve shopping on Amazon using the conversational capabilities of large language models, and are searching for pioneers who are passionate about technology, innovation, and customer experience, and are ready to make a lasting impact on the industry. In this role, you will be managing a team working on Large Language Model (LLM) and/or Vision-Language Model (VLM) post-training and alignment for new shopping experiences. You’ll be working with talented scientists, engineers, and technical program managers (TPM) to innovate on behalf of our customers. If you’re fired up about being part of a dynamic, driven team, then this is your moment to join us on this exciting journey!

We are looking for a Principal Applied Scientist to drive the research and development of real-time multimodal conversational AI. You will operate across two focus areas: advancing foundation models for speech and audio, and building the post-training systems (reward modeling, reinforcement learning) that shape natural, human-like conversational behavior. You will be the expert in your area while contributing across the full model lifecycle — from pre-training and architecture design through post-training alignment and real-time deployment. You will work at the frontier of what's possible in conversational AI, with the compute, data, and runway to pursue problems that few teams in the world have the resources to tackle. As a Principal Scientist, you will set the technical direction for your research area, influence the broader roadmap, and work closely with inference engineers to ensure your models are designed for real-time production deployment from inception. Key job responsibilities Foundation Model Scaling - Build and train large-scale multimodal foundation models for real-time speech and audio generation, from architecture design through production-scale training - Advance the scaling and efficiency of conversational modes, including the relationship between data, model size, and real time performance. - Design model architectures informed by hardware constraints and inference requirements, working with inference engineers to ensure models are servable from inception - Develop training methodologies for multimodal models that jointly process and generate speech, language, and audio in real-time streaming contexts Post-Training & Reinforcement Learning - Design and build reward models and reward functions for speech systems — capturing naturalness, fluency, conversational quality, and real-time responsiveness - Develop and apply reinforcement learning methods to shape conversational behavior — teaching models natural timing, responsiveness, and fluid interaction - Build the post-training pipeline from SFT through RL alignment, optimized for real-time multimodal outputs rather than text-only generation - Design evaluation frameworks that capture the quality dimensions unique to real-time conversation Real-Time Perception & Generation - Advance the team's capabilities in real-time perception - Work at the intersection of model architecture and production constraints to ensure multimodal capabilities function within hard real-time latency budgets About the team We are a small, focused group of scientists and engineers building the next generation of real-time conversational AI at Amazon — models that interact naturally across speech and audio. We operate with the autonomy and pace of a research lab, backed by frontier-scale compute and a multi-year investment horizon.

Are you energized by building technology that makes life easier for business customers? If you enjoy working at the center of enterprise commerce, connecting Amazon Business with the procurement, ERP, and finance systems that organizations run on ethn Amazon Business System (ABS) Integrations team is the place for you. We build systems integrations capabilities that let business customers buy on Amazon Business directly from the systems they already use. This includes APIs, protocols, and partner connections that make procurement faster, more automated, and more reliable at global scale. Our teams design, launch, and operates these integrations with a wide range of partners, and each launch has to work securely and seamlessly across many different systems, regions, and customer needs. We are seeking a Senior Manager Applied Science to build and lead the science organization in Amazon Business Systems Integrations. This is a foundational leadership role spanning the full integrations portfolio. This role will hire, grow, and lead a team of applied scientists who define how we measure and improve the performance of AI agents and human-AI teams. A core part of the role is defining the science agenda itself - identifying which problems are most worth solving and where the highest-leverage bets lie. Directions worth exploring might include Organizational Intelligence (turning institutional knowledge into agent-consumable skills) AI Agent Experience / AiAX (agent observability and autonomous remediation) and contextual behavioral security that adapts enforcement in real time for human and agent sessions and anything which the defines how we measure and improve agents and human-AI teams i.e benchmarks, task suites, and metrics (accuracy cost-per-task task completion productivity) that turn subjective "it works" judgments into rigorous reproducible measurement that gates what we ship. There are no established industry patterns in this field and the team will set the scientific direction, determine how AI agents and people perceive reason and act reliably within computing environments at enterprise scale. This role requires building, leading and retaining a high calibre applied science team spanning the Agentic Integrations portfolio. This leader will set the bar for scientific talent, create the growth paths, and build the culture that makes Amazon Business a destination for the best agent and human-AI researchers. Key job responsibilities • Set the long-term scientific vision and team strategy: Define what best-in-class agent performance evaluation and learning look like across Agentic WorkSpaces - for computer-using agents and human-AI teams alike. Chart a multi-year research roadmap and build the team and plan to deliver it. Secure buy-in from VP-level leadership. • Hire and grow scientific talent: Own recruiting calibration development and retention for the science team. Mentor scientists toward senior and principal scope and raise the scientific bar across the organization. • Direct research on highly ambiguous novel problems: Guide the team through foundational challenges in agent perception reasoning evaluation reliability and human-AI collaboration - problems where neither the approach nor the success criteria are pre-defined. • Drive cross-organizational alignment: Work across partner teams (AgentCore Bedrock model teams Identity Security the MCP ecosystem) and across the Applied AI Solutions product portfolio with product and engineering leadership to ensure scientific decisions compose into a coherent product. • Deliver measurable business impact: Ensure your team's research translates to customer outcomes: higher task accuracy lower cost-per-action faster time-to-production measurable productivity for human-AI teams and the trust that lets enterprises scale agent workflows. • Establish scientific rigor and operational excellence: Set the standard for experimentation evaluation and reproducibility and the mechanisms that keep the science organization productive and accountable. • Advance the state of the art: Enable and champion contributions to the external technical community through publications patents and open-source work that position AWS as the leader in the science of secure agent-computer interaction and human-AI teamwork. • Translate science into shipped product. Partner with engineering, product, and program leaders to move models evaluation and learning systems from prototype into a decade-old production service operating at massive scale without compromising the reliability that customers depend on. • Represent science in leadership and to customers. Be the scientific voice in org-level planning and roadmap decisions across AAWS and engage directly with enterprise customers on how agent performance safety and human-AI productivity are measured and earned.

At Amazon, we are obsessed with customer trust. Amazon Security enables Amazon's business leaders to build and operate securely while protecting the confidentiality and integrity of Amazon and customer data. We assess risk, classify data and systems, detect intrusion, and drive mitigation at scale. Veritas is Amazon's single source of truth for applications and services and the resources that make them up, spanning both Stores/Devices (SDO) and AWS. Security teams across Amazon rely on Veritas to understand attack paths, assign issue ownership, track the flow of sensitive data, and reason about risk across one of the largest and most diverse technology footprints in the world. We are seeking a talented, self-directed Senior Data Scientist to work on cutting-edge security technologies. You will take the lead on large, ambiguous problems that have not been solved before - defining both the problem and the solution approach autonomously. You will design and run experiments, research new algorithms, and find new ways to protect Amazon's customer trust. You will work closely with talented software engineers and security engineers who transform your prototypes and models into production. You should thrive in ambiguous environments and enjoy fast-paced settings where learning new concepts quickly is essential. You leverage exceptional technical expertise, strong statistical skills, and data acumen to analyze large volumes of business data and make Amazon safer. Your strong communication skills enable you to influence across multiple teams and to work effectively with both business and technical partners, including senior leadership. Key job responsibilities - Define problems and solution approaches autonomously in ambiguous, open-ended security problem spaces where no established pattern exists. - Process and analyze large data sets using the full range of techniques required, selecting the ideal method from a wide range of data science disciplines. - Deliver scalable models that analyze large data sets efficiently. - Build mathematical models to detect and classify specific data elements with high accuracy. - Prototype models in high-level modeling languages such as R, or in software languages such as Python. A software team will partner with you to transform prototypes into production. - Take the lead on large projects that require both business and technical domain expertise, delivering significant benefit to the business. - Influence multiple teams and build consensus across business, science, and engineering stakeholders; advise senior managers and directors on data-driven security decisions. - Mentor and develop other scientists; perform data science technical assessments and participate in science and data-engineering code reviews. - Create, enhance, and maintain technical documentation, and present findings to other scientists and business leaders, keeping teams current on relevant scientific advancements.