Careers

The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry leading generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. Key job responsibilities We are looking for an Applied Science Manager to lead the Amazon Sponsored Agent (ASA) team within Sponsored Products and Brands (SPB). ASA is new agentic service that enables publishers and apps to monetize their AI experiences with conversational and agentic ads. This team owns the core ASA platform that serves contextual ads across 1P surfaces (Alexa+, Amazon.com) and 3P publisher integrations, delivering AI-native ad formats including Sponsored Collections, Sponsored Brand Agents, and Commercial Insights that seamlessly integrate into conversational experiences. As an Applied Science Manager, you will innovate and design new conversational ad experiences that transform how customers discover and engage with products on conversational surfaces. You will lead a team of applied scientists and engineers to build and scale ASA's multi-agent system architecture for conversational commerce. You will own the science roadmap for contextual ad serving, conversation understanding, and commercial insights generation that help publishers monetize their AI chat experiences and unlock opportunities to scale Amazon's advertising business into new conversational surfaces. This role requires strong technical depth in NLP, LLMs, multi-agent systems, and information retrieval, combined with product innovation skills to envision and prototype new advertising experiences for conversational AI. You will manage and grow a science team, set research direction, and influence product strategy. You will work across organizational boundaries with engineering, product, and business teams to translate science investments and innovative product concepts into measurable business impact.

The Measurement, Ad Tech, and Data Science (MADS) team at Amazon Ads is at the forefront of developing innovative solutions that help tens of millions of advertisers understand the value of their ad spend while prioritizing customer privacy and measurement quality. The Media Planning Science team, part of broader MADS team, develops and implements models that deliver insights and recommendations for strategic media planning and measurement across Amazon Advertising's product portfolio. Our mission is to help advertisers create and execute plans that meet their objectives while providing accurate measurement tools. We work on a multitude of problem statements that encompass Reach and Frequency, Budget Planning Optimization, and Recommendations. Our models leverage both heuristic and machine learning approaches including deep learning techniques, with insights delivered through agent-based tools and APIs that integrate seamlessly into user interfaces and programmatic systems to ensure optimal advertising outcomes. As a Senior Applied Scientist on the team, you will be at the forefront of innovation, developing media planning solutions end-to-end from inception to production. You will set the technical vision and innovate on behalf of our customers. You will propose, design, analyze, and productionize models to provide novel measurement insights to our customers. You will partner with engineering to deploy these solutions into production. You will work with key stakeholders from various business teams to enable advertisers to act upon those metrics. Key job responsibilities * Lead the development of media planning models and solutions that address the full spectrum of an advertiser's investment, focusing on scalable and efficient methodologies. * Collaborate closely with cross-functional teams including engineering, product management, and business teams to define and implement measurement solutions. * Use state-of-the-art scientific technologies including Generative AI, Classical Machine Learning, Causal Inference, Natural Language Processing, and Computer Vision to develop state of the art models that measure the impact of media plans across different metrics. * Drive experimentation and the continuous improvement of ML models through iterative development, testing, and optimization. * Translate complex scientific challenges into clear and impactful solutions for business stakeholders. * Mentor and guide junior scientists, fostering a collaborative and high-performing team culture. * Foster collaborations between scientists to move faster, with broader impact. * Regularly engage with the broader scientific community with presentations, publications, and patents. A day in the life You will solve real-world problems by analyzing large amounts of data, generate business insights and opportunities, design simulations and experiments, and develop ML/DL models. The team is driven by business needs, which requires collaboration with other Scientists, Engineers, and Product Managers across the advertising organization. You will prepare written and verbal documents to share insights to audiences of varying levels of technical sophistication. About the team We are a team of scientists across Applied, Research, and Data Science disciplines. You will work with colleagues with deep expertise in ML, DL, NLP, Gen AI, and Causal Inference with a diverse range of backgrounds. We partner closely with top-notch engineers, product managers, sales leaders, and other scientists with expertise in the ads industry and on building scalable modeling and software solutions.

Do you want to join a team of innovative scientists to research and develop generative AI technology that would disrupt the industry? Do you enjoy dealing with ambiguity and working on hard problems in a fast-paced environment? Amazon Connect is a highly disruptive cloud-based contact center from AWS that enables businesses to deliver intelligent, engaging, dynamic, and personalized customer service experiences. The Agentic Customer Experience (ACX) org is responsible for weaving native-AI across the Connect application experiences delivered to end-customers, agents, and managers/supervisors. The Interactive AI Science team, serves as the cornerstone for AI innovation across Amazon Connect, functioning as the sole science team support high impact product including Amazon Q in Connect, Contact Lens and other key initiatives. As an Applied Scientist on our team, you will work closely with senior technical and business leaders from within the team and across AWS. You distill insight from huge data sets, conduct cutting edge research, foster ML models from conception to deployment. You have deep expertise in machine learning and deep learning broadly, and extensive domain knowledge in natural language processing, generative AI and LLM Agents evaluation and optimization, etc. You are comfortable with quickly prototyping and iterating your ideas to build robust ML models using technology such as PyTorch, Tensorflow and AWS Sagemaker. The ideal candidate has the ability to understand, implement, innovate on the state-of-the-art Agentic AI based systems. We have a rapidly growing customer base and an exciting charter in front of us that includes solving highly complex engineering and scientific problems. We are looking for passionate, talented, and experienced people to join us to innovate on modern contact centers in the cloud. The position represents a rare opportunity to be a part of a fast-growing business soon after launch, and help shape the technology and product as we grow. You will be playing a crucial role in developing the next generation contact center, and get the opportunity to design and deliver scalable, resilient systems while maintaining a constant customer focus. About the team Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. 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 (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. 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.

The Shopping Convo Foundations Team - Pre-purchases Science is looking for an Applied Scientist with expertise in Artificial Intelligence and Machine Learning to drive scientific innovation that expands Amazon's product catalogue. Our goal is to leverage AI/ML solutions to enhance catalogue coverage with high precision. In this role, you will research and develop novel machine learning approaches to solve complex catalogue expansion and product attribute challenges. You will design and develop state-of-the-art ML models, conduct rigorous experimentation, and translate scientific breakthroughs into production-ready solutions. You will work closely with ML Engineers and Software Development Engineers to optimize model performance, ensure scalability, and deploy low-latency solutions at Amazon scale.

Amazon's AGI Information is seeking an exceptional Applied Scientist to drive science advancements in the Amazon Knowledge Graph team (AKG). AKG is re-inventing knowledge graphs for the LLM era, optimizing for LLM grounding. At the same time, AKG is innovating to utilize LLMs in the knowledge graph construction pipelines to overcome obstacles that traditional technologies could not overcome. As a member of the AKG IR team, you will have the opportunity to work on interesting problems with immediate customer impact. The team is addressing challenges in web-scale knowledge mining, fact verification, multilingual information retrieval, and agent memory operating over Graphs. You will also have the opportunity to work with scientists working on the other challenges, and with the engineering teams that deliver the science advancements to our customers. A successful candidate has a strong machine learning and agent background, is a master of state-of-the-art techniques, has a strong publication record, has a desire to push the envelope in one or more of the above areas, and has a track record of delivering to customers. The ideal candidate enjoys operating in dynamic environments, is self-motivated to take on new challenges, and enjoys working with customers, stakeholders, and engineering teams to deliver big customer impact, shipping solutions via rapid experimentation and then iterating on user feedback and interactions. Key job responsibilities As an Applied Scientist, you will leverage your technical expertise and experience to demonstrate leadership in tackling large complex problems. You will collaborate with applied scientists and engineers to develop novel algorithms and modeling techniques to build the knowledge graph that delivers fresh factual knowledge to our customers, and that automates the knowledge graph construction pipelines to scale to many billions of facts. Your first responsibility will be to solve entity resolution to enable conflating facts from multiple sources into a single graph entity for each real world entity. You will develop generic solutions that work fo all classes of data in AKG (e.g., people, places, movies, etc.), that cope with sparse, noisy data, that scale to hundreds of millions of entities, and that can handle streaming data. You will define a roadmap to make progress incrementally and you will insist on scientific rigor, leading by example.

We are seeking a Senior Applied Scientist to pioneer the application of artificial intelligence and machine learning to cyber threat intelligence at Amazon scale. In this role, you will invent and deploy novel AI/ML systems that automate threat detection, accelerate intelligence analysis, and enable proactive defense capabilities. You will work on ambiguous, scientifically-complex problems where traditional engineering approaches fall short—from building predictive models that score threat likelihood against Amazon's specific attack surface, to developing graph neural networks that cluster adversary infrastructure, to creating LLM-powered systems that multiply analyst productivity. This is a unique opportunity to bring scientific rigor to one of the most consequential problem domains in technology—protecting hundreds of millions of customers and the infrastructure that powers the global economy. You will be the first Applied Scientist embedded within ACTI, establishing the science agenda and building the foundation for AI-driven threat intelligence at Amazon. This position requires that the candidate selected be a US Citizen. Key job responsibilities Invent • Identify, frame, and solve scientifically-complex threat intelligence problems where no textbook solutions exist—including threat scoring, malware classification, infrastructure clustering, and intelligence automation • Drive the scientific agenda for AI/ML within ACTI by proposing research initiatives, defining success metrics, and securing management buy-in • Extend and invent machine learning techniques for cybersecurity applications, including anomaly detection on noisy data, few-shot learning for emerging threat families, and graph-based reasoning over attacker infrastructure • Publish research at peer-reviewed venues (e.g., USENIX Security, IEEE S&P, ACM CCS, NeurIPS workshops) Implement • Design, build, and deploy production AI/ML systems that process threat data at scale—from model training on petabyte-scale security logs to real-time inference serving millions of predictions daily • Partner with ACTI engineering teams to integrate AI/ML models into existing intelligence platforms • Develop end-to-end solutions including data pipelines, feature engineering, model training, evaluation frameworks, and production monitoring • Write production-quality code and deploy models with operational excellence—reliability, maintainability, and cost efficiency Influence • Influence across multiple ACTI sub-teams and partner organizations • Build consensus on scientific approaches, balancing analytical rigor with operational urgency inherent to threat intelligence • Mentor security engineers and analysts on AI/ML concepts, helping the broader ACTI team develop data literacy and scientific thinking • Represent ACTI in Amazon's internal science community and contribute to the broader information security research ecosystem About the team Amazon Cyber Threat Intelligence (ACTI) is responsible for identifying, curating, and reporting timely, accurate, and actionable threat intelligence to protect Amazon's global businesses and customers. We investigate, analyze, and defend against sophisticated cyber threats across all Amazon business lines—AWS, retail, entertainment, logistics, and corporate infrastructure. Our intelligence products serve Amazon and AWS leadership, service teams, partners, and both internal and external customers. ACTI operates within Amazon's broader security organization led by the Chief Security Officer. We deliver intelligence that enables proactive defense, informs security investment decisions, and supports incident response across the world's largest cloud infrastructure. Diverse Experiences Amazon Security values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why Amazon Security? At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon’s products and services. We offer talented security professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores. Inclusive Team Culture In Amazon Security, it’s in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices. Training & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, training, and other career-advancing resources here to help you develop into a better-rounded professional. 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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.

Amazon is seeking exceptional talent to help develop the next generation of advanced robotics systems that will transform automation at Amazon's scale. We're building revolutionary robotic systems that combine cutting-edge AI, sophisticated control systems, and advanced mechanical design to create adaptable automation solutions capable of working safely alongside humans in dynamic environments. This is a unique opportunity to shape the future of robotics and automation at an unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic dexterous manipulation, locomotion, and human-robot interaction. We are seeking a talented Applied Scientist to join our advanced robotics team, focusing on developing and applying cutting-edge simulation methodologies for advanced robotics systems. This role centers on research and development of physics-based simulation techniques, sim-to-real transfer methods, and machine learning approaches that enable rapid development, testing, and validation of robotic systems operating in complex, real-world environments. Key job responsibilities - Advance physics-based simulation fidelity for contact-rich manipulation and locomotion - Design and build high-performance simulation tools integrated into a robotics design stack - Translate research ideas into robust, verifiable data - Develop methods to quantify and reduce simulation-to-reality gaps across design, safety, and control - Architect scalable simulation solutions for rigid and deformable body dynamics - Build simulation pipelines optimized for a digital twin level of fidelity - Establish frameworks for continuous simulation improvement using real-world hardware - Collaborate with engineering, science, and safety teams on simulation requirements and validation About the team Our team is building a comprehensive robot simulation and modeling platform for advanced robotics development, combining locomotion and manipulation capabilities. We operate at the cutting edge of physics simulation, reinforcement learning, hardware-in-the-loop (HIL), and sim-to-real transfer, collaborating with world-class robotics engineers, scientists, and mechanical designers in a fast-paced, innovation-driven environment. This role uniquely combines fundamental research with real-world development. You will pursue core research questions in physics-based simulation while seeing your work translated into real robots, validated on real hardware. Working alongside Robot scientist and designers, you will help transform research ideas into scalable, quantifiable simulation capabilities that directly impact how robots are designed and built.

As a Sr. Applied Scientist, you will be responsible for bringing new product designs through to manufacturing. You will work closely with multi-disciplinary groups including Product Design, Industrial Design, Hardware Engineering, and Operations, to drive key aspects of engineering of consumer electronics products. In this role, you will use expertise in physical sciences, theoretical, numerical or empirical techniques to create scalable models representing response of physical systems or devices, including: * Applying domain scientific expertise towards developing innovative analysis and tests to study viability of new materials, designs or processes * Working closely with engineering teams to drive validation, optimization and implementation of hardware design or software algorithmic solutions to improve product and customer risks * Establishing scalable, efficient, automated processes to handle large scale design and data analysis * Conducting research into use conditions, materials and analysis techniques * Tracking general business activity including device health in field and providing clear, compelling reports to management on a regular basis * Developing, implementing guidelines to continually optimize design processes * Using simulation tools like LS-DYNA, and Abaqus for analysis and optimization of product design * Using of programming languages like Python and Matlab for analytical/statistical analyses and automation * Demonstrating strong understanding across multiple physical science domains, e.g. structural, thermal, fluid dynamics, and materials * Developing, analyzing and testing structural solutions from concept design, feature development, product architecture, through system validation * Supporting product development and optimization through application of analysis and testing of complex electronic assemblies using advanced simulation and experimentation tools and techniques

Join the AWS Perimeter Protection team as an Applied Scientist, where you will design and build AI/ML models that protect AWS customers from cyber threats at massive scale. You will work on challenging problems in threat detection, bot management, DDoS protection, and web application security — developing and deploying machine learning solutions that leverage techniques including large language models, generative AI, and agentic AI systems. Operating across all AWS regions and processing trillions of requests per week, you will collaborate with experienced scientists and engineers to deliver production-grade, intelligent security systems that provide robust, adaptive, and forward-looking protection for AWS customers worldwide. Key job responsibilities - Design, develop, and evaluate ML models and algorithms for threat detection, anomaly detection, and mitigation of evolving cyber threats including DDoS attacks, bot activity, and web application exploits. - Explore and apply large language models, generative AI, and agentic AI approaches to security challenges such as automated threat analysis, intelligent mitigation, and adaptive defense systems. - Implement end-to-end ML solutions — from data exploration and feature engineering through model training, evaluation, and deployment into production systems. - Analyze large-scale datasets to uncover patterns, identify emerging threat vectors, and translate findings into effective ML-based security solutions. - Build and maintain data pipelines and model training workflows that support rapid experimentation and reliable production performance. - Collaborate with software engineers to integrate ML models into low-latency, high-throughput security systems at cloud scale. - Design and run experiments to validate model performance, measure impact, and iterate on approaches using rigorous scientific methodology. - Stay current with recent advances in AI/ML — including LLMs, generative AI, and agentic systems — and cybersecurity research, applying relevant techniques to improve detection and protection capabilities. - Contribute to design reviews, and knowledge sharing. - Participate in the team's scientific roadmap by proposing ideas and identifying opportunities to improve existing systems.

The Quantum Algorithms Team at the Amazon Web Services (AWS) Center for Quantum Computing (CQC) is looking to hire an Applied Scientist. In this role, you will conduct theoretical research into applications of fault-tolerant quantum computers and develop new quantum algorithms. You will work on the forefront of quantum computing research and contribute toward the development of useful quantum technology, working alongside theoretical and experimental scientists, engineers, and technicians across the CQC. You should have a deep and broad knowledge of quantum algorithms and applications for fault-tolerant quantum computers, and standard mathematical and computational methods for analyzing them. Key job responsibilities We are looking to hire an Applied Scientist focused on developing algorithms and applications for fault-tolerant quantum computers. In this role, you will: - Collaborate with other members of the Quantum Algorithms Team and our academic collaborators, to analyze and optimize existing quantum algorithms - Think big to invent new quantum algorithms and discover new application areas for fault-tolerant quantum computers - Provide subject matter expertise on the topic of quantum algorithms, and communicate the latest developments to the broader quantum computing team - Work with internal and external stakeholders to strengthen the long-term value proposition of quantum computing - Interact with the Quantum Error Correction team to understand the interplay between quantum algorithms and quantum error correction - Publish research papers in scientific journals and present at conferences - Mentor research interns working on scientific projects You are expected to develop and lead high-impact research projects that intersect with our engineering roadmap. Organization and communication skills are essential. A day in the life As an Applied Scientist on the Quantum Algorithms team, you develop practical applications for quantum computers. To do so, you will: - Read academic publications, understand their practical applicability, and present the results in internal meetings - Analyze and optimize existing quantum algorithms in domains such as quantum simulation, quantum chemistry, optimization, or machine learning - or develop entirely new algorithms - Perform resource estimates to quantify the cost of running quantum algorithms within a given hardware architecture - Write technical internal reports documenting research findings and analysis - Write research papers and present your research results at flagship academic and industry conferences.