View of the Massachusetts Institute of Technology in Cambridge, showcasing the architecture of its main building with an expansive green lawn in the foreground on a sunny autumn day.
Amazon and the Massachusetts Institute of Technology announced the establishment of the Science Hub, a collaboration that will focus on areas of mutual interest, beginning with artificial intelligence and robotics. Amazon will provide funding to support research and academic fellowships.
Marcio Jose Bastos Silva/Shutterstock

Amazon and MIT establish Science Hub

The collaboration will support research, education, and outreach efforts in areas of mutual interest, beginning with artificial intelligence and robotics.

Amazon and MIT today announced the establishment of the Science Hub, a collaboration that will focus on areas of mutual interest, beginning with artificial intelligence and robotics in the first year. To get the hub started, Amazon will provide gift and sponsored research funding over the next five years to support research and academic fellowships on campus.

The primary goals of the hub are to ensure the benefits of AI and robotics innovations are shared broadly — both through education and by advancing research — and to broaden participation in the research from diverse, interdisciplinary scholars, and other innovators.

 Aude Oliva, a senior research scientist and director of strategic industry engagement in the MIT Schwarzman College of Computing
Aude Oliva, a senior research scientist and director of strategic industry engagement in the MIT Schwarzman College of Computing

“AI and robotics have an enormous impact on every aspect of our lives, fundamentally changing how we work, learn, access resources and services, and connect to one another — so it’s critical we conduct research that advances the field in ways that are responsible, effective, and beneficial to society,” said Aude Oliva, a senior research scientist and director of strategic industry engagement in the MIT Schwarzman College of Computing. “We take an expansive view of AI and robotics to include expertise from across all five of the Institute’s schools. We’re excited by the potential of collaborations with industry leaders who bring their insights to the research, want to support the next generation of talent, and are best positioned to implement what is learned.”

Oliva will serve as the principal investigator for the Science Hub, which will be administered at MIT by the Schwarzman College of Computing, a cross-cutting entity with education and research links across MIT to increase connections in computing and AI.

Amazon’s support of the new Science Hub underscores a continuing commitment to collaborating with academia on research efforts as well as helping to fund the education and training of future scientists who reflect the diversity of perspectives and expertise at Amazon, MIT, and around the world.

Tye Brady, MIT alumni and Amazon Robotics chief technologist, noted that Amazon’s existing relationship with a number of MIT faculty helped lay the groundwork for the collaboration.

“Over the years we’ve worked with great people at MIT like Russ Tedrake, Alberto Rodriguez, Daniela Rus, Julie Shah, and Nicholas Roy,” Brady said. “Their hard work and ability to perform world class research is a model for what is possible when industry and academia work together.”

We are particularly keen to utilize the breadth of collaboration mechanisms available in the new hub, including sponsored research which could lead to open-source publications and community outreach.
Siddhartha Srinivasa

The gift will enable a broad set of programs across MIT, including fellowships that will be awarded annually to graduate students and postdoctoral researchers, as well as support for events and activities that accelerate AI and robotics research in ways to make it more accessible, such as research symposia that are open to other academic institutions and the public. Additional sponsored research funds will support research projects led by MIT faculty members.

“We are delighted to join forces with MIT, bringing together top scientists and engineers from our two organizations in a joint endeavor to find solutions to the most challenging problems in AI and robotics,” Brady said. “MIT’s well-established record of conducting leading-edge, multi-disciplinary research paired with Amazon’s emphasis on translating research into applied science will help ensure the new hub results in practical solutions whose benefits extend beyond industry and academia.”

“We are particularly keen to utilize the breadth of collaboration mechanisms available in the new hub, including sponsored research which could lead to open-source publications and community outreach that will broaden participation in the research process,” added Siddhartha Srinivasa director, Amazon Robotics AI. “These mechanisms are now open to all the business areas of Amazon beyond Robotics too, so we are excited to see the breadth of innovation to come from this collaboration in the coming years.”

Amazon in Massachusetts

The Science Hub complements existing collaborations between Amazon and MIT, and Amazon’s research presence in the Boston area, including an Alexa science team in Cambridge.

Dating back to 2003, Amazon has had a longstanding engagement with the MIT Leaders for Global Operations, focusing on data analytics, supply chain and systems optimization research.

Earlier this year, the Amazon Last Mile team announced a collaboration with MIT’s Center for Transportation & Logistics (MIT CTL) with the aim of incorporating driver know-how into route optimization models. The two groups sponsored a competition, called the Amazon Last Mile Routing Research Challenge, in which academic teams trained machine learning models to predict the delivery routes chosen by experienced drivers. The winners of that competition were announced recently.

In addition, Amazon’s Core AI team in Boston features three MIT faculty currently working as Amazon Scholars: Victor Chernozhukov, the International Ford Professor in the MIT Department of Economics and Statistics and Data Science Center; Yury Polyanskiy, associate professor in the MIT Department of Electrical Engineering and Computer Science, Institute for Data, Systems, and Society, Laboratory for Information and Decision Systems, and Statistics and Data Center; and Alexander Rakhlin, professor in the MIT Department of Brain and Cognitive Sciences and Statistics and Data Science Center.

Amazon is also building a new state-of-the-art robotics innovation center in Westborough, Mass. Opening this fall, the company is investing more than $40 million in the new site to allow Amazon Robotics to continue to grow its engineering, manufacturing, support and test teams in the state. The new 350,000 square feet facility will feature corporate offices, research and development labs, and manufacturing space and will be in addition to Amazon Robotics’ current site in North Reading — together serving as the company’s epicenter of robotics innovation.

Amazon also announced plans earlier this year to expand its Boston Tech Hub. The expansion will create 3,000 jobs which will include technology roles in software development, artificial intelligence, and machine learning, along with non-tech corporate roles in product management, HR, finance, and more. Amazon has invested more than $10 billion in Massachusetts over the past decade, including opening five fulfillment and sortation centers, 13 delivery stations, and 33 Whole Foods Market locations. Those investments have helped to create more than 20,000 full- and part-time jobs across the state.

Research areas

Related content

US, WA, Bellevue
Amazon is looking for a Principal Applied Scientist world class scientists to join its AWS Fundamental Research Team working within a variety of machine learning disciplines. This group is entrusted with developing core machine learning solutions for AWS services. At the AWS Fundamental Research Team you will invent, implement, and deploy state of the art machine learning algorithms and systems. You will build prototypes and explore conceptually large scale ML solutions across different domains and computation platforms. You will interact closely with our customers and with the academic community. You will be at the heart of a growing and exciting focus area for AWS and work with other acclaimed engineers and world famous scientists. About the team About the team Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. 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 (gender diversity) 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.
IN, KA, Bengaluru
Alexa+ is Amazon’s next-generation, AI-powered virtual assistant. Building on the original Alexa, it uses generative AI to deliver a more conversational, personalised, and effective experience. Alexa Sensitive Content Intelligence (ASCI) team is developing responsible AI (RAI) solutions for Alexa+, empowering it to provide useful information responsibly. The team is currently looking for Senior Applied Scientists with a strong background in NLP and/or CV to design and develop ML solutions in the RAI space using generative AI across all languages and countries. A Senior Applied Scientist will be a tech lead for a team of exceptional scientists to develop novel algorithms and modeling techniques to advance the state of the art in NLP or CV related tasks. You will work in a hybrid, fast-paced organization where scientists, engineers, and product managers work together to build customer facing experiences. You will collaborate with and mentor other scientists to raise the bar of scientific research in Amazon. Your work will directly impact our customers in the form of products and services that make use of speech, language, and computer vision technologies. We are looking for a leader with strong technical experiences a passion for building scientific driven solutions in a fast-paced environment. You should have good understanding of Artificial Intelligence (AI), Natural Language Understanding (NLU), Machine Learning (ML), Dialog Management, Automatic Speech Recognition (ASR), and Audio Signal Processing where to apply them in different business cases. You leverage your exceptional technical expertise, a sound understanding of the fundamentals of Computer Science, and practical experience of building large-scale distributed systems to creating reliable, scalable, and high-performance products. In addition to technical depth, you must possess exceptional communication skills and understand how to influence key stakeholders. You will be joining a select group of people making history producing one of the most highly rated products in Amazon's history, so if you are looking for a challenging and innovative role where you can solve important problems while growing as a leader, this may be the place for you. Key job responsibilities You'll lead the science solution design, run experiments, research new algorithms, and find new ways of optimizing customer experience. You set examples for the team on good science practice and standards. Besides theoretical analysis and innovation, you will work closely with talented engineers and ML scientists to put your algorithms and models into practice. Your work will directly impact the trust customers place in Alexa, globally. You contribute directly to our growth by hiring smart and motivated Scientists to establish teams that can deliver swiftly and predictably, adjusting in an agile fashion to deliver what our customers need. A day in the life You will be working with a group of talented scientists on researching algorithm and running experiments to test scientific proposal/solutions to improve our sensitive contents detection and mitigation. This will involve collaboration with partner teams including engineering, PMs, data annotators, and other scientists to discuss data quality, policy, and model development. You will mentor other scientists, review and guide their work, help develop roadmaps for the team. You work closely with partner teams across Alexa to deliver platform features that require cross-team leadership. About the hiring group About the team The mission of the Alexa Sensitive Content Intelligence (ASCI) team is to (1) minimize negative surprises to customers caused by sensitive content, (2) detect and prevent potential brand-damaging interactions, and (3) build customer trust through appropriate interactions on sensitive topics. The term “sensitive content” includes within its scope a wide range of categories of content such as offensive content (e.g., hate speech, racist speech), profanity, content that is suitable only for certain age groups, politically polarizing content, and religiously polarizing content. The term “content” refers to any material that is exposed to customers by Alexa (including both 1P and 3P experiences) and includes text, speech, audio, and video.
US, WA, Seattle
Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the limits. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. As an Research Scientist on our team, you will focus on building state-of-the-art ML models for healthcare. Our team rewards curiosity while maintaining a laser-focus in bringing products to market. Competitive candidates are responsive, flexible, and able to succeed within an open, collaborative, entrepreneurial, startup-like environment. At the forefront of both academic and applied research in this product area, you have the opportunity to work together with a diverse and talented team of scientists, engineers, and product managers and collaborate with other teams. This role offers a unique opportunity to work on projects that could fundamentally transform healthcare outcomes. Key job responsibilities In this role, you will: • Analyze complex healthcare data to identify patterns, trends, and insights • Develop and validate statistical methodologies • Collaborate with Applied Scientists to support model development efforts • Drive advancements in machine learning and data science • Balance theoretical knowledge with practical implementation • Work closely with customers and partners to understand their requirements • Navigate ambiguity and create clarity in early-stage product development • Collaborate with cross-functional teams while fostering innovation in a collaborative work environment to deliver impactful solutions • Establish best practices for data analysis, data curation, and model evaluation • Partner with leadership to define roadmap and strategic initiatives You’ll need a strong background in statistics, knowledge of the complications of longitudinal healthcare data, proven leadership skills, and the ability to translate complex concepts into actionable plans. You’ll also need to effectively translate research findings into practical solutions. A day in the life You'll work with large-scale healthcare datasets, conducting sophisticated statistical analyses to generate actionable insights. You'll collaborate with Applied Scientists to prepare data, build ML models, validate model predictions and ensure statistical rigor in our approach. The team is driven by business needs, which requires collaboration with other Scientists, Engineers, and Product Managers across the Special Projects organization. You will prepare written and verbal presentations to share insights to audiences of varying levels of technical sophistication. About the team We represent Amazon's ambitious vision to solve the world's most pressing challenges. We are exploring new approaches to enhance research practices in the healthcare space, leveraging Amazon's scale and technological expertise. We operate with the agility of a startup while backed by Amazon's resources and operational excellence. We're looking for builders who are excited about working on ambitious, undefined problems and are comfortable with ambiguity.
US, NJ, Newark
At Audible, we believe stories have the power to transform lives. It’s why we work with some of the world’s leading creators to produce and share audio storytelling with our millions of global listeners. We are dreamers and inventors who come from a wide range of backgrounds and experiences to empower and inspire each other. Imagine your future with us. ABOUT THIS ROLE As an Applied Scientist, you will solve large complex real-world problems at scale, draw inspiration from the latest science and technology to empower undefined/untapped business use cases, delve into customer requirements, collaborate with tech and product teams on design, and create production-ready models that span various domains, including Machine Learning (ML), Artificial Intelligence (AI), Natural Language Processing (NLP), Reinforcement Learning (RL), real-time and distributed systems. As an Applied Scientist on our AI Acceleration Team, you will be at the forefront of transforming how Audible harnesses the power of AI to enhance productivity, unlock new value, and reimagine how we work. In this unique role, you'll apply ML/AI approaches to solve complex real-world problems while helping build the blueprint for how Audible works with AI. ABOUT YOU You are passionate about applying scientific approaches to real business challenges, with deep expertise in Machine Learning, Natural Language Processing, GenAI, and large language models. You thrive in collaborative environments where you can both build solutions and empower others to leverage AI effectively. You have a track record of developing production-ready models that balance scientific excellence with practical implementation. You're excited about not just building AI solutions, but also creating frameworks, evaluation methodologies, and knowledge management systems that elevate how entire organizations work with AI. As an Applied Scientist, you will... - Design and implement innovative AI solutions across our three pillars: driving internal productivity, building the blueprint for how Audible works with AI, and unlocking new value through ML & AI-powered product features - Develop machine learning models, frameworks, and evaluation methodologies that help teams streamline workflows, automate repetitive tasks, and leverage collective knowledge - Enable self-service workflow automation by developing tools that allow non-technical teams to implement their own solutions - Collaborate with product, design and engineering teams to rapidly prototype new product ideas that could unlock new audiences and revenue streams - Build evaluation frameworks to measure AI system quality, effectiveness, and business impact - Mentor and educate colleagues on AI best practices, helping raise the AI fluency across the organization ABOUT AUDIBLE Audible is the leading producer and provider of audio storytelling. We spark listeners’ imaginations, offering immersive, cinematic experiences full of inspiration and insight to enrich our customers daily lives. We are a global company with an entrepreneurial spirit. We are dreamers and inventors who are passionate about the positive impact Audible can make for our customers and our neighbors. This spirit courses throughout Audible, supporting a culture of creativity and inclusion built on our People Principles and our mission to build more equitable communities in the cities we call home.
IL, Tel Aviv
We are looking for a Data Scientist to join our Prime Video team in Israel, focusing on personalizing customer experiences through Search and Recommendations. Our team leverages Machine Learning (ML) to deliver tailored content discovery, helping millions of customers find the entertainment they love. You will work on large-scale experimentation, measurement frameworks, and data-driven decision-making that directly shapes how customers interact with Prime Video. Key job responsibilities - Design metrics frameworks and evaluation systems to measure the quality, performance, and reliability of algorithmic solutions - Lead the design, execution, and analysis of A/B tests to validate product hypotheses and quantify customer impact - Communicate analytical findings and recommendations clearly to both technical teams and business stakeholders, driving data-informed decisions - Partner with Applied Scientists, Software Engineers, and Product Managers to define requirements, evaluate models, and drive data-informed product decisions - Act as the subject matter expert for data structures, metrics definitions, and analytical best practices - Identify opportunities for improving customer experience through deep-dive analyses of user behavior and algorithm performance
IL, Haifa
Are you a scientist interested in pushing the state of the art in Information Retrieval, Large Language Models and Recommendation Systems? Are you interested in innovating on behalf of millions of customers, helping them accomplish their every day goals? Do you wish you had access to large datasets and tremendous computational resources? Do you want to join a team of capable scientist and engineers, building the future of e-commerce? Answer yes to any of these questions, and you will be a great fit for our team at Amazon. Our team is part of Amazon’s Personalization organization, a high-performing group that leverages Amazon’s expertise in machine learning, generative AI, large-scale data systems, and user experience design to deliver the best shopping experiences for our customers. Our team is building next-generation personalization systems powered by Large Language Models. We are tackling novel research challenges to help customers discover products they'll love - at Amazon scale and latency requirements. We are a team uniquely placed within Amazon, to have a direct window of opportunity to influence how customers will think about their shopping journey in the future. As an Applied Science Manager, you will lead a team of scientists working at the frontier of LLM-based personalization. You will set the technical vision, drive the research agenda, and ensure your team delivers production-ready solutions. You will hire, mentor, and develop world-class scientists while fostering a culture of innovation and scientific rigor. You will partner closely with engineering and product teams to translate ambitious research into customer-facing impact, and represent your team's work to senior leadership. Please visit https://www.amazon.science for more information.
US, WA, Seattle
We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA Are you interested in building Agentic AI solutions that solve complex builder experience challenges with significant global impact? The Security Tooling team designs and builds high-performance AI systems using LLMs and machine learning that identify builder bottlenecks, automate security workflows, and optimize the software development lifecycle—empowering engineering teams worldwide to ship secure code faster while maintaining the highest security standards. As a Senior Applied Scientist on our Security Tooling team, you will focus on building state-of-the-art ML models to enhance builder experience and productivity. You will identify builder bottlenecks and pain points across the software development lifecycle, design and apply experiments to study developer behavior, and measure the downstream impacts of security tooling on engineering velocity and code quality. Our team rewards curiosity while maintaining a laser-focus on bringing products to market that empower builders while maintaining security excellence. Competitive candidates are responsive, flexible, and able to succeed within an open, collaborative, entrepreneurial, startup-like environment. At the forefront of both academic and applied research in builder experience and security automation, you have the opportunity to work together with a diverse and talented team of scientists, engineers, and product managers and collaborate with other teams. This role offers a unique opportunity to work on projects that could fundamentally transform how builders interact with security tools and how organizations balance security requirements with developer productivity. Key job responsibilities • Design and implement novel AI/ML solutions for complex security challenges and improve builder experience • Drive advancements in machine learning and science • Balance theoretical knowledge with practical implementation • Navigate ambiguity and create clarity in early-stage product development • Collaborate with cross-functional teams while fostering innovation in a collaborative work environment to deliver impactful solutions • Design and execute experiments to evaluate the performance of different algorithms and models, and iterate quickly to improve results • Establish best practices for ML experimentation, evaluation, development and deployment You’ll need a strong background in AI/ML, proven leadership skills, and the ability to translate complex concepts into actionable plans. You’ll also need to effectively translate research findings into practical solutions. A day in the life • Integrate ML models into production security tooling with engineering teams • Build and refine ML models and LLM-based agentic systems that understand builder intent • Create agentic AI solutions that reduce security friction while maintaining high security standards • Prototype LLM-powered features that automate repetitive security tasks • Design and conduct experiments (A/B tests, observational studies) to measure downstream impacts of tooling changes on engineering productivity • Present experimental results and recommendations to leadership and cross-functional teams • Gather feedback from builder communities to validate hypotheses About the team Diverse Experiences Amazon Security values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why Amazon Security? At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon’s products and services. We offer talented security professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores Inclusive Team Culture In Amazon Security, it’s in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices. Training & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, training, and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.
IN, TS, Hyderabad
Are you fascinated by the power of Natural Language Processing (NLP) and Large Language Models (LLM) to transform the way we interact with technology? Are you passionate about applying advanced machine learning techniques to solve complex challenges in the e-commerce space? If so, Amazon's International Seller Services team has an exciting opportunity for you as an Applied Scientist. At Amazon, we strive to be Earth's most customer-centric company, where customers can find and discover anything they want to buy online. Our International Seller Services team plays a pivotal role in expanding the reach of our marketplace to sellers worldwide, ensuring customers have access to a vast selection of products. As an Applied Scientist, you will join a talented and collaborative team that is dedicated to driving innovation and delivering exceptional experiences for our customers and sellers. You will be part of a global team that is focused on acquiring new merchants from around the world to sell on Amazon’s global marketplaces around the world. Join us at the Central Science Team of Amazon's International Seller Services and become part of a global team that is redefining the future of e-commerce. With access to vast amounts of data, technology, and a diverse community of talented individuals, you will have the opportunity to make a meaningful impact on the way sellers engage with our platform and customers worldwide. Together, we will drive innovation, solve complex problems, and shape the future of e-commerce. Please visit https://www.amazon.science for more information Key job responsibilities - Apply your expertise in LLM models to design, develop, and implement scalable machine learning solutions that address complex language-related challenges in the international seller services domain. - Collaborate with cross-functional teams, including software engineers, data scientists, and product managers, to define project requirements, establish success metrics, and deliver high-quality solutions. - Conduct thorough data analysis to gain insights, identify patterns, and drive actionable recommendations that enhance seller performance and customer experiences across various international marketplaces. - Continuously explore and evaluate state-of-the-art NLP techniques and methodologies to improve the accuracy and efficiency of language-related systems. - Communicate complex technical concepts effectively to both technical and non-technical stakeholders, providing clear explanations and guidance on proposed solutions and their potential impact. - Mentor and guide team of Applied Scientists from technical and project advancement stand point - Contribute research to science community and conference quality level papers.
US, WA, Seattle
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 AI/ML to shape Amazon Music experiences for millions. Develop state of the art models leveraging and advancing the latest developments in machine learning and genAI. 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 Amazon Music’s recommendations content types (music, podcasts, audiobooks), sequencing models for algorithmic stations across mobile, web and Alexa, ranking models for the carousels and Page strategy on Amazon Music surfaces, and Query Understanding for conversational flow and recommendations. 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.
US, WA, Seattle
We are seeking a Senior Applied Scientist to join our team in developing pioneering AI research, Generative AI, Agentic AI, Large Language Models (LLMs), Diffusion and Flow Models, and other advanced Machine Learning and Deep Learning solutions for Amazon Selection and Catalog Systems, within the AI Lab Team. This role offers a unique opportunity to work on AI research and AI products that will shape the future of online shopping experiences. Our team operates at the forefront of AI research and development, working on challenges that directly impact millions of customers worldwide. We push the boundaries of AI at both the foundational and application layers. As a Senior Applied Scientist, you will have the chance to experiment with LLMs and deep learning techniques, apply your research to solve real-world problems at an unprecedented scale, and collaborate with experienced scientists to contribute to Amazon's scientific innovation. Join us in redefining the future of shopping. Your work will directly influence how customers interact with the world's largest online store. Key job responsibilities - Design and implement novel AI solutions for Amazon catalog of products - Develop and train state-of-the-art LLMs, Diffusion Models, and other Generative AI models - Build and deploy autonomous AI Agents in Amazon production ecosystem - Scale AI models to handle billions of diverse products across multiple languages and geographies - Conduct research in areas such as Autonomous AI Agents, Generative AI, Language Modeling, Multi-modality Computer Vision, Diffusion Models, Reinforcement Learning - Collaborate with cross-functional teams to integrate AI models into Amazon's production ecosystem - Contribute to the scientific community through publications and conference presentations