Careers

As part of the AWS Applied AI Solutions organization, we're building the future of AI-powered enterprise services across multiple domains. Our vision is to be the trusted foundation for transforming every business with Amazon AI teammates. Our mission is to deliver turnkey, enterprise-grade foundational AI capabilities that create delightful AI powered solutions. We're developing sophisticated AI systems that address complex challenges across autonomous operations, geospatial intelligence, trust and safety, IoT services, and foundational AI platforms. Key job responsibilities - Develop and productize AI solutions that address complex technical challenges requiring novel approaches beyond off-the-shelf tools - Design and implement machine learning systems for diverse applications including video understanding, geospatial optimization, fraud detection, anomaly detection, and automation - Create scalable algorithms and models that generalize across multiple customer use cases and business problems - Conduct rigorous experimentation with state-of-the-art techniques including large language models, computer vision, federated learning, or physics-based modeling, and agentic AI systems - Collaborate with engineering teams to integrate science components into production systems with measurable customer impact - Work directly with product teams to understand requirements, frame ambiguous problems into tractable science solutions, and validate approaches through proof of concepts - Establish evaluation frameworks and best practices for measuring solution performance and business impact - Mentor other scientists and contribute to the broader scientific community through publications when appropriate A day in the life As an Applied Scientist, you'll work on challenging problems that span multiple domains within AWS Core Services. You might develop video processing architectures for autonomous systems, create optimization solvers for geospatial applications, build behavioral detection models for fraud prevention, design anomaly detection systems for IoT devices, or develop specialized AI capabilities for platform services. You'll investigate novel approaches, validate ideas through rigorous experimentation with real data, and collaborate with scientists and engineers to transform research insights into scalable solutions. About the team Our team is a central science organization supporting multiple product teams across AWS Core Services. We tackle fundamental challenges in AI and machine learning that require novel approaches beyond off-the-shelf solutions. Working at the intersection of machine learning, large language models, and domain-specific applications, we develop practical techniques that advance the state-of-the-art while maintaining a clear path to customer impact. Our team builds deep domain expertise across geospatial intelligence, trust and safety systems, autonomous operations, and other critical areas, collaborating closely with engineering teams to transform research insights into scalable production solutions.

We are embarking on a multi-year journey to improve the shopping experience for customers globally. Amazon Search team creates customer-focused search solutions and technologies that make shopping delightful and effortless for our customers. Our goal is to understand what customers are looking for in whatever language happens to be their choice at the moment and help them find what they need in Amazon's vast catalog of billions of products — starting from the very first keystroke. As Amazon expands to new interfaces, we are faced with the unique challenge of maintaining the bar on Search Results Quality and Search Autocomplete. We are looking for a Applied Scientist II to work on improving search on Amazon using NLP, ML, and DL technology. As an Applied Scientist, you will lead our efforts in query understanding, semantic matching, and ranking. You will build systems that anticipate search query intent and surface the right results. As part of this role, you will develop high precision, high recall, and low latency solutions for search. Your solutions should work for all languages that Amazon supports and will be used in all Amazon locales world-wide. You will develop scalable science and engineering solutions that work successfully in production. Key job responsibilities As an Applied Scientist on the team, you will lead science innovation to improve the customer search experience through higher-quality search results. You will: - Develop and deploy ML models to produce relevant search results. - Design and train semantic matching models (bi-encoders, cross-encoders, and distillation from large foundation models) for ranking and relevance. - Develop reinforcement learning and reward-modeling approaches to continuously improve search results quality. - Train multi-objective ranking and scoring systems that balance suggestion diversity, specificity, and relevance. - Design and implement scalable model architectures optimized for strict latency constraints, including knowledge distillation, quantization, and efficient inference strategies for production deployment. - Lead end-to-end science projects from problem formulation through production launch, collaborating closely with engineers and scientists within and outside the team to deliver customer-facing impact.

Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the limits. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. As an Applied Scientist on our team, you will focus on building state-of-the-art ML models for biology. Our team rewards curiosity while maintaining a laser-focus in bringing products to market. Competitive candidates are responsive, flexible, and able to succeed within an open, collaborative, entrepreneurial, startup-like environment. At the forefront of both academic and applied research in this product area, you have the opportunity to work together with a diverse and talented team of scientists, engineers, and product managers and collaborate with other teams.

Applied Scientists in AWS Science of Security are dedicated to making AWS the best computing service in the world for customers who require advanced and rigorous solutions for security, privacy, and sovereignty. Key job responsibilities The successful candidate will: * Solve large or significantly complex problems that require deep knowledge and understanding of your domain and scientific innovation. * Own the design, implementation, and delivery for solutions that have a long-term quantifiable impact. *Provide cross-organizational technical influence, increasing productivity and effectiveness by sharing your deep knowledge and experience. * Develop fundamentally new solutions for business problems. A day in the life This is a unique and rare opportunity to get in early on a fast-growing segment of AWS and help shape the technology, product and the business. You will have a chance to utilize your deep technical experience within a fast moving, start-up environment and make a large business and customer impact. About the team 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 Advertising is one of Amazon's fastest growing and most profitable 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. Millions of advertisers rely on Amazon's self-service support experience to resolve issues, unblock campaigns, and grow their business. Our Support Agents team is building the science behind intelligent, conversational support — systems that understand advertiser intent, retrieve the right knowledge, generate accurate answers, and know when to escalate. We serve ~2M monthly active advertisers across dozens of locales and languages, and every percentage point of improvement in resolution quality translates directly into advertiser success and retention. We are seeking an Applied Scientist who is passionate about building evaluation science, NLP systems, and quality measurement at scale. You will define how we measure "good" — designing LLM-as-a-judge evaluation pipelines, developing our next-generation Issue Resolution Rate (IRR) metrics, and closing the quality gap between English and non-English markets. Your work will directly shape what ships to advertisers and what leadership uses to assess the health of our support experience. Key job responsibilities 1. Enhance support agent capabilities across the broad suite of Amazon Advertising products — expanding coverage, depth of resolution, and advertiser task completion across Sponsored Products, Sponsored Brands, DSP, AMC, and more 2. Design and own the evaluation framework for agent quality — including automated LLM-based scoring of answer correctness, confidence calibration, and conversation-level resolution signals 3. Develop novel metrics that capture whether advertisers actually got the help they needed (beyond surface-level deflection rates) 4. Build and improve retrieval and generation models that power real-time advertiser interactions under strict latency SLAs 5. Drive multilingual science — improve non-English resolution rates through cross-lingual retrieval, translation quality modeling, and locale-aware evaluation 6. Partner with product, engineering, and business teams to productize research and inform roadmap decisions with data A day in the life You might start the morning reviewing overnight evaluation results from your LLM-as-a-judge pipeline, then jump into a whiteboard session designing a new resolution metric that captures whether advertisers actually unblocked their campaign. After lunch you're running offline experiments on a cross-lingual retrieval model to close the quality gap for non-English markets, and by end of day you're syncing with engineering on latency trade-offs for next week's A/B test. The constant: your science directly changes the experience millions of advertisers have when they need help. About the team This role sits within Amazon Advertising's broader Agentic Intelligence organization — a community of multiple Applied Science and Engineering teams building the next generation of AI-powered experiences for advertisers. You'll have access to Principal Engineers and Principal Applied Scientists to pressure-test ideas and elevate your work. What makes this team unique is the balance: you'll drive product-facing science through customer support agents that touch millions of advertisers, while also influencing and collaborating with a core AI infrastructure team within Amazon. The team is cross-functional — scientists and engineers work shoulder-to-shoulder, from problem framing through production deployment.

Are you an inventive, curious, and driven Applied Scientist with a strong background in AI, Computer Vision, and Deep Learning? Join Amazon's AGI IMAX Science team and contribute to significant advancements in Computer Vision, Multimodal Understanding, Generative AI, and foundational models. As part of the AGI IMAX Science team, you'll lead innovative research projects and train large-scale Vision-Language Models (VLMs), diffusion models, and multimodal foundation models that directly impact millions of Amazon and AWS customers. Leveraging Amazon's vast computing power, you'll work alongside a supportive and diverse group of skilled scientists and engineers, building models and services that make a meaningful difference in the industry. Key job responsibilities Lead research initiatives in Computer Vision and Multimodal generative AI, advancing model efficiency, accuracy, and scalability. Train and fine-tune large-scale Vision-Language Models (VLMs), diffusion models, and multimodal foundation models at scale. Design, implement, and evaluate deep learning models in a production environment. Collaborate with cross-functional teams to transfer research outcomes into scalable AWS services. Publish in top-tier conferences and journals, keeping Amazon at the forefront of innovation. Mentor and guide other scientists and engineers, fostering a culture of scientific curiosity and excellence.

Are you an inventive, curious, and driven Applied Scientist with a strong background in AI, Computer Vision, and Deep Learning? Join Amazon's AGI IMAX Science team and contribute to significant advancements in Computer Vision, Multimodal Understanding, Generative AI, and foundational models. As part of the AGI IMAX Science team, you'll lead innovative research projects and train large-scale Vision-Language Models (VLMs), diffusion models, and multimodal foundation models that directly impact millions of Amazon and AWS customers. Leveraging Amazon's vast computing power, you'll work alongside a supportive and diverse group of skilled scientists and engineers, building models and services that make a meaningful difference in the industry. Key job responsibilities Lead research initiatives in Computer Vision and Multimodal generative AI, advancing model efficiency, accuracy, and scalability. Train and fine-tune large-scale Vision-Language Models (VLMs), diffusion models, and multimodal foundation models at scale. Design, implement, and evaluate deep learning models in a production environment. Collaborate with cross-functional teams to transfer research outcomes into scalable AWS services. Publish in top-tier conferences and journals, keeping Amazon at the forefront of innovation. Mentor and guide other scientists and engineers, fostering a culture of scientific curiosity and excellence.

At Amazon Selection and Catalog Systems (ASCS), our mission is to power the online buying experience for customers worldwide so they can find, discover, and buy any product they want. We innovate on behalf of our customers to infer relationships between products in Amazon Catalog to drive the selection gateway for the search and browse experiences on the website. We're solving a fundamental AI challenge: establishing product identity and relationships at unprecedented scale. Using Generative AI, Visual Language Models (VLMs), and multimodal reasoning, we determine what makes each product unique and how products relate to one another across Amazon's catalog. The scale is staggering: billions of products, petabytes of multimodal data, millions of sellers, dozens of languages, and infinite product diversity—from electronics to groceries to digital content. The research challenges are immense. GenAI and VLMs hold transformative promise for catalog understanding, but we operate where traditional methods fail: ambiguous problem spaces, incomplete and noisy data, inherent uncertainty, reasoning across both images and textual data, and explaining decisions at scale. Establishing product identities and groupings requires sophisticated models that reason across text, images, and structured data—while maintaining accuracy and trust for high-stakes business decisions affecting millions of customers daily. Amazon's Item and Relationship Platform group is looking for an innovative and customer-focused applied scientist to help us make the world's best product catalog even better. In this role, you will partner with technology and business leaders to build new state-of-the-art algorithms, models, and services to infer product-to-product relationships that matter to our customers. You will pioneer advanced GenAI solutions that power next-generation agentic shopping experiences, working in a collaborative environment where you can experiment with massive data from the world's largest product catalog, tackle problems at the frontier of AI research, rapidly implement and deploy your algorithmic ideas at scale, across millions of customers. Key job responsibilities * Formulate novel research problems at the intersection of GenAI, multimodal learning, and large-scale information retrieval—translating ambiguous business challenges into tractable scientific frameworks * Design and implement leading models leveraging VLMs, foundation models, and agentic architectures to solve product identity, relationship inference, and catalog understanding at billion-product scale * Pioneer explainable AI methodologies that balance model performance with scalability requirements for production systems impacting millions of daily customer decisions * Own end-to-end ML pipelines from research ideation to production deployment—processing petabytes of multimodal data with rigorous evaluation frameworks * Define research roadmaps aligned with business priorities, balancing foundational research with incremental product improvements * Mentor peer scientists and engineers on advanced ML techniques, experimental design, and scientific rigor—building organizational capability in GenAI and multimodal AI * Represent the team in the broader science community—publishing findings, delivering tech talks, and staying at the forefront of GenAI, VLM, and agentic system research

The Amazon Web Services (AWS) Center for Quantum Computing (CQC) in Pasadena, CA, is looking to hire a Quantum Applied Scientist in the Test and Measurement group. You will be joining a multi-disciplinary team of scientists, engineers, and technicians, all working at the forefront of quantum computing to innovate for the benefit of our customers. You should have a deep and broad knowledge of experimental measurement techniques, and how to develop and automate them in software, towards improving the performance of quantum processors on the path towards delivering a fault-tolerant quantum computer. Key job responsibilities We are looking to hire an Applied Scientist focused on calibrating and optimizing the performance of integrated quantum processors. In this role, you will: - develop novel calibration and optimization routines - test and validate these experimental routines on processors hosted in a cryogenic environment - automate these routines to verify the expected performance of the processors at scale - contribute to novel quantum error correction demonstrations. You are expected to develop and lead high-impact research projects that intersect with our engineering roadmap. We are looking for candidates with strong engineering principles and resourcefulness. Organization and communication skills are essential. A day in the life As an Applied Scientist in the Test and Measurement group you characterize the integrated quantum processors designed and fabricated at CQC. To do so, you will: - collaborate with Software Development Engineers to develop and test novel calibration and optimization tools in software - work with System Engineers to set component level requirements as we scale processor complexity - work with quantum error correction (QEC) theorists to evaluate and improve the logical performance of these processors. About the team 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. AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS. Within AWS UC, Amazon Dedicated Cloud (ADC) roles engage with AWS customers who require specialized security solutions for their cloud services. 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. 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. 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. Export Control Requirement: Due to applicable export control laws and regulations, candidates must be either a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum, or be able to obtain a US export license. If you are unsure if you meet these requirements, please apply and Amazon will review your application for eligibility.

Employer: Amazon.com Services LLC Position: Data Scientist II - AMZ27596.1 Location: Irving, TX Multiple Positions Available: Design and implement scalable and reliable approaches to support or automate decision making throughout the business. Apply a range of data science techniques and tools combined with subject matter expertise to solve difficult business problems and cases in which the solution approach is unclear. Acquire data by building the necessary SQL / ETL queries. Import processes through various company specific interfaces for accessing Oracle, RedShift, and Spark storage systems. Build relationships with stakeholders and counterparts. Analyze data for trends and input validity by inspecting univariate distributions, exploring bivariate relationships, constructing appropriate transformations, and tracking down the source and meaning of anomalies. Build models using statistical modeling, mathematical modeling, econometric modeling, network modeling, social network modeling, natural language processing, machine learning algorithms, genetic algorithms, and neural networks. Validate models against alternative approaches, expected and observed outcome, and other business defined key performance indicators. Implement models that comply with evaluations of the computational demands, accuracy, and reliability of the relevant ETL processes at various stages of production. (40 hours / week, 8:00am-5:00pm, Salary Range $141773 - $184000) Amazon.com is an Equal Opportunity – Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation #0000