UT Austin campus tower is seen on a sunny day, there are students walking in the foreground
Amazon and the University of Texas at Austin have announced the launch of the UT Austin-Amazon Science Hub. The hub’s goals are to advance research that prompts new discoveries and addresses significant challenges while creating solutions whose benefits are shared broadly across all sectors of society.
UT Austin

Amazon and University of Texas at Austin launch Science Hub

The collaboration supports education, community outreach, and the application of academic research to video streaming and robotics.

Amazon and the University of Texas at Austin (UT Austin) have announced the launch of the UT Austin-Amazon Science Hub, continuing Amazon’s commitment to supporting academic research.

The hub’s goals are to advance research that prompts new discoveries and addresses significant challenges while creating solutions whose benefits are shared broadly across all sectors of society. This will be achieved by fostering collaboration among leading scholars, including faculty and students, along with the development of a diverse and sustainable pipeline of research talent. The initial areas of focus will include video streaming, search and information retrieval, and robotics.

The exterior of UT Austin’s Cockrell School of Engineering
As part of the collaboration, which will be hosted in UT Austin’s Cockrell School of Engineering, Amazon will provide funding for research projects, PhD graduate student fellowships, and community-building events.
UT Austin

As part of the collaboration, which will be hosted in UT Austin’s Cockrell School of Engineering, Amazon will provide funding for research projects, PhD graduate student fellowships, and community-building events designed to diversify and increase cross-disciplinary innovation. The inaugural event, open to all UT Austin research staff and research students, will be held April 12 on the UT Austin campus.

“Amazon is thrilled to establish a university hub at UT Austin,” said BA Winston, vice president of technology at Prime Video. “For years, our top scientists have been a resource to UT Austin graduate students collaborating on topics such as developing objective machine learning models to predict perceptual video quality, which drives smart compression, and multimodal AI models that help ensure the highest-quality media playback experience at scale.”

“We are striving to establish even more collaborations with leading companies and organizations in order to bring together more talented people, produce higher-impact research, and help our students reach their greatest ambitions. The launch of the new hub with Amazon is the latest success story in this effort,” said UT Austin President Jay Hartzell. “I am eager to see the discoveries that our researchers and students will create from this collaboration and how those discoveries will change the world.”

The UT Austin band is seen playing on the field
The initial areas of focus of the UT-Austin Amazon Science Hub will include video streaming, search and information retrieval, and robotics.
UT Austin

Amazon has extensive ties to UT Austin via the Amazon Scholars program. James Bornholt, an assistant professor in the Department of Computer Science, whose research is focused on programming languages and formal methods, has worked as a Scholar with Amazon Web Services since 2022. Deepayan Chakrabarti, a Scholar in the Customer Trust organization, is also an associate professor of information, risk, and operations management who researches a broad range of challenges, including large-graph mining and problems of limited data. Shuchi Chawla, a professor of computer science, works as a Scholar in Amazon Ads, where she applies her background in problems that involve stochastic input, online decision-making, uncertainty, and learning.

Matthew Lease, a professor in the School of Information and a Scholar with AWS, is also the head of the Laboratory for Artificial Intelligence and Human-Centered Computing, where his research integrates AI with human-computer-interaction techniques. Ayşegül Şahin, the Richard J. Gonzalez Regents Chair in Economics at UT Austin and a Scholar at Amazon, spent 14 years as a research economist at the Federal Reserve Bank of New York, where she founded and led the team that focused on the analysis of the US labor market. Sujay Sanghavi, associate professor of electrical and computer engineering, is both a principal research scientist and Scholar with Amazon Search. He also serves as the director of the NSF TRIPODS (Transdisciplinary Research in Principles of Data Science) Institute for Data Science.

austin-city-skyline-near-first-street-bridge.jpg
Amazon researchers in Austin are addressing challenges including supply chain optimization, transportation management, and data science.
UT Austin

“This Science Hub will strengthen the partnership between UT Austin and Amazon by leveraging our collective strengths and creating opportunities for our faculty and students and leaders at Amazon to work together to accelerate progress in the areas of computer vision, ML, AI, and robotics,” said Roger Bonnecaze, dean of the Cockrell School of Engineering.

“UT Austin has built an impressive program in robotics, with exceptional faculty and students,” said Ken Washington, vice president of Amazon Consumer Robotics. “The new hub will allow us to collaborate even more closely with them in robotics and related disciplines, so I’m very optimistic about our growing partnership.”

The establishment of the UT Austin Science Hub builds upon Amazon’s existing research efforts in Austin. Amazon researchers in Austin are addressing challenges including supply chain optimization, transportation management, and data science.

In addition, several researchers at UT-Austin are recipients of Amazon Research Awards, including Ying Ding, the Bill and Lewis Suit Professor in the School of Information, and Jon Tamir, assistant professor of electrical and computer engineering.

Founded in 1883, UT Austin is a leading public research institution, attracting more than $650 million annually. More than 52,000 students and 3,000 teaching faculty compose the university’s 18 colleges and schools. UT Austin was ranked first among US universities in research financed by the US National Science Foundation (NSF) in 2020, according to the annual Higher Education Research and Development (HERD) survey.

“With this hub, I look forward to seeing more cutting-edge research that will not only enhance our customer experience but also help us envision longer-term research goals,” Winston said.

Related content

US, VA, Arlington
Do you want a role with deep meaning and the ability to have a global 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. As part of the Intelligent Talent Acquisition (ITA) team, you'll have the opportunity to reinvent Amazon’s hiring process with unprecedented scale, sophistication, and accuracy. 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, driving a merit-based hiring approach that gives candidates the opportunity to showcase their true skills. Each year we also 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, at exactly the right time. You’ll work on state-of-the-art research with advanced software tools, new AI systems, and machine learning algorithms to solve complex hiring challenges. Join ITA in using cutting-edge 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 Global Hiring Science (GHS) team designs and implements innovative hiring solutions at scale. We work in a fast-paced, global environment where we use research to solve complex problems and build scalable hiring products that deliver measurable impact to our customers. We are seeking selection researchers with a strong foundation in hiring assessment development, legally-defensible validation approaches, research and experimental design, and data analysis. Preferred candidates will have experience across the full hiring assessment lifecycle, from solution design to content development and validation to impact analysis. We are looking for equal parts researcher and consultant, who is able to influence customers with insights derived from science and data. You will work closely with cross-functional teams to design new hiring solutions and experiment with measurement methods intended to precisely define exactly what job success looks like and how best to predict it. Key job responsibilities What you’ll do as a GHS Research Scientist: • Design large-scale personnel selection research that shapes Amazon’s global talent assessment practices across a variety of topics (e.g., assessment validation, measuring post-hire impact) • Partner with key stakeholders to create innovative solutions that blend scientific rigor with real-world business impact while navigating complex legal and professional standards • Apply advanced statistical techniques to analyze massive, diverse datasets to uncover insights that optimize our candidate evaluation processes and drive hiring excellence • Explore emerging technologies and innovative methodologies to enhance talent measurement while maintaining Amazon's commitment to scientific integrity • Translate complex research findings into compelling, actionable strategies that influence senior leader/business decisions and shape Amazon's talent acquisition roadmap • Write impactful documents that distill intricate scientific concepts into clear, persuasive communications for diverse audiences, from data scientists to business leaders • Ensure effective teamwork, communication, collaboration, and commitment across multiple teams with competing priorities A day in the life Imagine diving into challenges that impact millions of employees across Amazon's global operations. As a GHS Research Scientist, you'll tackle questions about hiring and organizational effectiveness on a global scale. Your day might begin with analyzing datasets to inform how we attract and select world-class talent. Throughout the day, you'll collaborate with peers in our research community, discussing different research methodologies and sharing innovative approaches to solving unique personnel challenges. This role offers a blend of focused analytical time and interacting with stakeholders across the globe.
US, WA, Seattle
We are looking for a researcher in state-of-the-art LLM technologies for applications across Alexa, AWS, and other Amazon businesses. In this role, you will innovate in the fastest-moving fields of current AI research, in particular in how to integrate a broad range of structured and unstructured information into AI systems (e.g. with RAG techniques), and get to immediately apply your results in highly visible Amazon products. If you are deeply familiar with LLMs, natural language processing, computer vision, and machine learning and thrive in a fast-paced environment, this may be the right opportunity for you. Our fast-paced environment requires a high degree of autonomy to deliver ambitious science innovations all the way to production. You will work with other science and engineering teams as well as business stakeholders to maximize velocity and impact of your deliverables. It's an exciting time to be a leader in AI research. In Amazon's AGI Information team, you can make your mark by improving information-driven experience of Amazon customers worldwide!
US, MA, N.reading
Amazon Industrial Robotics is seeking exceptional talent to help develop the next generation of advanced robotics systems that will transform automation at Amazon's scale. We're building revolutionary robotic systems that combine cutting-edge AI, sophisticated control systems, and advanced mechanical design to create adaptable automation solutions capable of working safely alongside humans in dynamic environments. This is a unique opportunity to shape the future of robotics and automation at unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic manipulation, locomotion, and human-robot interaction. This role presents an opportunity to shape the future of robotics through innovative applications of deep learning and large language models. At Amazon Industrial Robotics we leverage advanced robotics, machine learning, and artificial intelligence to solve complex operational challenges at unprecedented scale. Our fleet of robots operates across hundreds of facilities worldwide, working in sophisticated coordination to fulfill our mission of customer excellence. We are pioneering the development of robotics foundation models that: - Enable unprecedented generalization across diverse tasks - Enable unprecedented robustness and reliability, industry-ready - Integrate multi-modal learning capabilities (visual, tactile, linguistic) - Accelerate skill acquisition through demonstration learning - Enhance robotic perception and environmental understanding - Streamline development processes through reusable capabilities The ideal candidate will contribute to research that bridges the gap between theoretical advancement and practical implementation in robotics. You will be part of a team that's revolutionizing how robots learn, adapt, and interact with their environment. Join us in building the next generation of intelligent robotics systems that will transform the future of automation and human-robot collaboration. Key job responsibilities As an Applied Science Manager in the Foundations Model team, you will: - Build and lead a team of scientists and developers responsible for foundation model development - Define the right ‘FM recipe’ to reach industry ready solutions - Define the right strategy to ensure fast and efficient development, combining state of the art methods, research and engineering. - Lead Model Development and Training: Designing and implementing the model architectures, training and fine tuning the foundation models using various datasets, and optimize the model performance through iterative experiments - Lead Data Management: Process and prepare training data, including data governance, provenance tracking, data quality checks and creating reusable data pipelines. - Lead Experimentation and Validation: Design and execute experiments to test model capabilities on the simulator and on the embodiment, validate performance across different scenarios, create a baseline and iteratively improve model performance. - Lead Code Development: Write clean, maintainable, well commented and documented code, contribute to training infrastructure, create tools for model evaluation and testing, and implement necessary APIs - Research: Stay current with latest developments in foundation models and robotics, assist in literature reviews and research documentation, prepare technical reports and presentations, and contribute to research discussions and brainstorming sessions. - Collaboration: Work closely with senior scientists, engineers, and leaders across multiple teams, participate in knowledge sharing, support integration efforts with robotics hardware teams, and help document best practices and methodologies.
CA, QC, Montreal
Join the next revolution in robotics at Amazon's Frontier AI & Robotics team, where you'll work alongside world-renowned AI pioneers to push the boundaries of what's possible in robotic intelligence. As an Applied Scientist, you'll be at the forefront of developing breakthrough foundation models that enable robots to perceive, understand, and interact with the world in unprecedented ways. You'll drive independent research initiatives in areas such as perception, manipulation, scene understanding, sim2real transfer, multi-modal foundation models, and multi-task learning, designing novel algorithms that bridge the gap between state-of-the-art research and real-world deployment at Amazon scale. In this role, you'll balance innovative technical exploration with practical implementation, collaborating with platform teams to ensure your models and algorithms perform robustly in dynamic real-world environments. You'll have access to Amazon's vast computational resources, enabling you to tackle ambitious problems in areas like very large multi-modal robotic foundation models and efficient, promptable model architectures that can scale across diverse robotic applications. Key job responsibilities - Design and implement novel deep learning architectures that push the boundaries of what robots can understand and accomplish - Drive independent research initiatives in robotics foundation models, focusing on breakthrough approaches in perception, and manipulation, for example open-vocabulary panoptic scene understanding, scaling up multi-modal LLMs, sim2real/real2sim techniques, end-to-end vision-language-action models, efficient model inference, video tokenization - Lead technical projects from conceptualization through deployment, ensuring robust performance in production environments - Collaborate with platform teams to optimize and scale models for real-world applications - Contribute to the team's technical strategy and help shape our approach to next-generation robotics challenges A day in the life - Design and implement novel foundation model architectures, leveraging our extensive compute infrastructure to train and evaluate at scale - Collaborate with our world-class research team to solve complex technical challenges - Lead technical initiatives from conception to deployment, working closely with robotics engineers to integrate your solutions into production systems - Participate in technical discussions and brainstorming sessions with team leaders and fellow scientists - Leverage our massive compute cluster and extensive robotics infrastructure to rapidly prototype and validate new ideas - Transform theoretical insights into practical solutions that can handle the complexities of real-world robotics applications About the team At Frontier AI & Robotics, we're not just advancing robotics – we're reimagining it from the ground up. Our team is building the future of intelligent robotics through ground breaking foundation models and end-to-end learned systems. We tackle some of the most challenging problems in AI and robotics, from developing sophisticated perception systems to creating adaptive manipulation strategies that work in complex, real-world scenarios. What sets us apart is our unique combination of ambitious research vision and practical impact. We leverage Amazon's massive computational infrastructure and rich real-world datasets to train and deploy state-of-the-art foundation models. Our work spans the full spectrum of robotics intelligence – from multimodal perception using images, videos, and sensor data, to sophisticated manipulation strategies that can handle diverse real-world scenarios. We're building systems that don't just work in the lab, but scale to meet the demands of Amazon's global operations. Join us if you're excited about pushing the boundaries of what's possible in robotics, working with world-class researchers, and seeing your innovations deployed at unprecedented scale.
US, NY, New York
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through cutting-edge generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. Key job responsibilities Participate in the Science hiring process as well as mentor other scientists - improving their skills, their knowledge of your solutions, and their ability to get things done. Identify and devise new video related solutions following a customer-obsessed scientific approach to address customer or business problems when the problem is ill-defined, needs to be framed, and new methodologies or paradigms need to be invented at the product level. Articulate potential scientific challenges of ongoing or future customers’ needs or business problems, and present interventions to address them. Independently assess alternative video related technologies, driving evaluation and adoption of those that fit best A day in the life As an Applied Scientist on the Sponsored Products Video team, you will work with a team of talented and experienced engineers, scientists, and designers to help bring new products to market and ensure that our customers are delighted by what we create. The Sponsored Products Video team is responsible for the design, development, and implementation of Sponsored Products Video experiences worldwide. About the team The Sponsored Products Video team within Sponsored Products and Brands creates relevant and engaging video experiences, connecting advertisers and shoppers. We are on a mission to make Amazon the best in class destination for shoppers to discover, engage and build affinity with brands, making shopping delightful, & personal.
IN, TS, Hyderabad
We're seeking an Applied Scientist to lead and innovate in applying advanced AI technologies that will reshape how businesses sell on Amazon. Our team is passionate about leveraging Machine Learning, GenAI, and Agentic AI to help B2B sellers optimize their operations and drive growth. Join Amazon Business 3P (Third Party - Sellers) - a rapidly growing global organization where we innovate at the intersection of AI technology and B2B commerce. We're reimagining how sellers reach and serve business customers, creating intelligent solutions that help them grow their B2B business on Amazon. From AI-powered Seller Central tools to smart business certifications, dynamic pricing capabilities, and advanced analytics, we're transforming how B2B selling happens. As an Applied Scientist II on our AB 3P Tech team, you'll drive the development and implementation of state-of-the-art algorithms and models for supervised fine-tuning and reinforcement learning. You'll work with highly technical, entrepreneurial teams to: - Design and implement AI models that power the B2B selling experience - Lead the development of GenAI products that can handle Amazon-scale use cases - Drive research and implementation of advanced algorithms for human feedback and complex reasoning - Make strategic AI technology decisions and mentor technical talent - Own critical AI systems spanning from Seller Central to Amazon Business detail pages Join us in shaping the future of B2B selling - we're building applied AI solutions that businesses love and trust for their day-to-day success. If you are scrappy and bias for action is your favorite Leadership Principle, you'll fit right in as we innovate across the seller experience to create significant impact in this fast-growing business. Key job responsibilities Key job responsibilities: - Collaborate with cross-functional teams of engineers, product managers, and scientists to identify and solve complex problems in Gen AI - 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 Gen AI 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 About the team At Amazon Business Third Party (AB3P) Tech, we're revolutionizing B2B e-commerce by empowering sellers in the business marketplace. Our scope spans the complete B2B selling journey, from Seller Central to Amazon Business detail pages, cart, and checkout for merchant-fulfilled offers. Our entrepreneurial culture and global reach define us. We develop features across seller experience, delivery, certifications, fees, registration, and analytics, collaborating with worldwide teams and leveraging advanced AI technologies to continuously innovate. Working in true Day 1 spirit, we build next-generation solutions that shape the future of B2B commerce. Join us in building next-generation solutions that shape the future of B2B commerce.
GB, London
Come build the future of entertainment with us. Are you interested in shaping the future of movies and television? Prime Video is a premium streaming service that offers customers a vast collection of TV shows and movies - all with the ease of finding what they love to watch in one place. We offer customers thousands of popular movies and TV shows including Amazon Originals and exclusive licensed content to exciting live sports events. Prime Video is a fast-paced, growth business - available in over 200 countries and territories worldwide. The Video Content Research team works in a dynamic environment where innovating on behalf of our customers is at the heart of everything we do. We are seeking a Data Scientist to develop scalable models that uncover key insights into how, why and when customers engage with Prime Video marketing. Key job responsibilities In this role you will work closely with business stakeholders and technical peers (data scientists, economists and engineers) to develop causal marketing measurement models, analyze experiments and investigate customer, marketing and content related factors that drive engagement with Prime Video. You will create mechanisms and infrastructure to deploy complex models and generate insights at scale. You will have the opportunity to work with large datasets, work with AWS to build and deploy machine learning models that impact Prime Video's marketing decisions. About the team The Video Content Research team uses machine learning, econometrics, and data science to optimize Amazon's marketing and content investments. We generate insights for Amazon's digital video strategy, partnering with finance, marketing, and content teams. We analyze customer behavior on Prime Video (marketing impressions, clicks on owned channels) to identify optimization opportunities.
US, MA, Boston
AI is the most transformational technology of our time, capable of tackling some of humanity’s most challenging problems. That is why Amazon is investing in generative AI (GenAI) and the responsible development and deployment of large language models (LLMs) across all of our businesses. Come build the future of human-technology interaction with us. We are looking for a Research Scientist with strong technical skills which includes coding and natural language processing experience in dataset construction, training and evaluating models, and automatic processing of large datasets. You will play a critical role in driving innovation and advancing the state-of-the-art in natural language processing and machine learning. You will work closely with cross-functional teams, including product managers, language engineers, and other scientists. Key job responsibilities Specifically, the Research Scientist will: • Ensure quality of speech/language/other data throughout all stages of acquisition and processing, including data sourcing/collection, ground truth generation, normalization, transformation, cross-lingual alignment/mapping, etc. • Clean, analyze and select speech/language/other data to achieve goals • Build and test models that elevate the customer experience • Collaborate with colleagues from science, engineering and business backgrounds • Present proposals and results in a clear manner backed by data and coupled with actionable conclusions • Work with engineers to develop efficient data querying infrastructure for both offline and online use cases
US, VA, Arlington
The People eXperience and Technology Central Science (PXTCS) team uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, wellbeing, and the value of work to Amazonians. PXTCS is an interdisciplinary team that combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal. PXTCS is looking for an economist who can apply economic methods to address business problems. The ideal candidate will work with engineers and computer scientists to estimate models and algorithms on large scale data, design pilots and measure impact, and transform successful prototypes into improved policies and programs at scale. PXTCS is looking for creative thinkers who can combine a strong technical economic toolbox with a desire to learn from other disciplines, and who know how to execute and deliver on big ideas as part of an interdisciplinary technical team. Ideal candidates will work in a team setting with individuals from diverse disciplines and backgrounds. They will work with teammates to develop scientific models and conduct the data analysis, modeling, and experimentation that is necessary for estimating and validating models. They will work closely with engineering teams to develop scalable data resources to support rapid insights, and take successful models and findings into production as new products and services. They will be customer-centric and will communicate scientific approaches and findings to business leaders, listening to and incorporate their feedback, and delivering successful scientific solutions. A day in the life The Economist will work with teammates to apply economic methods to business problems. This might include identifying the appropriate research questions, writing code to implement a DID analysis or estimate a structural model, or writing and presenting a document with findings to business leaders. Our economists also collaborate with partner teams throughout the process, from understanding their challenges, to developing a research agenda that will address those challenges, to help them implement solutions. About the team PXTCS is a multidisciplinary science team that develops innovative solutions to make Amazon Earth's Best Employer
JP, 13, Tokyo
The JP Books - Manga team is looking for an Applied Scientist to participate in our AI related efforts to develop new prototypes and concepts that can then be translated into meaningful technologies impacting millions of customers. In this position, you will be expected to research, design and build/train/tune models and provide recommendations in areas including but not limited to natural language processing (automatic translation, summarization, extraction) and image processing (boundary detection, image understanding, image generation). The ideal candidate will have strong knowledge in the areas of Computer Vision, Translations and or Image understanding/generation. This is the ideal role if you are excited about leveraging science for tangible business impact to the Manga books business. Amazon encourages publications, and you will work within an international team of engineers, all based in Tokyo, Japan while collaborating with partner scientists in Tokyo and Seattle. Key job responsibilities As an Applied Scientist, your responsibilities will be: - Spot opportunities for innovation using AI for the JP Manga business, and publish to internal or external conferences. - Work closely with other Books scientists and engineers to build, review and improve your model design proposals. - Partner with product managers and other business stakeholders, documenting and explaining your progress in business reviews, and being the technical voice in charge of your product. - Be active in the community, participating in science education/growth activities for Books and Amazon JP - Keep up to date with scientific development in related field About the team Our team develops and owns the experience for Manga books on Amazon in Japan. We build products powering the solutions offered to publishers, authors and customers in Japan and worldwide. We interact with Product Managers and business stakeholders to develop features that allow us to better serve our customers. We place strong emphasis on continuous learning through internal mechanisms for our team to keep on growing their expertise and keep up with the state of the art. Our mission is to establish Amazon Manga as the go-to destination for digital and print Manga.