TaskBot Challenge FAQs

Frequently asked questions about the challenge.
TaskBot
What is a TaskBot?
A TaskBot is a conversational agent that assists customers in completing DIY and Cooking tasks requiring multiple steps and decisions. It is the second conversational AI challenge to incorporate multimodal (voice and vision) customer experiences.
Can I choose to build any type of conversational bot?
No, you must build a TaskBot.
What will my TaskBot do?
A TaskBot helps customers complete tasks that require multiple steps and decisions in target domains such as hobbies and at-home activities such as Home Improvement and Cooking. For example, customers could ask a TaskBot to help them “bake a healthy birthday cake”. A successful TaskBot will be able to discuss different approaches to nutrition and understand individual customer’s preferences. It would then walk the customer through baking a cake step-by-step, while solving problems arising along the way, e.g., missing ingredients, and continue the conversation over multiple-days sessions.
How will I build my TaskBot?
You will use the Alexa Skills Kit (ASK) to build an Alexa skill, hosted on AWS Lambda that will create the end-to-end conversational experience for a user. Using the provided APIs, your skill will receive as input the text of the user’s utterance, and produce as output a text sentence that will be spoken to the user. You do not need to tackle ASR (automatic speech recognition) or TTS (text to speech). You will also be provided with the TaskBot Toolkit (a conversational bot toolkit), a software development kit that works with ASK and was built specifically for Alexa Prize teams to reduce the involved engineering in setting up a TaskBot and allow teams to focus on the science.


Your skill will need to determine an appropriate response at each turn of the conversation. You may use additional data sources or libraries if you wish, subject to the terms described in the Official Rules.
What is the Alexa Skills Kit (ASK)?
The Alexa Skills Kit (ASK) is a collection of free, self-service APIs, tools, documentation, and code samples that make it fast and easy for you to add skills to Alexa. Your team will use ASK to build, deploy, and test a TaskBot that is capable of conversing with millions of Alexa users.
What is TaskBot toolkit?
TaskBot, is a conversational bot toolkit in Python for natural language understanding and dialog management. The toolkit provides a set of tools, libraries and base models designed to help develop, train and deploy multimodal conversational experiences through the Alexa Skills Kit (ASK), and to provide uniform visual look for TaskBots on screened devices. The primary goal of the toolkit is to drive improved quality of conversational agents by providing a solution that is modular, extensible, and scalable, and provide abstractions for infrastructure and low-level tasks.
Competition details
How will winners be selected?
Through various phases of the competition, TaskBots will be evaluated based on feedback from Alexa users and assessment by Amazon.


Midway through the competition, all TaskBots that have been certified and published will be evaluated by Alexa users and Amazon. As defined in the Official Rules, TaskBots that meet the required criteria will advance to later phases of the competition and eventually the semifinals.



During the semifinals round, Alexa users will evaluate the semifinalist TaskBots. Two TaskBots selected by Alexa users and up to three TaskBots selected by the Amazon panel will advance to the finals. During the finals in September 2023, the finalist teams will compete head-to-head in front of judges. The judges will score the TaskBots on their ability to successfully complete the task requested.
Will this competition be judged like a Turing Test?
No. The goal of the Alexa Prize is to create TaskBots that fluently and effectively assist the user, not to make them indistinguishable from a human when compared side-by-side. While the TaskBots built for the Alexa Prize will be human-like in some respects, they will be very different in others, and could easily reveal themselves in a Turing Test. For example, TaskBots may have ready access to much more information than a human. Asking the TaskBots to act like a human could diminish the customer experience and hinder the efforts of the participants to build the best TaskBot to further conversational AI.
When and where is the finals event?
The finals event will be held in September 2023 at a location to be determined, with the results will be announced in September 2023.
Can we use other funding to help us participate in this challenge?
Yes, you may use other funding to support your team, subject to the terms described in the Official Rules. External funding must be disclosed to Amazon.
Can we use technology other than AWS to host our TaskBot?
Your team may build its TaskBot in any framework of your choosing, but the TaskBot must be hosted on AWS to leverage Alexa’s TaskBot toolkit.
Will Alexa customers be able to engage with our TaskBot?
Your team will be required to submit its TaskBot for certification and publication by the Amazon Alexa team. After certification, you will enter the Internal Amazon Beta Period, where Amazon employees will test your TaskBot and provide feedback. After the Internal Amazon Beta Period, we will allow Alexa users to try your TaskBot and provide feedback to you. Amazon may impose requirements that the TaskBots must meet before they will be made available to Alexa users. Such requirements, specified in the Official Rules, may include, among other things, a minimum average customer rating, uptime requirements, or the ability to consistently filter offensive content.
Which Alexa users will be able to interact with the TaskBots, and what languages must they support?
TaskBots will be made available to Alexa users in the United States or who select the United States as their preferred marketplace. Your team must build its TaskBot using U.S. English.
Will we publish our research from the Alexa Prize?
Yes. Publishing research papers as an outcome of your work on Alexa Prize is required for all teams participating in the competition, although teams may not publish Amazon confidential information, as described in the Official Rules. The Alexa Prize requires all teams to submit a technical paper for the Alexa Prize proceedings. Your TaskBot will not be selected for the finals if your team does not submit a technical paper for Alexa Prize proceedings. Papers will be published online at the end of the competition and made publicly available.


Teams may also publish research papers in third-party publications and conferences, as long as all papers are provided to Amazon for review at least two weeks before the submission deadlines and no research papers are published before the Alexa Prize proceedings are published, unless Amazon approves otherwise in writing.
Who will own the intellectual property rights in my submission?
You will retain ownership over your TaskBot. Amazon will have a non-exclusive license to any technology or software you develop in connection with the competition. See the Official Rules for details.
Eligibility
Who can apply to participate?
The Alexa Prize is open to full-time students enrolled in an accredited university, with the exception of universities in Cuba, Iran, Syria, North Korea, Sudan, the region of Crimea, and where prohibited by law (see Official Rules). Proof of enrollment will be required to participate.
Can I participate if I don’t attend a university?
No. The Alexa Prize is open only to full-time enrolled university students.
Do I need to be enrolled in a university program throughout my participation in the competition?
All participating team members must remain full-time students in good standing at their university while participating in the competition.
Do I need to be a certain age?
Participants must be at or above the age of majority in the country, state, province or jurisdiction of residence at the time of entry.
Can I enroll if a family member is an Amazon employee?
Immediate family members and household members of Amazon employees, directors, and contractors are not eligible to participate. See Official Rules for additional restrictions.
Teams
How many teams will be selected to participate?
All applications will be reviewed and evaluated by Amazon. Up to ten teams will be selected and sponsored by Amazon. All teams will receive a $250,000 grant intended to support two full-time students and a month of faculty time, free Alexa devices, and free AWS hosting including access to CPU and GPU based machines, SQL and NoSQL databases, and object storage. See the Official Rules for details.
How many team members can our team have?
There is no minimum or maximum number of team members. All team members must be enrolled in their university throughout their participation. All teams will receive a $250,000 grant regardless of how many members are on the team. We recommend a team with 4-6 students with diverse fields of study or areas of expertise.
Can students from different universities be on the same team?
No. Teams must be comprised of students attending the same university.
Can one university have more than one team?
Yes, universities may have more than one team. Multiple teams cannot have the same faculty advisor.
Can I participate on two separate teams?
No. You can only be a part of one team for the duration of the competition.
Can undergraduate and graduate students work together?
Yes, teams may be comprised of undergraduate and graduate students.
Do I need a faculty advisor?
All teams must nominate a faculty advisor and include the faculty advisor’s consent in the applications.
What is the role of the faculty advisor?
Faculty advisors will advise students on technical directions and be a sounding board for new ideas, similar to a graduate school advisor. They will also act as the official representative from the university for this competition.
Can we add or remove team members during the competition?
During the competition, there will be a period of time during which faculty advisors may request to remove or add members to the team, subject to approval by Amazon. See the Official Rules for details.
Can we discuss our TaskBot with faculty or students who aren’t on our team?
Only team members may work on their TaskBots. However, the faculty advisor and other students and faculty members at your university may provide support and advice to your team and may co-author technical publications and research papers.
Application process
How do we apply?
Please fill in the Taskbot Challenge 2 application hosted on YouNoodle.
What do we need to apply?
Once you have selected your team members, team leader, and faculty sponsor, you are ready to begin the application process.
Do all team members have to apply?
Each team must have a team lead, who should submit only one application on behalf of the whole team. Your application must include all of your team members’ information.
Is there an application fee?
There is no application fee.
How will teams be selected to participate?
All applications will be reviewed by Amazon. Teams will be selected by Amazon based on the following criteria: (1) the potential scientific contribution to the field; (2) the technical merit of the approach; (3) the novelty of the idea; and (4) an assessment of the team’s ability to execute against their plan. Please be sure to provide enough detail in your application to enable evaluation of your proposal.
Prizes
What are the prizes for winning the competition?
A prize of $500,000 will be awarded to team that creates the best TaskBot. The second-place and third-place finalist teams will receive a $100,000 and a $50,000 prize, respectively. See the Official Rules for details.
Do we get a stipend and devices to participate in the Alexa Prize?
Up to ten teams will be sponsored to participate in the competition. Each sponsored team’s university will receive a $250,000 research grant to help fund the team’s participation.


The sponsorship includes Alexa-enabled devices, free AWS services to support the development of the team’s TaskBot, and support from the Alexa team.
How can the grant be spent?
The grants are intended to support two full-time students for the duration of the Competition and one month of the Faculty Advisor’s salary. No more than 35% of the research grant may be allocated to administrative fees. If your team would like to use the funds in another manner, your faculty advisor must receive approval from Amazon before doing so.
What happens if we are selected and receive a stipend but can no longer participate?
Stipends will be awarded in installments payable to the university. If your team withdraws before any of the installments, remaining funds will not be transferred to the university.
How will the prizes be distributed among a team?
The first, second, and third place prizes will be distributed equally among all registered team members.
Timeline
What are the key milestones of the competition?
Teams must submit their applications by early November, 2022. Teams selected to participate in the competition will be notified by early January, 2023. The competition will run from about January 2023 through September 2023. See the Official Rules for details.
More information
See the Official Rules or submit your questions. Need assistance? Email: alexaprizesupport@amazon.com

Latest news

The latest updates, stories, and more about Alexa Prize.
GB, London
We are looking for a passionate, talented, and inventive Data Scientist with a strong machine learning and analytics background to help build industry-leading language technology powering Rufus, our AI-driven search and shopping assistant, helping customers with their shopping tasks at every step of their shopping journey. This innovative role focuses on developing and optimizing large language model (LLM)-powered conversational experiences. The core emphasis is to get the best performance out of state-of-the-art LLMs via careful and methodical instruction design, contextual grounding, informed choices of MCP tools and agent/multi-agent systems, evaluation frameworks, and experimentation to systematically improve LLM quality, robustness, and customer impact. The work combines scientific rigor with product intuition to systematically raise the bar for conversational AI performance at Amazon scale. Our mission in conversational shopping is to make it easy for customers to find and discover the best products to meet their needs by helping with their product research, providing comparisons and recommendations, answering product questions, enabling shopping directly from images or videos, providing visual inspiration, and more. We do this by leveraging advanced analytics, Natural Language Processing (NLP), Machine Learning (ML), A/B testing, causal inference, and data-driven insights to continuously improve our systems. Key job responsibilities As a Data Scientist on our team, you will develop and maintain LLM instructions iterations and evaluation frameworks, including automated eval pipelines, LLM-as-a-judge methodologies, rubric design, and dataset curation to measure nuanced aspects of response quality. You will partner with the wider org to experiment with techniques such as retrieval augmentation, context enrichment, prompt decomposition, and model fine-tuning or post-training strategies, if and when applicable. You will leverage petabytes of data and identify opportunities to leverage machine learning models aimed at making conversational systems more performant. A day in the life You will: Perform hands-on analysis of large-scale multimodal interaction datasets to develop insights into how customers engage with conversational AI systems and how to improve response quality and customer experience. Use statistical methods, experimentation, and data-driven analysis to develop scalable approaches for measuring, evaluating, and optimizing large language model (LLM)-based shopping assistant systems, leveraging structured and unstructured contextual signals. Design and analyze A/B tests and experiments to evaluate new features and model improvements, ensuring statistical rigor and actionable insights. Develop metrics, dashboards, and reporting frameworks to monitor system performance, customer engagement, and business impact. Conduct deep-dive analyses to identify opportunities for improving conversational relevance, grounding, customer satisfaction, and downstream business impact. Collaborate with Applied Scientists and Engineers to translate analytical insights into production systems, working closely on model evaluation and deployment. Establish automated processes for large-scale data analysis, ETL pipelines, metric generation, and experimentation frameworks. Communicate results and insights to both technical and non-technical audiences, including through presentations, written reports, and data visualizations. About the team The Rufus Features Science team, based in London, works alongside ~150 engineers, designers and product managers, shaping the future of AI-driven shopping experiences at Amazon. The team works on every aspect of the Rufus AI, from making Rufus agentic, enabling customers to set price alerts or empower Rufus to act on their behalf and automatically purchase products when the price is right, to understanding multimodal user queries and generating answers that combine text, image, audio and video, including deep research reports that scour the web and the Amazon catalog to provide detailed and personalised shopping guidance. We utilize and advance state-of-art techniques in the fields of Natural Language Processing, gen AI, Information Retrieval, Machine/Deep Learning, and Data Mining. We validate our work by actively participating in the internal and external scientific communities.
CN, 44, Shenzhen
职位:Applied scientist 应用科学家实习生 毕业时间:2026年10月 - 2027年7月之间毕业的应届毕业生 · 入职日期:2026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:深圳福田区 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。中英文对应表请查这里(无法浏览请登录后浏览)https://docs.qq.com/sheet/DVmdaa1BCV0RBbnlR?tab=BB08J2 关于职位 Amazon Device &Services Asia团队正在寻找一位充满好奇心、善于沟通的应用科学家实习生,成为连接前沿AI研究与现实世界认知的桥梁。这是一个独特的角色——既需要动手参与机器学习项目,又要接受将复杂AI概念转化为通俗易懂内容的创意挑战。D&S Asia是亚马逊设备与服务业务在亚洲的支柱组织,自2009年支持Kindle制造起步,现已发展为横跨软硬件、AI(Alexa)及智能家居(Ring/Blink)的综合性团队,持续驱动区域业务创新与人才发展。 你将做什么 • 解密AI: 将复杂的技术发现转化为直观的解释、博客文章、教程或互动演示,让非技术背景的业务方和更广泛的社区都能理解 • 技术叙事: 与工程团队协作,以清晰、引人入胜的方式记录AI的能力与局限性 • 知识共享: 协助开发内部工作坊或"AI入门"课程,提升跨职能团队(产品、设计、商务)的AI素养 • 保持前沿: 持续学习并整合最新突破(如大语言模型、扩散模型、智能体),为团队输出简明易懂的趋势简报 • 研究与应用: 参与端到端的应用研究项目,从文献综述到原型开发,涵盖自然语言处理、计算机视觉或多模态AI领域
US, MA, N.reading
Amazon Industrial Robotics Group 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 an unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic dexterous 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 Group, we leverage advanced robotics, machine learning, and artificial intelligence to solve complex operational challenges at an 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 dexterous manipulation system that: - Enables unprecedented generalization across diverse tasks - Enables contact-rich manipulation in different environments - Seamlessly integrates low-level skills and high-level behaviors - Leverage mechanical intelligence, multi-modal sensor feedback and advanced control techniques. 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. A day in the life - Lead design and implementation of methods for Visual SLAM, navigation and spatial reasoning - Leverage simulation and real-world data collection to create large datasets for model development - Develop a hierarchical system that combines low-level control with high-level planning - Collaborate effectively with multi-disciplinary teams to co-design hardware and algorithms for dexterous manipulation
US, WA, Seattle
Amazon Prime is looking for an ambitious Economist Intern to help create econometric insights for world-wide Prime. Prime is Amazon's premiere membership program, with over 200M members world-wide. This role is at the center of many major company decisions that impact Amazon's customers. These decisions span a variety of industries, each reflecting the diversity of Prime benefits. These range from fast-free e-commerce shipping, digital content (e.g., exclusive streaming video, music, gaming, photos), reading, healthcare, and grocery offerings. Prime Science creates insights that power these decisions. As an economist intern in this role, you will create statistical tools that embed causal interpretations. You will utilize massive data, state-of-the-art scientific computing, econometrics (causal, counterfactual/structural, experimentation), and machine-learning, to do so. Some of the science you create will be publishable in internal or external scientific journals and conferences. You will work closely with a team of economists, applied scientists, data professionals (business analysts, business intelligence engineers), product managers, and software/data engineers. You will create insights from descriptive statistics, as well as from novel statistical and econometric models. You will create internal-to-Amazon-facing automated scientific data products to power company decisions. You will write strategic documents explaining how senior company leaders should utilize these insights to create sustainable value for customers. These leaders will often include the senior-most leaders at Amazon. The team is unique in its exposure to company-wide strategies as well as senior leadership. It operates at the research frontier of utilizing data, econometrics, artificial intelligence, and machine-learning to form business strategies. A successful candidate will have demonstrated a capacity for building, estimating, and defending statistical models (e.g., causal, counterfactual, machine-learning) using software such as R, Python, or STATA. They will have a willingness to learn and apply a broad set of statistical and computational techniques to supplement deep training in one area of econometrics. For example, many applications on the team motivate the use of structural econometrics and machine-learning. They rely on building scalable production software, which involves a broad set of world-class software-building skills often learned on-the-job. As a consequence, already-obtained knowledge of SQL, machine learning, and large-scale scientific computing using distributed computing infrastructures such as Spark-Scala or PySpark would be a plus. Additionally, this candidate will show a track-record of delivering projects well and on-time, preferably in collaboration with other team members (e.g. co-authors). Candidates must have very strong writing and emotional intelligence skills (for collaborative teamwork, often with colleagues in different functional roles), a growth mindset, and a capacity for dealing with a high-level of ambiguity. Endowed with these traits and on-the-job-growth, the role will provide the opportunity to have a large strategic, world-wide impact on the customer experiences of Prime members.
US, WA, Bellevue
The Mission Build AI safety systems that protect millions of Alexa customers every day. As conversational AI evolves, you'll solve challenging problems in Responsible AI by ensuring LLMs provide safe, trustworthy responses, building AI systems that understand nuanced human values across cultures, and maintaining customer trust at scale. What You'll Build You'll pioneer breakthrough solutions in Responsible AI at Amazon's scale. Imagine training models that set new safety standards, designing automated testing systems that hunt for vulnerabilities before they surface, and certifying the systems that power millions of daily conversations. You'll create intelligent evaluation systems that judge responses with human-level insight, build models that truly understand what makes interactions safe and delightful, and craft feedback mechanisms that help Alexa+ grasp the nuances of complex customer conversations. Here's where it gets even more exciting: you'll build AI agents that act as your team's safety net—automatically detecting and fixing production issues in real-time, often before anyone notices there was a problem. Your innovations won't just improve Alexa+; they'll fundamentally shape how it learns, evolves, and earns customer trust. As Alexa+ continues to delight customers, your work ensures it becomes more trustworthy, safer, and deeply aligned with customer needs and expectations. Your work directly protects customer trust at Amazon's scale. Every innovation you create—from novel safety mechanisms to sophisticated evaluation techniques—shapes how millions of people interact with AI confidently. You're not just building products; you're defining industry standards for responsible AI. This is frontier research with immediate real-world impact. You'll tackle problems that require innovative solutions: training models that remain truthful and grounded across diverse contexts, building reward models that capture the nuanced spectrum of human values across cultures and languages, and creating automated systems that continuously discover and address potential issues before customers encounter them. You'll collaborate with world-class scientists, product managers, and engineers to transform state-of-the-art ideas into production systems serving millions. What We're Looking For * Deep expertise in state-of-the-art NLP and Large Language Models * Track record of building scalable ML systems * Passion for impactful research—where frontier science meets real-world responsibility at scale * Excitement about solving problems that will shape the future of AI Ready to work on AI safety challenges that define the industry? Join us. Key job responsibilities This is where you'll make your mark. You'll architect breakthrough Responsible AI solutions that become industry benchmarks, pioneering algorithms that eliminate false information, designing frameworks that hunt down vulnerabilities before bad actors find them, and developing models that understand human values across every culture we serve. Working with world-class engineers and scientists, you'll push the boundaries of model training—transforming bold research into production systems that protect millions of customers daily while withstanding attacks and delivering exceptional experiences. But here's what makes this role truly special: you'll shape the future. You'll lead certification processes, advance optimization techniques, build evaluation systems that reason like humans, and mentor the next generation of AI safety experts. Every innovation you drive will set new standards for trustworthy AI at the world's largest scale. A day in the life As a Responsible AI Scientist, you're at the frontier of AI safety—experimenting with breakthrough techniques that push the boundaries of what's possible. You partner with engineering to transform research into production-ready solutions, tackling complex optimization challenges. You brainstorm with Product teams, translating ambitious visions into concrete objectives that drive real impact. Your expertise shapes critical deployment decisions as you review impactful work and guide go/no-go calls. You mentor the next generation of AI safety leaders, watching ideas spark and capabilities grow. This is where science meets impact—building AI that's not just intelligent, but trustworthy and aligned with human values. About the team Our team pioneers Responsible AI for conversational assistants. We ensure Alexa delivers safe, trustworthy experiences across all devices, modalities, and languages worldwide. We work on frontier AI safety challenges—and we're looking for scientists who want to help shape the future of trustworthy AI.
US, WA, Bellevue
The Mission Build AI safety systems that protect millions of Alexa customers every day. As conversational AI evolves, you'll solve challenging problems in Responsible AI by ensuring LLMs provide safe, trustworthy responses, building AI systems that understand nuanced human values across cultures, and maintaining customer trust at scale. What You'll Build You'll pioneer breakthrough solutions in Responsible AI at Amazon's scale. Imagine training models that set new safety standards, designing automated testing systems that hunt for vulnerabilities before they surface, and certifying the systems that power millions of daily conversations. You'll create intelligent evaluation systems that judge responses with human-level insight, build models that truly understand what makes interactions safe and delightful, and craft feedback mechanisms that help Alexa+ grasp the nuances of complex customer conversations. Here's where it gets even more exciting: you'll build AI agents that act as your team's safety net—automatically detecting and fixing production issues in real-time, often before anyone notices there was a problem. Your innovations won't just improve Alexa+; they'll fundamentally shape how it learns, evolves, and earns customer trust. As Alexa+ continues to delight customers, your work ensures it becomes more trustworthy, safer, and deeply aligned with customer needs and expectations. Your work directly protects customer trust at Amazon's scale. Every innovation you create—from novel safety mechanisms to sophisticated evaluation techniques—shapes how millions of people interact with AI confidently. You're not just building products; you're defining industry standards for responsible AI. This is frontier research with immediate real-world impact. You'll tackle problems that require innovative solutions: training models that remain truthful and grounded across diverse contexts, building reward models that capture the nuanced spectrum of human values across cultures and languages, and creating automated systems that continuously discover and address potential issues before customers encounter them. You'll collaborate with world-class scientists, product managers, and engineers to transform state-of-the-art ideas into production systems serving millions. What We're Looking For * Deep expertise in state-of-the-art NLP and Large Language Models * Track record of building scalable ML systems * Passion for impactful research—where frontier science meets real-world responsibility at scale * Excitement about solving problems that will shape the future of AI Ready to work on AI safety challenges that define the industry? Join us. Key job responsibilities This is where you'll make your mark. You'll architect breakthrough Responsible AI solutions that become industry benchmarks, pioneering algorithms that eliminate false information, designing frameworks that hunt down vulnerabilities before bad actors find them, and developing models that understand human values across every culture we serve. Working with world-class engineers and scientists, you'll push the boundaries of model training—transforming bold research into production systems that protect millions of customers daily while withstanding attacks and delivering exceptional experiences. But here's what makes this role truly special: you'll shape the future. You'll lead certification processes, advance optimization techniques, build evaluation systems that reason like humans, and mentor the next generation of AI safety experts. Every innovation you drive will set new standards for trustworthy AI at the world's largest scale. A day in the life As a Responsible AI Scientist, you're at the frontier of AI safety—experimenting with breakthrough techniques that push the boundaries of what's possible. You partner with engineering to transform research into production-ready solutions, tackling complex optimization challenges. You brainstorm with Product teams, translating ambitious visions into concrete objectives that drive real impact. Your expertise shapes critical deployment decisions as you review impactful work and guide go/no-go calls. You mentor the next generation of AI safety leaders, watching ideas spark and capabilities grow. This is where science meets impact—building AI that's not just intelligent, but trustworthy and aligned with human values. About the team Our team pioneers Responsible AI for conversational assistants. We ensure Alexa delivers safe, trustworthy experiences across all devices, modalities, and languages worldwide. We work on frontier AI safety challenges—and we're looking for scientists who want to help shape the future of trustworthy AI.
GB, London
We are looking for an Economist to work on exciting and challenging business problems related to Amazon Retail’s worldwide product assortment. You will build innovative solutions based on econometrics, machine learning, and experimentation. You will be part of a interdisciplinary team of economists, product managers, engineers, and scientists, and your work will influence finance and business decisions affecting Amazon’s vast product assortment globally. If you have an entrepreneurial spirit, you know how to deliver results fast, and you have a deeply quantitative, highly innovative approach to solving problems, and long for the opportunity to build pioneering solutions to challenging problems, we want to talk to you. Key job responsibilities * Work on a challenging problem that has the potential to significantly impact Amazon’s business position * Develop econometric models and experiments to measure the customer and financial impact of Amazon’s product assortment * Collaborate with other scientists at Amazon to deliver measurable progress and change * Influence business leaders based on empirical findings
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 Applied Scientist on our team, you will focus on building state-of-the-art ML models for biology. 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. Key job responsibilities - Build, adapt and evaluate ML models for life sciences applications - Collaborate with a cross-functional team of ML scientists, biologists, software engineers and product managers
US, WA, Seattle
Amazon Prime is looking for an ambitious Economist Intern to help create econometric insights for world-wide Prime. Prime is Amazon's premiere membership program, with over 200M members world-wide. This role is at the center of many major company decisions that impact Amazon's customers. These decisions span a variety of industries, each reflecting the diversity of Prime benefits. These range from fast-free e-commerce shipping, digital content (e.g., exclusive streaming video, music, gaming, photos), reading, healthcare, and grocery offerings. Prime Science creates insights that power these decisions. As an economist intern in this role, you will create statistical tools that embed causal interpretations. You will utilize massive data, state-of-the-art scientific computing, econometrics (causal, counterfactual/structural, experimentation), and machine-learning, to do so. Some of the science you create will be publishable in internal or external scientific journals and conferences. You will work closely with a team of economists, applied scientists, data professionals (business analysts, business intelligence engineers), product managers, and software/data engineers. You will create insights from descriptive statistics, as well as from novel statistical and econometric models. You will create internal-to-Amazon-facing automated scientific data products to power company decisions. You will write strategic documents explaining how senior company leaders should utilize these insights to create sustainable value for customers. These leaders will often include the senior-most leaders at Amazon. The team is unique in its exposure to company-wide strategies as well as senior leadership. It operates at the research frontier of utilizing data, econometrics, artificial intelligence, and machine-learning to form business strategies. A successful candidate will have demonstrated a capacity for building, estimating, and defending statistical models (e.g., causal, counterfactual, machine-learning) using software such as R, Python, or STATA. They will have a willingness to learn and apply a broad set of statistical and computational techniques to supplement deep training in one area of econometrics. For example, many applications on the team motivate the use of structural econometrics and machine-learning. They rely on building scalable production software, which involves a broad set of world-class software-building skills often learned on-the-job. As a consequence, already-obtained knowledge of SQL, machine learning, and large-scale scientific computing using distributed computing infrastructures such as Spark-Scala or PySpark would be a plus. Additionally, this candidate will show a track-record of delivering projects well and on-time, preferably in collaboration with other team members (e.g. co-authors). Candidates must have very strong writing and emotional intelligence skills (for collaborative teamwork, often with colleagues in different functional roles), a growth mindset, and a capacity for dealing with a high-level of ambiguity. Endowed with these traits and on-the-job-growth, the role will provide the opportunity to have a large strategic, world-wide impact on the customer experiences of Prime members.
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, well-being, and the value of work to Amazonians. The Benefits Science team is looking for a senior economist to transform complex business challenges into actionable scientific insights. In this role, you will partner directly with business leaders to design and evaluate pilots, build models using large-scale data, and scale successful prototypes into company-wide policies and programs. We're looking for someone who can combine rigorous scientific thinking with practical business acumen and is passionate about using economics to improve employee experiences at scale. The ideal candidate will thrive in interdisciplinary environments, working alongside engineers, data scientists, and business leaders from diverse backgrounds. Key job responsibilities * Design and evaluate innovative research pilots that address critical business challenges * Develop sophisticated economic models using large-scale organizational data * Collaborate with engineers, data scientists, and business leaders to transform research insights into actionable strategies * Write and present comprehensive research findings to senior leadership * Scale successful prototypes into company-wide policies and programs A day in the life 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 Our Benefits Science team is a dynamic group of economists, data scientists, and business strategists committed to understanding human capital at scale. We use interdisciplinary approaches to solve complex workforce challenges, combining economics, behavioral science, and advanced analytics to create meaningful workplace improvements.