Careers

Are you passionate about solving big problems from ground-up? Do you enjoy building new state-of-the-art products at internet scale? Come lead the innovation in this startup team, vertical ad products. This is a green field problem without a known answer or a pattern to follow. We have ambitious vision to simplify full funnel advertising solutions, at scale, with specialized agentic AI-powered models and diversify the demand to strategic verticals including finserv, autos, locals.. etc. We are seeking an experienced Applied Scientist to drive innovation in our Ads Foundational Model. In this individual contributor role, you will apply advanced machine learning techniques to improve advertiser performance and customer experience. Key job responsibilities As an Applied Scientist on this team, you will: 1. Develop and drive the science strategy for Ads Foundational Model (Ads-FM), aligning it with the program's objectives and overall business goals. 2. Identify high-impact opportunities within Ads-FM program and lead the ideation, planning, and execution of science initiatives to address them. 3. Build and deploy machine learning models using computer vision, natural language processing, and deep learning to evaluate and enhance ad effectiveness. 4. Develop algorithms that extract meaningful signals from image, video, and audio content to predict and improve customer engagement 5. Leverage Amazon's extensive data repository to create predictive models that generate actionable recommendations for more compelling ad creative 6. Collaborate with business leaders and cross-functional teams to implement ML-powered solutions 7. Contribute to the ML roadmap for the Ads-FM program through innovation and research.

As part of the AWS Applied AI Solutions organization, we have a vision to provide business applications, leveraging Amazon's unique experience and expertise, that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers' businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. We blend vision with curiosity and Amazon's real-world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are no-brainers to buy and easy to use. The Applied Scientist II will contribute to the development of AI systems. The role requires extending existing scientific techniques and inventing new ones to address specific customer needs at a project level. You should be comfortable working semi-autonomously on difficult problems with visible risks or roadblocks. You'll work closely with technical leaders within the team. We're looking for scientists who can maintain high standards while moving quickly, prioritizing both rapid experimentation and responsible AI development to deliver measurable customer impact. Key job responsibilities * Design and implement solutions that extend or adapt scientific approaches for customer needs at the project level * Deliver components into production that meet high quality standards (efficient, reproducible, testable code) * Produce research reports demonstrating correctness, scholarship, and scientific rigor * Work with product and science teams to deliver impactful AI features * Contribute to operational excellence in the team's deliverables About the team ABOUT AWS: Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred 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. 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 in the cloud. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity and AmazeCon conferences, inspire us to never stop embracing our uniqueness. Mentorship and 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.

As part of the AWS Applied AI Solutions organization, we have a vision to provide business applications, leveraging Amazon's unique experience and expertise, that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers' businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. We blend vision with curiosity and Amazon's real-world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are no-brainers to buy and easy to use. The Applied Scientist II will contribute to the development of AI systems. The role requires extending existing scientific techniques and inventing new ones to address specific customer needs at a project level. You should be comfortable working semi-autonomously on difficult problems with visible risks or roadblocks. You'll work closely with technical leaders within the team. We're looking for scientists who can maintain high standards while moving quickly, prioritizing both rapid experimentation and responsible AI development to deliver measurable customer impact. Key job responsibilities * Design and implement solutions that extend or adapt scientific approaches for customer needs at the project level * Deliver components into production that meet high quality standards (efficient, reproducible, testable code) * Produce research reports demonstrating correctness, scholarship, and scientific rigor * Work with product and science teams to deliver impactful AI features * Contribute to operational excellence in the team's deliverables About the team ABOUT AWS: Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred 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. 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 in the cloud. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity and AmazeCon conferences, inspire us to never stop embracing our uniqueness. Mentorship and 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.

Reinventing How the World Shops! We are building the future of human-AI collaboration in commerce. We are creating an AI-native shopping partner that truly understands what customers mean, what they need, and what they haven't yet realized they want—rivaling the intuition of the best human experts, operating at a scale no human ever could. This is a complex personalization challenge. We sit at the intersection of massive-scale language understanding, real-time decision systems, hundreds of millions of customers, and billions of products. Our mission is to collapse the distance between intent and discovery—to make the leap from "searching for products" to "being understood as a person." As a Principal Applied Scientist, you will be the intellectual engine behind this transformation. You will define the frontier, architect the science strategy for a large, multidisciplinary organization, and drive breakthroughs that reshape how Amazon thinks about customers and products at the deepest level. The problems you'll solve don't have textbook answers. You will pioneer next-generation LLM-based reasoning systems that build rich, evolving models of customer intent. You will design transformer architectures that abstract noisy behavioral signals into high-quality latent representations of human preference. You will invent real-time, multi-objective ranking systems that balance exploration, personalization, and serendipity at billions of decisions per day. And you will do all of this as a force multiplier, building foundational technology that empowers teams across Amazon to deliver experiences that feel almost magical. Your work will be felt, not just measured. Every model you build ships directly to hundreds of millions of customers. The feedback loop between your science and real human delight is immediate. This role offers a rare combination of intellectual depth, technical ambition, and tangible impact. Come define what shopping looks like in the age of AI! Key job responsibilities - Innovate new features and models that have huge impact on the customer experience. Help customers find the right products and content on their shopping journey. - Leverage the use of advanced machine learning to create customer shopping experience at Amazon's scale - for all Amazon customers across all countries in realtime - Be a key leader on a multidisciplinary team across science, product, design, and engineering to see through ideas from inception, prototype, to launch in the hands of all Amazon's customers - Drive the science roadmap across multiple teams, helping coordinate a cohesive science agenda across the org. - Mentoring applied scientists across the org, growing their skills and careers. About the team Our mission is to delight every Amazon customer with a personalized shopping experience tailed to their intent. We achieve our mission through investments in Science, UX, and central systems with the purpose of delivering the future of shopping on Amazon. We are seeking a Principal Applied Scientist to lead the science charter across the recommendations and intent identification space.

Are you a scientist interested in pushing the state of the art in machine learning and recommendation systems? Are you interested in working on novel ideas that can positively impact millions of customers? Do you wish you had access to large datasets and tremendous computational resources? Answer yes to any of these questions and you will be a great fit for our team at Amazon. As an Senior Applied Scientist in our team, you will be responsible for the research, design, and development of new AI technologies for Personalization. You will adopt or invent new machine learning and analytical techniques in the realm of recommendations and large language models. You will collaborate with scientists, engineers, and product partners locally and abroad. Your work will include inventing, experimenting with, and launching new features, products and systems. Key job responsibilities - Using Amazon’s large-scale computing resources, you will ask research questions about customer behavior, build state-of-the-art models to optimize the shopping experience, and run these models directly on the retail website. - Develop AI solutions for Recommendation systems using Deep learning, LLMs, Reinforcement Learning, distillation, and Optimization methods; - Work closely with engineers and product managers to design, implement and launch AI solutions end-to-end; - Design and conduct offline and online (A/B) experiments to evaluate proposed solutions based on in-depth data analyses; - Effectively communicate technical and non-technical ideas with teammates and stakeholders; - Stay up-to-date with advancements and the latest modeling techniques in the field; - Publish your research findings in top conferences and journals. About the team Our team is part of Amazon’s Personalization organization, a high-performing group that leverages Amazon’s expertise in machine learning, big data, distributed systems, and user experience design to deliver the best shopping experiences for our customers. We run global experiments and our work has revolutionized e-commerce with features such as "Keep shopping for ...", “Customers who bought this item also bought”, and “Frequently bought together”.

The Private Brands team is looking for a Research Scientist to join the team in building science solutions at scale. Our team applies Optimization, Machine Learning, Statistics, Causal Inference, and Econometrics/Economics to derive actionable insights about the complex economy of Amazon’s retail business and develop Statistical Models and Algorithms to drive strategic business decisions and improve operations. We are an interdisciplinary team of Scientists, Engineers, and Economists. Key job responsibilities You will work with business leaders, scientists, and economists to translate business and functional requirements into concrete deliverables, including the design, development, testing, and deployment of highly scalable optimization solutions and ML models. This is a unique, high visibility opportunity for someone who wants to have business impact, dive deep into large-scale problems, enable measurable actions on the consumer economy, and work closely with scientists and economists. As a Research Scientist, you bring business and industry context to science and technology decisions. You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems, acquiring expertise as needed. You decompose complex problems into straightforward solutions. We are particularly interested in candidates with experience in Operations Research and predictive models and working with distributed systems. Academic and/or practical background in Operations Research, Machine Learning and Reinforcement Learning are particularly relevant for this position. To know more about Amazon science, Please visit https://www.amazon.science

Alexa for Shopping (previously Rufus) is seeking a Senior Manager, Applied Science to lead multidisciplinary teams of Applied Scientists and Machine Learning Engineers building next-generation conversational AI and multi-agent systems powering customer-facing experiences at scale. This leader will drive both scientific innovation and execution across large language models (LLMs), agent orchestration, retrieval and grounding systems, evaluation frameworks, and scalable AI infrastructure. The role requires a combination of deep technical judgment, organizational leadership, product and engineering partnership, and operational excellence. The ideal candidate has a strong track record of building high-performing science and engineering teams, translating ambiguous business problems into scalable AI solutions, and delivering measurable customer impact through applied machine learning and generative AI technologies. Key job responsibilities - Lead and grow teams of Applied Scientists and Machine Learning Engineers working on conversational AI and multi-agent orchestration systems. - Define and drive technical strategy for large-scale generative AI systems, including LLM routing, prompting, grounding, memory, tool use, personalization, and response optimization. - Partner closely with Product, Engineering, and Tech leadership to align AI investments with long-term business and customer goals. - Drive end-to-end delivery of production AI systems balancing quality, latency, scalability, safety, and operational reliability. - Establish scientific and engineering best practices across experimentation, evaluation, model iteration, and production deployment. - Lead roadmap prioritization and execution across research innovation and product delivery timelines. - Build scalable evaluation methodologies and quality frameworks for multilingual and global customer experiences. - Mentor and develop technical leaders across both science and engineering disciplines. - Foster a high-performance culture centered on customer obsession, innovation, operational excellence, and strong cross-functional collaboration.

We are seeking a Human-Robot Interaction (HRI) Applied Scientist to develop cutting-edge interactions that make robots feel alive, personal, and fun. In this role, you will focus on verbal and non-verbal conversational systems, social dynamics, memory, and long-term relationship formation between robots, their environments, and the people they interact with. Your contributions will be essential in advancing robotics by enabling expressive, socially intelligent, and trustworthy interactions between robots and humans. Key job responsibilities - Develop interactive systems that leverage large language models, multimodal inputs and outputs, reinforcement learning from human feedback, or other advanced techniques to achieve fluid, engaging, and socially appropriate robot behavior - Design and implement intelligent conversational systems that handle turn-taking, grounding, interruption, and incorporates context drawn from a robot's physical environment and shared history with a user - Integrate perceptual sensor streams including gaze, facial expression, gesture, posture, and more to understand social context and produce coherent, lifelike interactions. - Develop memory and personalization systems that allow robots to form lasting relationships with individual users, learn their environments, and adapt their behavior over weeks and months - Stay updated on advancements in HRI, NLP, multimodal AI, and cognitive and social science to apply cutting-edge techniques to robot interaction challenges - Lead technical projects from conception through production deployment - Mentor junior scientists and engineers - Bridge research initiatives with practical engineering implementation

Do you want to join an innovative team applying machine learning and advanced statistical techniques to protect Amazon customers and enable a trusted eCommerce experience? Are you excited about working with large-scale datasets and developing models that solve real-world fraud and risk challenges? If so, the Amazon Buyer Risk Prevention (BRP) Machine Learning team may be the right fit for you. We are seeking an Applied Scientist to help develop scalable machine learning solutions that safeguard millions of transactions every day. In this role, you will partner with senior scientists and engineers to translate business problems into data-driven solutions, build and evaluate models, and contribute to next-generation risk prevention systems, including applications of Generative AI and LLM technologies. Key job responsibilities Apply machine learning and statistical techniques to build and improve risk management models Analyze large-scale historical data to identify risk patterns and emerging trends Develop, validate, and deploy innovative models under the guidance of senior scientists Experiment with emerging technologies, including GenAI/LLMs, to enhance automation and risk evaluation Collaborate closely with software engineers to implement models in real-time production systems Partner with operations and business teams to improve risk policies and operational efficiency Build scalable, automated pipelines for data analysis, model training, and validation Monitor model performance and provide clear reporting on key risk and business metrics Research and prototype new modeling approaches to improve system performance

Do you want to join an innovative team of scientists applying machine learning and advanced statistical techniques to protect Amazon customers and enable a trusted eCommerce experience? Are you excited about modeling terabytes of data and building state-of-the-art algorithms to solve complex, real-world fraud and risk challenges? Do you enjoy owning end-to-end machine learning problems, directly influencing customer experience and company profitability, while collaborating in a diverse, high-performing team? If so, the Amazon Buyer Risk Prevention (BRP) Machine Learning team may be the right fit for you. We are seeking an Applied Scientist to design, develop, and deploy advanced algorithmic systems that safeguard millions of transactions every day. In this role, you will independently drive model development from problem formulation to production deployment, build scalable ML solutions, and leverage emerging technologies—including Generative AI and LLMs—to enhance fraud detection and next-generation risk prevention systems. Key job responsibilities Own end-to-end development of machine learning models for large-scale risk management systems Analyze large volumes of historical and real-time data to identify fraud patterns and emerging risk trends Design, develop, validate, and deploy innovative models to production environments Apply GenAI/LLM technologies to automate risk evaluation and improve operational efficiency Collaborate closely with software engineering teams to implement scalable, real-time model solutions Partner with operations and business stakeholders to translate risk insights into measurable impact Establish scalable and automated processes for data analysis, model experimentation, validation, and monitoring Track model performance and business metrics; communicate insights clearly to technical and non-technical stakeholders Research and implement novel machine learning and statistical methodologies