Careers

We are looking for a passionate, talented, and inventive Applied Scientist with a strong machine learning background to help build industry-leading language technology powering Alexa for Shopping, our AI-driven search and shopping assistant, helping customers with their shopping tasks at every step of their shopping journey. This innovative role focuses on developing and optimizing language model-powered (LLM/SLM) conversational experiences. The core emphasis is to get the best performance out LLMs/SLMs via careful and methodical instruction design, contextual grounding, informed choices of MCP tools and agent/multi-agent systems, context engineering, model fine-tuning, evaluation frameworks, and experimentation to systematically improve quality, robustness, and customer impact. The work combines scientific rigor with product intuition to systematically raise the bar for conversational AI performance at Amazon scale. Our mission in conversational shopping is to make it easy for customers to find and discover the best products to meet their needs by helping with their product research, providing comparisons and recommendations, answering product questions, enabling shopping directly from images or videos, providing visual inspiration, and more. We do this by leveraging advanced analytics, Natural Language Processing (NLP), Machine Learning (ML), A/B testing, causal inference, and data-driven insights to continuously improve our systems. Key job responsibilities As an Applied Scientist on our team, you will develop and maintain LLM agents, including automated eval pipelines, LLM-as-a-judge methodologies, rubric design, and dataset curation to measure nuanced aspects of response quality. You will partner with the wider org to experiment with techniques such as retrieval augmentation, context enrichment, prompt decomposition, and model fine-tuning or post-training strategies, if and when applicable. Where latency and cost constraints demand it, you will lead post-training of small language models (SLMs) — including supervised fine-tuning, preference optimisation, and distillation — to deliver low-latency conversational and shopping experiences. You will apply applied machine learning and deep learning techniques as last-mile improvements to shopping experiences, that might span ranking, relevance, personalisation, and multimodal understanding. You will design and evaluate agentic architectures that balance the needs of diverse shopping use cases, making principled choices across paradigms such as single-agent and multi-agent systems, memory management strategies, and tool orchestration to optimise for quality, latency, and reliability at scale. You will leverage petabytes of data and identify opportunities to leverage machine learning models aimed at making conversational systems more performant. A day in the life - Perform hands-on analysis of large-scale multimodal interaction datasets to develop insights into how customers engage with conversational AI systems and how to improve response quality and customer experience. - Use statistical methods, experimentation, and data-driven analysis to develop scalable approaches for measuring, evaluating, and optimizing large language model (LLM)-based shopping assistant systems, leveraging structured and unstructured contextual signals. - Conduct deep-dive analyses to identify opportunities for improving conversational relevance, grounding, customer satisfaction, and downstream business impact. - Collaborate with Product management and Engineers to translate analytical insights into production systems, working closely on model evaluation and deployment. - Communicate results and insights to both technical and non-technical audiences, including through presentations, written reports, and data visualizations. About the team The Alexa for Shopping Science team, based in London, works alongside ~150 engineers, designers and product managers, shaping the future of AI-driven shopping experiences at Amazon. The team works on every aspect of the conversational AI system, from making it agentic, enabling customers to set price alerts or empower the assistant to act on their behalf and automatically purchase products when the price is right, to understanding multimodal user queries and generating answers that combine text, image, audio and video, including deep research reports that scour the web and the Amazon catalog to provide detailed and personalised shopping guidance. We utilize and advance state-of-art techniques in the fields of Natural Language Processing, gen AI, Information Retrieval, Machine/Deep Learning, and Data Mining. We validate our work by actively participating in the internal and external scientific communities.

Do you have proven analytical capabilities to identify business opportunities, develop predictive models and optimization algorithms to help us build state of the art Support organization? At Amazon, we are working to be the most customer-centric company on earth. To get there, we need exceptionally talented, bright, and driven people. We set big goals and are looking for people who can help us reach and exceed them. Amazon Web Services (AWS) is one of the world’s most comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from data centers globally. Amazon Web Services, Inc. provides services for broad range of applications including compute, storage, databases, networking, analytics, machine learning and artificial intelligence (AI), Internet of Things (IoT), security, and application development, deployment, and management. AWS Support's Capacity Planning team is looking for a strong, talented Data Scientist to model contact and volume forecasting, discovering insights and identifying opportunities through the use of statistics, machine learning, and combinatorial optimization problems to drive business and operational improvements. You are passionate about building solutions that will help drive a more efficient operations network and optimize cost. In this role, you will partner with data engineering, tooling team, operations, training, workforce management and finance teams, driving optimization and prediction solutions across the network influencing the long-term strategy of the business. We are looking for an experienced and motivated Data Scientist with proven abilities to build and manage modeling projects, forecasting solutions, identify data requirements, build methodology and tools that are statistically grounded. You are an expert in the areas of data science, forecasting, optimization, machine learning and statistics, and is comfortable facilitating ideation and working from concept through execution. You are customer obsessed, innovative, independent, results-oriented and enjoys working in a fast-paced growing organization. An interest in operations, process improvement is helpful. The ability to embrace this ambiguity and work with a highly distributed team of experts is critical. While this is a small team, there is opportunity to own globally impactful work and grow your career in technical, programmatic or people leadership. You will likely to work in Python or R, building forecasting, predictive and optimization models. Your problem solving ability, knowledge of data models and ability to drive results through ambiguity are more important to us. Key job responsibilities Key job responsibilities • Establish and execute data management and strategy frameworks including data collection, storage, integration and ensuring data quality and integrity • Collaborate with cross-functional teams to identify data-related challenges and opportunities, develop data-driven solutions, and align data strategy with the organization's overall objectives • Conduct thorough research and analysis to understand organization's data needs and requirements, including evaluating existing data infrastructure and systems, identifying gaps and areas for improvement, and proposing innovative solutions. • Leverage large-scale data processing frameworks, such as Apache Spark or Hadoop, to handle big data and ensure efficient model training and evaluation • Continuously evaluate and improve machine learning models by incorporating feedback from stakeholders, monitoring their performance in real-world scenarios, and exploring new algorithms and techniques to enhance accuracy and efficiency • Develop and implement machine learning models that drive business value: o Analyze historical data and identifying patterns, to forecast future outcomes and provide inputs into strategic plans o Analyze customer data and market trends, to help develop targeted go to market strategies that our efforts are data driven and have a higher chance of success o Analyze financial data, to identify cost-saving opportunities, optimize pricing strategies, and forecast revenue growth helping the leaders to make informed decisions o Analyze operational data, to identify bottlenecks, inefficiencies, and areas for process improvement, helping in streamlining operations, reducing costs, and improving customer satisfaction About the team About the team About Us Diverse Experiences AWS 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. 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. 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.

We're seeking a Senior Applied Scientist to pioneer sensor-based algorithms that power next-generation experiences across Amazon's device ecosystem, including Echo, Kindle, Fire TV, and Fire Tablets. Working with multidisciplinary teams of scientists and engineers, you'll develop innovative technologies at the intersection of signal processing and machine learning that transform how millions of customers interact with our products. The ideal candidate combines strong theoretical foundations in machine learning and signal processing with practical implementation skills. You'll develop state-of-the-art sensor algorithms from concept to production, translate complex research problems into practical consumer technologies, and create solutions optimized for diverse hardware platforms. We're looking for someone who thrives in fast-paced environments, solves complex problems efficiently, and iterates quickly based on real-world feedback. Your technical decisions will directly shape future product capabilities and deliver exceptional experiences to Amazon customers worldwide. Key job responsibilities - Develop and implement advanced algorithms and machine learning models to enhance Amazon's products and services. - Collaborate with cross-functional teams, including software engineers, scientists, and product managers to translate business needs into technical solutions. - Conduct thorough data analysis to identify trends, patterns, and insights that drive product innovation and improvement. - Optimize algorithms for performance, scalability, and efficiency across various Amazon platforms. - Present findings and recommendations to stakeholders, influencing product strategy and decision-making. - Stay abreast of the latest research and technological advancements in machine learning and related fields to continuously improve Amazon's offerings. - Mentor and guide junior scientists and engineers, fostering a culture of learning and innovation. - Ensure the ethical use of data and algorithms, adhering to Amazon's guidelines and best practices. - Contribute to the publication of research findings in conferences and journals, elevating Amazon's reputation in the scientific community. About the team At Amazon Lab126, we're a pioneering research and development hub dedicated to designing and engineering revolutionary consumer electronics. Established in 2004 as a subsidiary of Amazon.com, Inc., we've been at the forefront of innovation, starting with the creation of the best-selling Kindle family of products. Our portfolio has since expanded to include transformative devices such as Fire tablets, Fire TV, and Amazon Echo. Our Lab126 team is dedicated to developing advanced sensing technologies and algorithms, collaborating with program managers to design and implement transformative user features and experiences.

Amazon.com’s Product Detail Page team is looking for talented, motivated and passionate applied scientist to be part of the design and development of a highly scalable multi-tiered shopping application to provide the best possible online shopping experience for Amazon customers world-wide. Our team is comprised of talented applied scientists, developers, testers, program managers, designers and product managers tasked with the singular goal to create THE world's best buying experience. Scientists on this team develop the next-generation technologies and experiences that change how millions interact and shop online. To provide the best possible online shopping at the scale of the web requires ideas from every area of computer science, including distributed computing, large-scale system design, machine learning, natural language processing, data compression and user interface design; the list goes on and is growing every day. We need our scientists to be versatile and always eager to tackle new problems as we continue to push technology forward. Our team leverages sophisticated econometric, machine learning, and big data technologies to help customers to discover the right products at the right prices from millions of trusted sellers billions of times a day. If you are looking for a career-defining opportunity on one of the most customer centric and business impacting teams within Amazon, we’d love to hear from you. We are looking for an Applied Scientist to help build the next generation of Detail Page optimization algorithms. These new set of algorithms will incorporate the continually changing preferences of our customers and continue to scale with numerous new programs that Amazon is introducing for our customers. You will work with multiple Amazon businesses and programs to identify big business opportunities and propose new business features and technical systems to improve customer experience on Amazon Detail Page, Search Page and many other widgets throughout the website. You will be responsible for the quality of algorithm design and will get the opportunity to present your ideas and share results of your deliverables with Amazon executives on a frequent basis. You will get an opportunity to work with senior scientists to define and enforce broad, company-wide technical standards in optimization techniques, statistical modeling and simulation techniques, and/or data analytics.

Are you a passionate scientist in the computer vision area who is aspired to apply your skills to bring value to millions of customers? Here at Ring, we have a unique opportunity to innovate and see how the results of our work improve the lives of millions of people and make neighborhoods safer. You will be part of a team committed to pushing the frontier of computer vision and machine learning technology to deliver the best experience for our neighbors. This is a great opportunity for you to innovate in this space by developing highly optimized algorithms that will work on scale. This position requires experience with developing CV, Multi-modal LLMs and/or Vision Language Models. You will collaborate with different Amazon teams to make informed decisions on the best practices in machine learning to build highly-optimized integrated hardware and software platforms. Key job responsibilities - Participate in the design, development, evaluation, deployment and updating of data-driven models for computer vision applications. - Research and implement the state-of-the-art computer vision and Vision Language models algorithms. - Collaborate with product managers and engineering teams to design and implement computer vision and machine learning based features for Ring devices - Influence system design and product vision by making informed decisions on the selection of technology, data sources, algorithms, and sensors.

We are seeking Data Scientist II with strong science application skills to join our Device Economics team. This role will focus primarily on Amazon's innovative devices and services (e.g. Echo Family of Devices), working at the intersection of economic modeling, forecasting science, and business strategy. The ideal candidate will be responsible for pre-launch forecasts, annualized overall forecasts, identifying substitution patterns, and partnering closely with product managers and marketing managers to understand the evolution of the Devices portfolio. Key job responsibilities Forecasting & Modeling 1. Develop and maintain pre-launch forecasts and annualized overall forecasts for Amazon Devices 2. Identify and model substitution patterns across the device portfolio 3. Build economic and financial models to support demand planning and business decisions 4. Formulate relevant analytical frameworks to address key economic issues in device forecasting Science Communication & Collaboration 1. Explain complex science models and methodologies to non-technical stakeholders including product managers and marketing managers 2. Collaborate with economists, data scientists, and applied scientists across Decision Science 3. Present results of analyses to cross-functional teams and leadership 4. Build trust in science models and forecast outputs with product teams Innovation & Strategic Thinking 1. Think creatively about ways that leading-edge analytics and emerging data sources can address Devices' most pressing business challenges 2. Help internal teams leverage analytic tools to better manage innovation 3. Conduct empirical studies and perform quantitative and qualitative research 4. Identify opportunities to improve forecasting accuracy and business impact Cross-Functional Partnership 1. Work closely with product managers and marketing managers to understand portfolio evolution and business strategy 2. Support DSO leadership in quarterly business reviews and strategic planning A day in the life Your days will be split between refining and building models and working with business leaders to interpret them. You own science-based forecasts that can directly impact Amazon's bottom line on the order of multi-million dollar decisions. - You will perform model refreshes or updates to analyses as needed; and, - You will be expected to develop new techniques to process large data sets, address quantitative problems, and contribute to design of automated systems. About the team The Decision Science team within DSO (Device Supply Organization) is responsible for forecasting and demand planning initiatives across Amazon Devices. The DSO team of 300+ engineers, scientists, and PMs applies quantitative methods and data-driven approaches to replace judgment-based decisions with science-driven forecasts. Decision Science focuses on lifetime demand forecasting using econometric and machine learning models for rapid reforecasting, mix adjustments, and portfolio management for new product launches. We also inform to go/no-go investment decision for new product initiatives

Are you a passionate scientist in the computer vision area who is aspired to apply your skills to bring value to millions of customers? Here at Ring, we have a unique opportunity to innovate and see how the results of our work improve the lives of millions of people and make neighborhoods safer. As an Applied Scientist, you will work with talented peers pushing the frontier of computer vision and machine learning technology to deliver the best experience for our neighbors. This is a great opportunity for you to innovate in this space by developing highly optimized algorithms that will work at scale. This position requires experience with developing Multi-modal LLMs and/or Vision Language Models. You will collaborate with different Amazon teams to make informed decisions on the best practices in machine learning to build highly-optimized integrated hardware and software platforms. Key job responsibilities - Participate in the design, development, evaluation, deployment and updating of data-driven models for computer vision applications. - Research and implement the state-of-the-art computer vision and Vision Language models algorithms. - Collaborate with product managers and engineering teams to design and implement computer vision and machine learning based features for Ring devices - Influence system design and product vision by making informed decisions on the selection of technology, data sources, algorithms, and sensors.

Are you a passionate scientist in the computer vision area who is aspired to apply your skills to bring value to millions of customers? Here at Ring, we have a unique opportunity to innovate and see how the results of our work improve the lives of millions of people and make neighborhoods safer. As an Applied Scientist, you will work with talented peers pushing the frontier of computer vision and machine learning technology to deliver the best experience for our neighbors. This is a great opportunity for you to innovate in this space by developing highly optimized algorithms that will work at scale. This position requires experience with developing Computer Vision, Multi-modal LLMs and/or Vision Language Models. You will collaborate with different Amazon teams to make informed decisions on the best practices in machine learning to build highly-optimized integrated hardware and software platforms. Key job responsibilities - Participate in the design, development, evaluation, deployment and updating of data-driven models for computer vision applications. - Research and implement the state-of-the-art computer vision and Vision Language models algorithms. - Collaborate with product managers and engineering teams to design and implement computer vision and machine learning based features for Ring devices - Influence system design and product vision by making informed decisions on the selection of technology, data sources, algorithms, and sensors.

Are you a passionate scientist in the computer vision area who is aspired to apply your skills to bring value to millions of customers? Here at Ring, we have a unique opportunity to innovate and see how the results of our work improve the lives of millions of people and make neighborhoods safer. As an Applied Scientist, you will work with talented peers pushing the frontier of computer vision and machine learning technology to deliver the best experience for our neighbors. This is a great opportunity for you to innovate in this space by developing highly optimized algorithms that will work at scale. This position requires experience with developing Computer Vision, Multi-modal LLMs and/or Vision Language Models. You will collaborate with different Amazon teams to make informed decisions on the best practices in machine learning to build highly-optimized integrated hardware and software platforms. Key job responsibilities - Participate in the design, development, evaluation, deployment and updating of data-driven models for computer vision applications. - Research and implement the state-of-the-art computer vision and Vision Language models algorithms. - Collaborate with product managers and engineering teams to design and implement computer vision and machine learning based features for Ring devices - Influence system design and product vision by making informed decisions on the selection of technology, data sources, algorithms, and sensors. Key job responsibilities -

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