Careers

External job description As a Sr. Applied Scientist, you will be responsible for assessing and optimizing the performance and reliability of our new and emerging category of devices – Kuiper Customer Terminal. Project Kuiper is an initiative to launch a constellation of Low Earth Orbit satellites that will provide low-latency, high-speed broadband connectivity to un-served and under-served communities around the world. 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

The Artificial General Intelligence (AGI) team is looking for a highly skilled and experienced Senior Applied Scientist, to lead the development and implementation of cutting-edge algorithms and models for supervised fine-tuning, reinforcement learning through human feedback and complex reasoning; with a focus across text, image, and video modalities. As a Senior Applied Scientist, you will play a critical role in driving the development of Generative AI (GenAI) technologies that can handle Amazon-scale use cases and have a significant impact on our customers' experiences. Key job responsibilities - Collaborate with cross-functional teams of engineers, product managers, and scientists to identify and solve complex problems in GenAI - Design and execute experiments to evaluate the performance of different algorithms and models, and iterate quickly to improve results - Think big about the arc of development of GenAI over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems - Communicate results and insights to both technical and non-technical audiences, including through presentations and written reports - Mentor and guide junior scientists and engineers, and contribute to the overall growth and development of the team

Amazon Music is an immersive audio entertainment service that deepens connections between fans, artists, and creators. From personalized music playlists to exclusive podcasts, concert livestreams to artist merch, Amazon Music is innovating at some of the most exciting intersections of music and culture. We offer experiences that serve all listeners with our different tiers of service: Prime members get access to all the music in shuffle mode, and top ad-free podcasts, included with their membership; customers can upgrade to Amazon Music Unlimited for unlimited, on-demand access to 100 million songs, including millions in HD, Ultra HD, and spatial audio; and anyone can listen for free by downloading the Amazon Music app or via Alexa-enabled devices. Join us for the opportunity to influence how Amazon Music engages fans, artists, and creators on a global scale. Key job responsibilities - Work backwards from customer problems to research and develop novel machine learning solutions for music and podcast recommendations. Through A/B testing and online experiments done hand-in-hand with engineering teams, you'll implement and validate your ideas and solutions. - Advocate solutions and communicate results, insights and recommendations to stakeholders and partners. - Produce innovative research on recommender systems that shapes the field and meets the high standards of peer-reviewed publications. You'll cement your team's reputation as thought leaders pioneering new recommenders. Stay current with advancements in the field, adapting latest in literature to build efficient and scalable models A day in the life Lead innovation in ML to shape Amazon Music experiences for millions. Collaborate with talented engineers and scientists to guide research and build scalable models across our audio portfolio - music, podcasts, live streaming, and more. Drive experiments and rapid prototyping, leveraging Amazon's data at scale. Innovate daily alongside world-class teams to delight customers worldwide through personalization. About the team The team is responsible for models that underly all of Amazon Music’s recommendations across content types on mobile, web and Alexa. You will collaborate with a team of product managers, applied scientists and software engineers delivering meaningful recommendations, personalized for each of the millions of customers using Amazon Music globally. As a scientist on the team, you will be involved in every aspect of the development lifecycle, from idea generation and scientific research to development and deployment of advanced models. You will work closely with engineering to realize your scientific vision.

Are you looking for an opportunity to build an LLM-based enterprise-grade, highly available, large scale solution? Does it excite you to find patterns and build generic, composable solutions to solve complex problems? Are you looking for inventing newer and simpler ways of building solutions? If so, we are looking for you to fill a challenging position in Alexa Enterprise (AE) team. AE brings the power of Alexa voice assistant to enterprise partners in industries such as hospitality and senior living. We tackle pressing challenges like workforce shortage. We are inventing Large Language Models (LLM)-driven interactions to create memorable moments for users while simultaneously boosting partner revenues and reinforcing brand identity. Beyond managed properties, AE extends Alexa's reach to premium third-party devices, seamlessly integrating with household names like Samsung, LG, and Sonos, thus amplifying its impact across diverse ecosystems. AE team is looking for a passionate, highly skilled and inventive Senior Applied Scientist, with a strong machine learning background, to lead the development and implementation of state-of-the-art ML systems for Alexa Enterprise use cases. As a Senior Applied Scientist in the team, you will play a critical role in driving the development of conversational assistants, in particular those based on Large Language Models (LLM's), that meet enterprise standards. You will handle Amazon-scale use cases with significant impact on our customers' experiences. Key job responsibilities - You will analyze, understand and improve user experiences by leveraging Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in artificial intelligence - You will work on core LLM technologies, including developing best-in-class modeling, prompt optimization algorithms to enable Conversation AI use cases - Build and measure novel online & offline metrics for personal digital assistants and customer scenarios, on diverse devices and endpoints - Create, innovate, and deliver deep learning, policy-based learning, and/or machine learning-based algorithms to deliver customer-impacting results - Perform model/data analysis and monitor metrics through online A/B testing

You will collaborate cross-functionally with engineering teams and program managers throughout the organization to deliver projects aimed at characterizing and improving the performance of new robotic automation technology in Amazon's network of warehouses. In this role, you will use a combination of unified and disparate data sources to uncover insights delivered through decision-driving analytics white-papers and automated data visualizations to influence the development and deployment of new robotic technologies. You will collaborate with Data Engineers, Software, Hardware, and Program Managers to define and deliver world class robotics technologies, analytics tools, and insights to shape the robotic technology landscape. We are looking for an enthusiastic data science professional with a passion for delivering business influencing analysis, papers, and recommendations to complex and ambiguous problems. A practiced data scientists, who uses data engineering, statistics, data visualization, and data science to influence decision making in cross-functional organizations. We are seeking an individual who can think holistically through compound problems to understand how systems work together to define and execute projects which drive improvements to robotic architecture or design. A day in the life In this role, you'll support new technologies looking for decision-making support and deep root cause analysis. These technologies will be in alpha/beta phases and have a start-up mentality of heavy Bias for Action, Ownership, and Customer Obsession. Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply! About the team The Amazon Robotics Storage Analytics team discovers insights in vast and varied robotic data to help our engineering teams understand how their technologies operate across Amazon’s network of fulfillment warehouses. We collaborate with designers, software and hardware engineers, and operations teams to understand product requirements, make feature trade-offs, design, and operate new applications of Amazon Robotics Storage technology. We conduct relevant, insightful analysis and communicate the results through white papers and presentations. Our methods are inclusive of design of experiments, statistical modeling, machine learning, financial analysis, and data visualization.

Do you want a role with deep meaning and the ability to make a massive impact? Hiring top talent is not only critical to Amazon’s success—it can literally change the world. It took a lot of great hires to deliver innovations like AWS, Prime, and Alexa, which make life better for millions of customers around the world every day. As part of the Intelligent Talent Acquisition (ITA) team, you'll have the opportunity to reinvent the hiring process and deliver unprecedented scale, sophistication, and accuracy that Amazon's Talent Acquisition operations need. ITA is an industry-leading people science and technology organization made up of scientists, engineers, analysts, product professionals and more. Our shared goal is to fairly and precisely connect the right people to the right jobs. Last year, we delivered over 6 million online candidate assessments, replacing the "game of chance" with a merit-based approach that gives candidates the chance to showcase their true skills. Each year we help Amazon deliver billions of packages around the world by making it possible to hire hundreds of thousands of associates in the right quantity, at the right location and at exactly the right time. You’ll work on state-of-the-art research, advanced software tools, new AI systems, and machine learning algorithms to solve complex hiring challenges. Leveraging Amazon's in-house tech stack built on AWS, you'll have the autonomy and flexibility to bring innovative solutions to life. One day, we can bring these solutions to the rest of the world. Join ITA in using technologies to transform the hiring landscape and make a meaningful difference in people's lives. Together, we can solve the world's toughest hiring problems. Within ITA, the Candidate Generation team uses scientific experimentation, causal inference, generative AI, machine learning, and forecasting techniques to bring new and returning candidates to the top of the recruitment funnel. Driven by the goal of ensuring every marketing dollar is spent efficiently and effectively, the Candidate Generation team builds innovative decisioning products that provide tailored recommendations for recruiting challenges across a wide array of marketing channels globally. Our award-winning solutions tackle complex and ambiguous problems by applying science methodically and creatively, increasing candidate engagement while driving down costs. As a member of Candidate Generation, your work will modernize the field of Marketing and revolutionize the way we find and attract Amazonian talent.

Amazon Devices is looking for a dynamic, innovative and accomplished Applied Scientist to work on machine learning and data science initiatives to help customers discover Devices products and enabled stakeholders make informed product decisions. Are you excited by the prospect of analyzing terabytes of data and leveraging state-of-the-art data science and machine learning techniques to solve real world problems? Do you like to own business problems/metrics of high ambiguity where you get to define the path forward for success for initiatives? You will get an opportunity to act as a thought leader, work backwards from the customer needs, dive deep into data to understand the issues, conceptualize and build algorithms and collaborate with cross-functional teams. You will take the lead on developing advanced ML systems that are key to reaching our customers with the right recommendations at the right time. Your work will directly impact the success of Amazon's growing Devices business. Key job responsibilities Key job responsibilities * Design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both analysis and business judgment. * Collaborate with software engineering teams to integrate successful experiments into large-scale, highly complex Amazon production systems. * Promote the culture of experimentation and applied science at Amazon. * Excellent communication and presentation skills working with multiple peer groups and different levels of management * Influence and continuously improve a sustainable team culture that exemplifies Amazon’s leadership principles. A day in the life You will work with other scientists, engineers, product managers, and marketers to develop new products that benefit our customers and help us reach our business goals. You will own solutions from end to end: conceptualization, prioritization, development, delivery, and deploy in production. About the team We are a full stack science team that empowers product, marketing, and other business leaders to better understand customers who use Amazon devices, make decisions on product development or optimization, and measure the effectiveness of their efforts against our customer’s expectation. Our focus area is to build analytical frameworks that help the organization easily access data, better understand the decisions customers are making and why, and assess customer satisfaction.

Our team is at the forefront of machine learning research. Led by scientists including Dean Foster, the team is dedicated to developing innovative RL algorithms and applying them to complex, real-world challenges in Amazon's global inventory and supply chain network. Our focus is not just on advancing theoretical knowledge but also on implementing these insights to optimize operations and enhance customer satisfaction. We foster a collaborative environment where exploration of new ideas and tackling complex problems is encouraged. The supply chain spans a wide range of operations,managing decisions that impact billions of dollars worth of inventory. For scientists passionate about impactful research in machine learning and AI, our team offers a dynamic and fulfilling environment to make a tangible difference in the field and Amazon's operations. Key job responsibilities * Design, implement, and evaluate innovative models, agents, and software prototypes. * Collaborate with a team of experienced scientists to drive technological advancements. * Develop innovative solutions to complex business problems in collaboration with partner teams. * Contribute to Amazon's global science community through collaboration and publication of ground-breaking research. * Engage in research projects that contribute to the wider scientific community, sharing findings through publications in top-tier journals and conferences. A day in the life As a part of our team, you will be working alongside thought leaders like Dean Foster, contributing to academic research and complex, real-world applications. Your work will directly influence Amazon's global inventory planning systems, shaping decisions that affect billions of dollars worth of inventory and a wide array of product lines. You will tackle complex inventory planning challenges using Reinforcement Learning, contributing both to the theoretical aspect of the field and its practical applications. We value innovative thinking and the ability to approach problems from new perspectives.

Amazon is investing heavily in building a world class advertising business and we are responsible for defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities. The ATT team, based in Bangalore, is responsible for ensuring that ads are relevant and are of good quality, leading to higher conversion for the sellers and providing a great experience for the customers. We deal with one of the world’s largest product catalog, handle billions of requests a day with plans to grow it by an order of magnitude and use automated systems to validate tens of millions of offers submitted by thousands of merchants in multiple countries and languages. In this role, you will build and develop ML models to address content understanding and labelling problems in Ads. These models will rely on a variety of visual and textual features requiring expertise in both domains. These models need to scale to multiple languages and countries. You will collaborate with engineers and other scientists to build, train and deploy these models. As part of these activities, you will develop production level code that enables labelling of advertising assets and moderation of millions of ads submitted each day.

Are you a MS or PhD student interested in a 2025 Internship in the field of machine learning, deep learning, speech, robotics, computer vision, optimization, quantum computing, automated reasoning, or formal methods? If so, we want to hear from you! We are looking for students interested in using a variety of domain expertise to invent, design and implement state-of-the-art solutions for never-before-solved problems. You can find more information about the Amazon Science community as well as our interview process via the links below; https://www.amazon.science/ https://amazon.jobs/content/en/career-programs/university/science https://amazon.jobs/content/en/how-we-hire/university-roles/applied-science Emirati nationality is required. Key job responsibilities As an Applied Science Intern, you will own the design and development of end-to-end systems. You’ll have the opportunity to write technical white papers, create roadmaps and drive production level projects that will support Amazon Science. You will work closely with Amazon scientists, and other science interns to develop solutions and deploy them into production. You will have the opportunity to design new algorithms, models, or other technical solutions whilst experiencing Amazon’s customer focused culture. The ideal intern must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. A day in the life At Amazon, you will grow into the high impact, visionary person you know you’re ready to be. Every day will be filled with developing new skills and achieving personal growth. How often can you say that your work changes the world? At Amazon, you’ll say it often. Join us and define tomorrow. About the team Applicants will be reviewed on a rolling basis and are assigned to teams aligned with their research interests and experience prior to interviews. Start dates are available throughout the year and durations can vary in length from 3-6 months for full time internships. Some more benefits of an Amazon Science internship include; • All of our internships offer a competitive stipend/salary • Interns are paired with an experienced manager and mentor(s) • Interns receive invitations to different events such as intern program initiatives or site events • Interns can build their professional and personal network with other Amazon Scientists • Interns can potentially publish work at top tier conferences each year This role may available across multiple locations in the EMEA region. Please note these are not remote internships.