Ten university teams selected for Alexa Prize TaskBot Challenge 2

Second iteration features five new teams.

Amazon today announced that ten teams from around the globe have been selected to participate in the Alexa Prize TaskBot Challenge year 2, a university challenge focused on developing multimodal (voice and vision) conversational agents that assist customers in completing tasks requiring multiple steps and decisions.

Alexa Prize is a flagship industry-academic collaboration dedicated to accelerating the science of conversational artificial intelligence (AI) and multimodal human-AI interactions.

“Prize competitions provide an agile science experimentation framework for researchers and students encouraging them to explore transformational ideas at the boundaries of what is achievable,” said Reza Ghanadan, senior principal scientist with Alexa AI and head of Alexa Prize. “We have developed the CoBot platform and tools to lower the barriers to AI innovation for both the academic research community and students interested in conversational AI assistants. These tools allow students to quickly deploy their solutions at scale in the real world with Alexa, then observe, evaluate, and enhance their research results using feedback from Alexa customers.”

Photo of Participants in the Alexa Prize TaskBot Challenge Bootcamp
The Alexa Prize TaskBot Bootcamp was held in Seattle, Washington, with representatives from all ten university teams.

The teams selected for the challenge, which began in January, feature five returning entrants — including the top three finishers in the most recent challenge — and five new universities.

Team

University

Faculty advisor

Returning

TWIZNOVA School of Science and TechnologyJoão Magalhães
EvoquerBOTPenn State UniversityRui Zhang
Taco 2.0The Ohio State UniversityHuan Sun
GRILLUniversity of GlasgowJeff Dalton
MarunaUniversity of Massachusetts AmherstHamed Zamani

New

BoilerBotPurdue UniversityJulia Rayz
DiWBotRutgers UniversityMatthew Stone
SageUniversity of California, Santa CruzXin (Eric) Wang
ISABELUniversity of PittsburghMalihe Alikhani
PLAN-BotVirginia TechIsmini Lourentzou

The prizes for overall performance in the competition will be $500,000 for the first-place team, $100,000 for second, and $50,000 for third. Those prizes will be paid out to the students on the teams with the best overall performance.

“I am delighted to see that new teams are joining the second year of the competition together with returning teams, who, by competing again, are signaling to us that they found value in the TaskBot challenge, said Yoelle Maarek, vice president research and science for Amazon Shopping.  

“We expect these talented graduate students to continue surprising us, as well as Amazon customers, this year. Connecting academia, Amazonians, and actual customers experimenting with taskbots, is a winning combination to keep pushing the boundaries of science in conversational AI for Alexa to delight and ease the lives of millions of customers.”

The Alexa Prize is a competition for university students dedicated to advancing the field of conversational AI. Launched in 2016, the program was created to recognize students from around the globe who are changing the way we interact with technology.

TaskBot Challenge 2 teams are working to address one of the hardest problems in conversational AI — creating next-generation conversational AI experiences that delight customers by addressing their changing needs as they complete complex tasks. This challenge builds upon the Alexa Prize’s foundation of providing universities a unique opportunity to test cutting-edge machine learning models with actual customers at scale.

The Alexa Prize TaskBot challenge provides a realistic scenario with real-user multimodal interactions, making this the perfect setting to observe and measure human-bot conversations and AI algorithms in a groundbreaking setting.
rafael_ferreira_twiz.jpg
Rafael Ferreira, NOVA School of Science and Technology, Team TWIZ
Our vision of EvoquerBOT combines improving task completion rates and elevating user satisfaction. To this end, we deliver innovative solutions to fundamental NLP challenges.
haoran_zhang.jpeg
Haoran Zhang, Penn State University, Team EvoquerBOT
We are especially interested in developing innovative ways to achieve successful coordination of multiple modalities, such as visual and verbal elements, and create a more engaging and intuitive user experience.
Lingbo_Mo.JPG
Lingbo Mo, The Ohio State University, Team Taco 2.0
The GRILL team is excited to continue bringing cutting-edge AI research to improve people’s lives. Our research team works on new capabilities of foundation models that understand text, images, and the surrounding world.
Sophie_portrait.jpg
Sophie Fischer, University of Glasgow, Team GRILL
The competition lets us create interfaces for the general public in a production environment – it’s a unique opportunity to connect our research with our career goals.
Baber (Rutgers).jpeg
Baber Khalid, Rutgers University, Team DiWBot
We are very excited to be part of the community and look forward to working with the Alexa team and other teams.
Anthony_Sicilia.jpg
Anthony Sicilia, University of Pittsburgh, Team ISABEL
The Alexa Prize TaskBot Challenge combines a vast range of tasks over multiple domains with multimodal outputs. This is the ultimate test for any moonshot concept, and we can't wait to see what the real world has in store for us.
purdue 2.jpg
Rey (Alex) Gonzalez, Purdue University, Team BoilerBot
Participating in this competition is an incredible opportunity that will allow us to do applied research and ship it to real users.
ChrisSamarinas_DSC02670.jpg
Chris Samarinas, University of Massachusetts Amherst, Team Maruna
Although artificial intelligence has experienced explosive development in the past decade, there is still a gap between research and real-world application. The TaskBot Challenge provides us with a unique opportunity to explore multimodal AI in practical situations.
UCSC Kaishi TB2.png
Kaizhi Zheng Univerisity of California, Santa Cruz-Amherst, Team Sage
Our bot will make adaptable conversation a reality by allowing customers to follow personalized decisions through the completion of multiple, sequential sub-tasks and adapt to the tools, materials, or ingredients available to the user by proposing appropriate substitutes and alternatives.
Afrina Tabassum
Afrina Tabassum

TaskBot is the first conversational AI challenge to incorporate multimodal customer experiences, so in addition to receiving verbal instructions, customers with Echo Show or Fire TV devices, can also be presented with step-by-step instructions, images, or diagrams that enhance task guidance.

This year’s challenge has been expanded to include more hobbies and at-home activities. Participating teams were asked to propose interesting ways to incorporate visual aids into every conversation turn when a screen is available. Innovative ideas on improving the presentation of visual aids, as well as the coordination of visual and verbal modalities, were part of the team selection criteria.

Each university selected for the challenge receives a $250,000 research grant, Alexa-enabled devices, free Amazon Web Services (AWS) cloud computing services to support their research and development efforts, access to Amazon scientists, the CoBot (conversational bot) toolkit and other tools such as automated speech recognition through Alexa, neural detection and generation models, conversational data sets, and design guidance and development support from the Alexa Prize team.

"Alexa, let's work together"

The university teams’ taskbots will be available for Alexa customers to engage with in May 2023 with a finals event being held in September, and winners announced later that month.

As with the previous challenge, Alexa customers can engage in conversation with teams’ taskbots when they become available in May by saying, “Alexa, let’s work together.” Until then, “Alexa, let’s work together” will direct you to conversations with the previous challenge winners of 2022 and the Alexa Prize TaskBot.

After initiating the interaction, Alexa customers then receive a brief message informing them that they are interacting with an Alexa Prize university taskbot before being randomly connected to one of the participating taskbots.

After exiting the conversation with the taskbot, which customers can do at any time, the customer is prompted for a verbal rating, followed by an option to provide additional feedback. The interactions, ratings, and feedback are shared with the teams to help them improve their taskbots. Customer ratings are also used to determine which university teams will move on to the semifinals and finals.

Our goal is to contribute to the multimodal conversational AI field and move it closer to the way humans perceive, reason, and communicate through multimodal information.
joao_magalhaes_twiz.jpg
João Magalhães, associate professor, NOVA School of Science and Technology, Team TWIZ
We look forward to the Challenge because it is the perfect platform to create multimodal, tasked-oriented dialogue systems that elevate user experience and engagement.
rui_zhang.jpeg
Rui Zhang, assistant professor, Penn State University, Team EvoquerBOT
Through this TaskBot Challenge, we hope our work can expand the horizon of conversational AI along dimensions like dialogue depth, multi-modal coordination, commonsense reasoning, and learning from use.
Huan_Sun.png
Huan Sun, associate professor, The Ohio State University, Team Taco 2.0
The GRILL team is creating the next generation of open assistants that understand and use knowledge about the world and can communicate effectively to inform and educate.
jeff.jpeg
Jeff Dalton, associate professor, University of Glasgow, Team GRILL
Our TaskBot will help people get things done through personalized, adaptive, and context-aware conversational interaction by combining our research results with the state-of-the-art capabilities of Alexa devices.
Matthew Stone (Rutgers).jpg
Matthew Stone, professor, Rutgers University, Team DiWBot
We work towards making conversational AI technology more inclusive and collaborative. Inclusive Alexa can collaborate with users from diverse cultures and with different communication capabilities and preferences.
Malihe_Alikhani.jpg
Malihe Alikhani, assistant professor, University of Pittsburgh, Team ISABEL
We hope to develop a task-oriented system that can interact with users based on their level of knowledge, experience, and communication preference.
purdue 1.jpg
Julia Rayz, professor, Purdue University, Team BoilerBot

Success in the previous TaskBot Challenge required teams to address many difficult AI obstacles. The challenge required the fusion of multiple AI techniques including knowledge representation and inference, commonsense and causal reasoning, and language understanding and generation.

The “GRILLBot” team from University of Glasgow won the TaskBot 1 Challenge, earning a $500,000 prize for its performance. Teams from NOVA School of Science and Technology (Portgual) and The Ohio State University earned second- and third-place prizes, respectively.

Research papers from Amazon’s Alexa Prize team, and each of the competing teams, can be viewed and downloaded here.

Alexa Prize Taskbot Challenge Finals | Amazon Science

Research areas

Latest news

The latest updates, stories, and more about Alexa Prize.
IN, TN, Chennai
DESCRIPTION The Digital Acceleration (DA) team in India is seeking a talented, self-driven Applied Scientist to work on prototyping, optimizing, and deploying ML algorithms for solving Digital businesses problems. Key job responsibilities - Research, experiment and build Proof Of Concepts advancing the state of the art in AI & ML. - Collaborate with cross-functional teams to architect and execute technically rigorous AI projects. - Thrive in dynamic environments, adapting quickly to evolving technical requirements and deadlines. - Engage in effective technical communication (written & spoken) with coordination across teams. - Conduct thorough documentation of algorithms, methodologies, and findings for transparency and reproducibility. - Publish research papers in internal and external venues of repute - Support on-call activities for critical issues BASIC QUALIFICATIONS - Experience building machine learning models or developing algorithms for business application - PhD, or a Master's degree and experience in CS, CE, ML or related field - Knowledge of programming languages such as C/C++, Python, Java or Perl - Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing - Proficiency in coding and software development, with a strong focus on machine learning frameworks. - Understanding of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc. - Excellent communication skills (written & spoken) and ability to collaborate effectively in a distributed, cross-functional team setting. PREFERRED QUALIFICATIONS - 5+ years of building machine learning models or developing algorithms for business application experience - Have publications at top-tier peer-reviewed conferences or journals - Track record of diving into data to discover hidden patterns and conducting error/deviation analysis - Ability to develop experimental and analytic plans for data modeling processes, use of strong baselines, ability to accurately determine cause and effect relations - Exceptional level of organization and strong attention to detail - Comfortable working in a fast paced, highly collaborative, dynamic work environment
US, WA, Seattle
Are you seeking an environment where you can drive innovation? WW Amazon Stores Finance Science (ASFS) works to leverage science and economics to drive improved financial results, foster data backed decisions, and embed science within Finance. ASFS is focused on developing products that empower controllership, improve financial planning by understanding financial drivers, and innovate science capabilities for efficiency and scale. Our team owns sophisticated science capabilities for forecasting the WW Amazon Stores P&L, focusing on costs and the bottomline (profitability). We are looking for an outstanding Senior economist to lead new high visibility initiatives for forecasting the WW Amazon Stores P&L (focusing on costs and the bottomline). The forecasting models will be used to enable better financial planning and decision making for senior leadership up to VP level. You will build new econometric models from the ground up. The role will develop new driver based forecasting models for Retail related P&L lines that incorporate business drivers. The Sr Economist will also help generate new insights on how macroeconomic factors impact the P&L. This role will have very high visibility with senior leadership up to VP level. We prize creative problem solvers with the ability to draw on an expansive methodological toolkit to transform financial planning and decision-making through economics. The ideal candidate combines econometric acumen with strong business judgment. You have versatile modeling skills and are comfortable owning and extracting insights from data. You are excited to learn from and alongside seasoned scientists, engineers, economists, and business leaders. You are an excellent communicator and effectively translate technical findings into business action.
US, CA, East Palo Alto
The Customer Engagement Technology team leads AI/LLM-driven customer experience transformation using task-oriented dialogue systems. We develop multi-modal, multi-turn, goal-oriented dialog systems that can handle customer issues at Amazon scale across multiple languages. These systems are designed to adapt to changing company policies and invoke correct APIs to automate solutions to customer problems. Additionally, we enhance associate productivity through response/action recommendation, summarization to capture conversation context succinctly, retrieving precise information from documents to provide useful information to the agent, and machine translation to facilitate smoother conversations when the customer and agent speak different languages. Key focus areas include: 1. Task-Oriented Dialog Systems: Building reliable, scalable, and adaptive LLM-based agents for understanding intents, determining eligibilities, making API calls, confirming outcomes, and exploring alternatives across hundreds of customer service intents, while adapting to changing policies. 2. Lifelong Learning: Researching continuous learning approaches for injecting new domain knowledge while retaining the model's foundational abilities and prevent catastrophic forgetting. 3. Agentic Systems: Developing a modular agentic framework to handle multi domain conversations through appropriate system abstractions. 4. Complex Multi-turn Instruction Following: Identifying approaches to guarantee compliance with instructions that specify standard operating procedures for handling multi-turn complex scenarios. 5. Inference-Time Adaptability: Researching inference-time scaling methods and improving in-context learning abilities of custom models to enable real-time adaptability to new features, actions, or bug fixes without solely relying on retraining. 6. Context Adherence: Exploring methods to ground responses in specific customer attributes, account information, and behavioral data to prevent hallucinations and ensure high-fidelity responses. 7. Policy Grounding: Investigating techniques to align bot behavior with evolving company policies by grounding on complex, unstructured policy documents, ensuring consistent and compliant actions. 1. End to End Dialog Policy Optimization: Researching alignment approaches to optimize successful dialog completions. 2. Scalable Evaluations: Developing automated approaches to evaluate quality of experience, and correctness of agentic resolutions Key job responsibilities 1. Research and development of LLM-based chatbots and conversational AI systems for customer service applications. 2. Design and implement state-of-the-art NLP and ML models for tasks such as language understanding, dialogue management, and response generation. 3. Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to integrate LLM-based solutions into Amazon's customer service platforms. 4. Develop and implement strategies for data collection, annotation, and model training to ensure high-quality and robust performance of the chatbots. 5. Conduct experiments and evaluations to measure the performance of the developed models and systems, and identify areas for improvement. 6. Stay up-to-date with the latest advancements in NLP, LLMs, and conversational AI, and explore opportunities to incorporate new techniques and technologies into Amazon's customer service solutions. 7. Collaborate with internal and external research communities, participate in conferences and publications, and contribute to the advancement of the field.
CN, 11, Beijing
职位:Applied scientist 应用科学家实习生 毕业时间:2025年10月 - 2026年9月之间毕业的应届毕业生 · 入职日期:2025年6月及之前 · 实习时间:保证一周实习4-5天全职实习,至少持续5个月 · 工作地点:北京朝阳区酒仙桥路恒通商务园区 · 校招信息请参考校园招聘申请手册: https://amazonexteu.qualtrics.com/CP/File.php?F=F_55YI0e7rNdeoB6e 投递须知: 1 填写简历申请时,请把必填和非必填项都填写完整。提交简历之后就无法修改了哦! 2 学校的英文全称请准确填写。 如果您正在攻读计算机视觉、生成式AI或多模态领域的博士或硕士研究生,而且对应用科学家的实习工作感兴趣。 如果您也喜爱深入研究棘手的技术问题并提出解决方案,用成功的产品显著地改善人们的生活。 那么,我们诚挚邀请您加入亚马逊的International Technology自动化营销团队改善亚马逊节假日促销的用户体验。我们的目标是帮助亚马逊的客户找到他们所需的产品,并发现他们感兴趣的新产品。 这会是一份收获满满的工作。您每天的工作都与全球数百万亚马逊客户的体验紧密相关。您将提出和探索LLM和CV领域的创新,例如如何精准控制最前沿的基座大语言模型和图像生成模型以满足自动化的需求。您将集成这些模型到工具链中生成个性化的促销广告图,通过标注数据、建模和客户反馈来完成闭环。您对模型的选择需要能够平衡业务指标和响应时间的需求。
CN, 11, Beijing
职位:Applied scientist 应用科学家实习生 毕业时间:2025年10月 - 2026年9月之间毕业的应届毕业生 · 入职日期:2025年6月及之前 · 实习时间:保证一周实习4-5天全职实习,至少持续3个月 · 工作地点:北京朝阳区酒仙桥路恒通商务园区 · 校招信息请参考校园招聘申请手册: https://amazonexteu.qualtrics.com/CP/File.php?F=F_55YI0e7rNdeoB6e 投递须知: 1 填写简历申请时,请把必填和非必填项都填写完整。提交简历之后就无法修改了哦! 2 学校的英文全称请准确填写。 如果您正在攻读NLP,IR或搜索领域专业的博士或硕士研究生,而且对应用科学家的实习工作感兴趣。如果您也喜爱深入研究棘手的技术问题并提出解决方案,用成功的产品显著地改善人们的生活。 那么,我们诚挚邀请您加入亚马逊的International Technology搜索团队改善Amazon的产品搜索服务。我们的目标是帮助亚马逊的客户找到他们所需的产品,并发现他们感兴趣的新产品。 这会是一份收获满满的工作。您每天的工作都与全球数百万亚马逊客户的体验紧密相关。您将提出和探索NLP和IR领域的创新,基于TB级别的产品和流量数据设计机器学习模型。您将集成这些模型到搜索引擎中为客户提供服务,通过数据,建模和客户反馈来完成闭环。您对模型的选择需要能够平衡业务指标和响应时间的需求。
US, CA, San Diego
Amazon Games is seeking a highly effective Senior Machine Learning Scientist to build and integrate novel ML, RL and Generative AI (Gen AI) approaches into our game pipelines and customer experiences. In this role, you will work closely with our game development studios and operations teams to research and develop generative AI-powered tools, pipelines and features across Amazon Games. At Amazon Games, our ambition is to create bold new experiences that foster community in and around our games. Our team of game industry veterans develops AAA multiplayer games and original IPs, with teams in Seattle, Orange County, San Diego, Montreal, and Bucharest. Amazon Games, through its Studios, Publishing, and Prime Gaming divisions collaborating with external partners, aims to develop, publish, and deliver compelling AAA games and content experiences for gamers to discover. Key job responsibilities - Drive the research, implementation, and productionizing for ambitious and complex AI/ML initiatives for Amazon Games. - Collaborate with game team engineers, designers and artists to design, develop, and integrate new generative AI tools into developer workflows. - Proactively identify and solve problems that affect the quality of life for players, operations, and other developers. - Stay up to date with and analyze the latest advancements, in generative AI technology, and continuously improve product features where meaningful improvements in cost, scalability, quality, or functionality can be achieved. - Consult and contribute to evaluations of other internal or 3rd ML, RL and Gen AI services that could be leveraged by the project or the organization. A day in the life - You thrive in a collaborative environment where your decisions have significant impact and influence. - You are passionate about building game experiences that delight players. - You deliver great workflows, tools, and game innovations to your fellow developers and constantly seek improvement. - You want to be part of something exciting and unique in the gaming ecosystem. About the team The Amazon Games Studio AI Research team focuses on artificial intelligence innovation in gaming. Our highly skilled, multi-discipline team works across Machine Learning, Reinforcement Learning, and Generative AI to reimagine game development. We work closely with first-party game developers and partner studios to bring creative visions to life. Our mission is to use AI responsibly to transform gameplay experiences, enrich narratives, and provide creators with practical tools to optimize their production pipelines.
CA, QC, Montreal
Amazon Games recherche un.e scientifique en apprentissage automatique sénior.e pour développer et intégrer de nouvelles approches d'apprentissage automatique (ML), d'apprentissage par renforcement (RL) et d'IA générative (Gen AI) dans nos processus de développement de jeux et dans nos expériences de jeux. Dans ce rôle, vous travaillerez en étroite collaboration avec nos studios de développement de jeux et nos équipes opérationnelles pour imaginer et développer des outils, des processus et des fonctionnalités alimentés par l'IA générative à travers Amazon Games. Chez Amazon Games, notre ambition est de créer de expériences inédites et audacieuses qui rassemblent et cultivent les communautés de joueurs et de joueuses. Notre équipe d'experts de l'industrie développe des jeux multijoueurs AAA et des propriétés intellectuelles originales, avec des équipes à Seattle, Orange County, San Diego, Montréal et Bucarest. À travers nos divisions - Studios, Publishing et Prime Gaming et en collaboration avec des partenaires externes, nous développons, publions et livrons des jeux et des expériences de contenu exceptionnelles pour les joueurs et joueuses. /// Amazon Games is seeking a highly effective Senior Machine Learning Scientist to build and integrate novel ML, RL and Generative AI (Gen AI) approaches into our game pipelines and customer experiences. In this role, you will work closely with our game development studios and operations teams to research and develop generative AI-powered tools, pipelines and features across Amazon Games. At Amazon Games, our ambition is to create bold new experiences that foster community in and around our games. Our team of game industry veterans develops AAA multiplayer games and original IPs, with teams in Seattle, Orange County, San Diego, Montreal, and Bucharest. Amazon Games, through its Studios, Publishing, and Prime Gaming divisions collaborating with external partners, aims to develop, publish, and deliver compelling AAA games and content experiences for gamers to discover. Key job responsibilities Responsabilités - Diriger la recherche, l'implémentation et la mise en production d'initiatives ambitieuses et complexes en IA/ML pour Amazon Games. - Collaborer avec les équipes de programmation, de conception et artistique pour concevoir, développer et intégrer de nouveaux outils d'IA générative dans les flux de travail des développeuses et développeurs. - Identifier et résoudre de manière proactive les problèmes qui affectent la qualité de vie des joueurs, des opérations et des autres développeurs. - Se tenir au courant et analyser les dernières avancées en matière de technologie d'IA générative, et améliorer continuellement les fonctionnalités des produits lorsque des améliorations significatives en termes de coût, d'évolutivité, de qualité ou de fonctionnalité peuvent être réalisées. - Consulter et contribuer aux évaluations d'autres services internes ou tiers de ML, RL et Gen AI qui pourraient être utilisés par le projet ou l'organisation. /// Responsibilities - Drive the research, implementation, and productionizing for ambitious and complex AI/ML initiatives for Amazon Games. - Collaborate with game team engineers, designers and artists to design, develop, and integrate new generative AI tools into developer workflows. - Proactively identify and solve problems that affect the quality of life for players, operations, and other developers. - Stay up to date with and analyze the latest advancements, in generative AI technology, and continuously improve product features where meaningful improvements in cost, scalability, quality, or functionality can be achieved. - Consult and contribute to evaluations of other internal or 3rd ML, RL and Gen AI services that could be leveraged by the project or the organization. A day in the life Une journée type - Vous vous épanouissez dans un environnement collaboratif où vos décisions ont un impact et une influence significatifs. - Vous exprimer votre passion par la création d'expériences de jeu qui ravissent les joueurs et les joueuses. - Vous proposez d'excellents flux de travail, outils et innovations de jeu à vos collègues et aux équipes de développement et recherchez constamment l'amélioration. - Vous souhaitez faire partie de quelque chose d'excitant et unique dans l'écosystème du jeu. /// A day in the life - You thrive in a collaborative environment where your decisions have significant impact and influence. - You are passionate about building game experiences that delight players. - You deliver great workflows, tools, and game innovations to your fellow developers and constantly seek improvement. - You want to be part of something exciting and unique in the gaming ecosystem. About the team À propos de l'équipe L'équipe de recherche en IA d'Amazon Games Studio se concentre sur l'innovation en intelligence artificielle dans le domaine du jeu vidéo. Notre équipe hautement qualifiée et multidisciplinaire travaille sur l'apprentissage automatique, l'apprentissage par renforcement et l'IA générative pour réinventer le développement des jeux. Nous travaillons de près avec les équipe internes et nos studios partenaires pour donner vie à leur vision créative. Notre mission est d'utiliser l'IA de manière responsable pour transformer l'expérience de jeu, enrichir les récits, et fournir aux créateurs et créatrices des outils pratiques pour optimiser leurs chaînes de production. /// About the Team The Amazon Games Studio AI Research team focuses on artificial intelligence innovation in gaming. Our highly skilled, multi-discipline team works across Machine Learning, Reinforcement Learning, and Generative AI to reimagine game development. We work closely with first-party game developers and partner studios to bring creative visions to life. Our mission is to use AI responsibly to transform gameplay experiences, enrich narratives, and provide creators with practical tools to optimize their production pipelines.
IL, Haifa
Come build the future of entertainment with us. Are you interested in helping shape the future of movies and television? Do you want to help define the next generation of how and what Amazon customers are watching? 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 from Originals and Exclusive content to exciting live sports events. We also offer our members the opportunity to subscribe to add-on channels which they can cancel at any time and to rent or buy new release movies and TV box sets on the Prime Video Store. Prime Video is a fast-paced, growth business - available in over 240 countries and territories worldwide. The team works in a dynamic environment where innovating on behalf of our customers is at the heart of everything we do. If this sounds exciting to you, please read on We are seeking an exceptional Applied Scientist to join our Prime Video Sports tech team in Israel. Our team is dedicated to developing state-of-the-art science to allow for personalizing the customers’ experience and customers to seamlessly find any live event in our selection. You will have the opportunity to work on innovative, large-scale projects that push the boundaries of what's possible in sports content delivery and engagement. Your expertise will be crucial in tackling complex challenges such as temporal information retrieval, leveraging Generative AI and Large Language Models (LLMs), and building state-of-the-art recommender systems. Key job responsibilities We are looking for an Applied Scientist with domain expertise in Personalization, Information Retrieval, and Recommender Systems, or general ML to lead the development of new algorithms and end-to-end solutions. As part of our team of applied scientists and software development engineers, you will be responsible for researching, designing, developing, and deploying algorithms into production pipelines. Your role will involve working with cutting-edge technologies such as Gen AI/LLMs to enhance content discovery and search capabilities. You'll also tackle unique challenges like temporal information retrieval to improve real-time sports content recommendations. As a technologist, you will drive the publication of original work in top-tier conferences in Machine Learning and Information Retrieval. We expect you to thrive in ambiguous situations, demonstrating outstanding analytical abilities and comfort in collaborating with cross-functional teams and systems. The ideal candidate is a self-starter with the ability to learn and adapt quickly in our fast-paced environment. About the team We are the Prime Video Sports team. In September 2018 Prime Video launched its first full-scale live streaming experience to world-wide Prime customers with NFL Thursday Night Football. That was just the start. Now Amazon has exclusive broadcasting rights to major leagues like NFL Thursday Night Football, Tennis major like Roland-Garros and English Premium League to list few and are broadcasting live events across 30+ sports world-wide. Prime Video is expanding not just the breadth of live content that it offers, but the depth of the experience. This is a transformative opportunity, the chance to be at the vanguard of a program that will revolutionize Prime Video, and the live streaming experience of customers everywhere.
IL, Haifa
Come build the future of entertainment with us. Are you interested in helping shape the future of movies and television? Do you want to help define the next generation of how and what Amazon customers are watching? 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 from Originals and Exclusive content to exciting live sports events. We also offer our members the opportunity to subscribe to add-on channels which they can cancel at any time and to rent or buy new release movies and TV box sets on the Prime Video Store. Prime Video is a fast-paced, growth business - available in over 240 countries and territories worldwide. The team works in a dynamic environment where innovating on behalf of our customers is at the heart of everything we do. If this sounds exciting to you, please read on. We are seeking an exceptional Sr. Applied Scientist to join our Prime Video Sports tech team in Israel. Our team is dedicated to developing state-of-the-art science to allow for personalizing the customers’ experience and customers to seamlessly find any live event in our selection. You will have the opportunity to work on innovative, large-scale projects that push the boundaries of what's possible in sports content delivery and engagement. Your expertise will be crucial in tackling complex challenges such as temporal information retrieval, leveraging Generative AI and Large Language Models (LLMs), and building state-of-the-art recommender systems. Key job responsibilities We are looking for a Senior Applied Scientist with domain expertise in Personalization, Information Retrieval, and Recommender Systems, or general ML to lead the development of new algorithms and end-to-end solutions. As part of our team of applied scientists and software development engineers, you will be responsible for researching, designing, developing, and deploying algorithms into production pipelines. Your role will involve working with cutting-edge technologies such as GenAI/LLMs to enhance content discovery and search capabilities. You'll also tackle unique challenges like temporal information retrieval to improve real-time sports content recommendations. As a technologist, you will drive the publication of original work in top-tier conferences in Machine Learning and Information Retrieval. We expect you to thrive in ambiguous situations, demonstrating outstanding analytical abilities and comfort in collaborating with cross-functional teams and systems. The ideal candidate is a self-starter with the ability to learn and adapt quickly in our fast-paced environment. About the team We are the Prime Video Sports team. As part of this team, you will be working on the science behind the Discovery, Personalization and Search experiences of PV Sports. In September 2018 Prime Video launched its first full-scale live streaming experience to world-wide Prime customers with NFL Thursday Night Football. That was just the start. Now Amazon has exclusive broadcasting rights to major leagues like NFL Thursday Night Football, Tennis major like Roland-Garros and English Premium League to list few and are broadcasting live events across 30+ sports world-wide. Prime Video is expanding not just the breadth of live content that it offers, but the depth of the experience. This is a transformative opportunity, the chance to be at the vanguard of a program that will revolutionize Prime Video, and the live streaming experience of customers everywhere.
IN, Hyderabad
Customer addresses, Geospatial information and Road-network play a crucial role in Amazon Logistics' Delivery Planning systems. We own exciting science problems in the areas of Address Normalization, Geocode learning, Maps learning, Time estimations including route-time, delivery-time, transit-time predictions which are key inputs in delivery planning. As part of the Geospatial science team within Last Mile, you will partner closely with other scientists and engineers in a collegial environment to develop enterprise ML solutions with a clear path to business impact. The setting also gives you an opportunity to think about a complex large-scale problem for multiple years and building increasingly sophisticated solutions year over year. In the process there will be opportunity to innovate, explore SOTA and publish the research in internal and external ML conferences. Successful candidates will have deep knowledge of competing machine learning methods for large scale predictive modelling, natural language processing, semi-supervised & graph based learning. We also look for the experience to graduate prototype models to production and the communication skills to explain complex technical approaches to the stakeholders of varied technical expertise. Key job responsibilities As an Applied Scientist I, your responsibility will be to deliver on a well defined but complex business problem, explore SOTA technologies including GenAI and customize the large models as suitable for the application. Your job will be to work on a end-to-end business problem from design to experimentation and implementation. There is also an opportunity to work on open ended ML directions within the space and publish the work in prestigious ML conferences.