Alexa Prize

The Alexa Prize is a series of competitions for university students dedicated to accelerating the field of artificial intelligence. Participating teams will advance several areas of AI through generalizable methodologies such as continuous learning, teachable AI, multimodal understanding, and reasoning.

Through the innovative work of students, Amazon Alexa customers will have novel, engaging interactions. And, the immediate feedback from these customers will help students improve their algorithms much faster than previously possible.
  • The grand challenge is focused on creating a SocialBot, an Alexa skill that converses coherently and engagingly with humans on popular topics and news.
  • The challenge is focused on helping advance development of next-gen virtual assistants that will assist humans in completing real-world tasks by continuously learning, and gaining the ability to perform commonsense reasoning.
  • The challenge is focused on developing agents that assist customers in completing complex tasks that require multiple steps and decisions. It's the first conversational AI challenge to incorporate multimodal (voice and vision) customer experiences.

Resources

  • View the competing Alexa Prize teams from universities around the world, and learn more about the students, team leaders, and faculty advisors.
  • Businessman hands searching data information in Stack of papers files on work desk in office, business report paper or piles of unfinished documents achives with clips on offices indoor, Business concept
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    See the research in conversational AI resulting from the pursuit of the Alexa Prize competition goals.
  • FAQ, ask quiestion online, what where when how and why, search information on internet
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    Before getting in touch, check and see if we've covered your query in our frequently asked questions.
  • Teams build their bots using the Alexa Skills Kit (ASK), which enables them to receive continuous feedback on their inventions in real-world settings.

Up next

Alexa Prize TaskBot Challenge Finals On now
Alexa Prize TaskBot Challenge Finals
Alexa Prize SocialBot Grand Challenge 4 On now
Alexa Prize SocialBot Grand Challenge 4
How to create a compelling Alexa Prize application On now
How to create a compelling Alexa Prize application
Panelists discuss the Alexa Prize during WSDM 2021 On now
Panelists discuss the Alexa Prize during WSDM 2021
Welcome to the Alexa Prize On now
Welcome to the Alexa Prize
Winners of the Alexa Prize SocialBot Grand Challenge 3 discuss their research On now
Winners of the Alexa Prize SocialBot Grand Challenge 3 discuss their research
Alexa Prize SocialBot Grand Challenge 3 On now
Alexa Prize SocialBot Grand Challenge 3
Understanding conversational AI with Professor Oliver Lemon On now
Understanding conversational AI with Professor Oliver Lemon
Team Gunrock, UC Davis, discuss the Alexa Prize SocialBot Grand Challenge 3 On now
Team Gunrock, UC Davis, discuss the Alexa Prize SocialBot Grand Challenge 3
Yoelle Maarek, Alexa Shopping vice president of research and science On now
Yoelle Maarek, Alexa Shopping vice president of research and science
Dilek Hakkani-Tür, Alexa AI senior principal scientist On now
Dilek Hakkani-Tür, Alexa AI senior principal scientist
Alexa Prize SocialBot Grand Challenge 2 On now
Alexa Prize SocialBot Grand Challenge 2
Alexa Prize SocialBot Grand Challenge 1 On now
Alexa Prize SocialBot Grand Challenge 1
Introducing the Alexa Prize On now
Introducing the Alexa Prize
Alexa Prize TaskBot Challenge Finals
Jeff Bezos Amazon Science Shareholder Letter.jpg
I believe the dreamers come first, and the builders come second. A lot of the dreamers are science fiction authors, they’re artists...They invent these ideas, and they get catalogued as impossible. And we find out later, well, maybe it’s not impossible. Things that seem impossible if we work them the right way for long enough, sometimes for multiple generations, they become possible.
Jeff Bezos, founder and executive chairman of Amazon

Latest news

The latest updates, stories, and more about Alexa Prize.
GB, London
"Are you a MS or PhD student interested in the fields of Computer Science or Operational Research? Do you enjoy diving deep into hard technical problems and coming up with solutions that enable successful products? If this describes you, come join our research teams at Amazon. " Key job responsibilities The candidate will be responsible for the design and implementation of optimization algorithms. The candidate will translate high-level business problems into mathematical ones. Then, they will design and implement optimization algorithms to solve them. The candidate will be responsible also for the analysis and design of KPIs and input data quality. About the team ATS stands for Amazon Transportation Service, we are the middle-mile planners: we carry the packages from the warehouses to the cities in a limited amount of time to enable the “Amazon experience”. As the core research team, we grow with ATS business to support decision making in an increasingly complex ecosystem of a data-driven supply chain and e-commerce giant. We take pride in our algorithmic solutions: We schedule more than 1 million trucks with Amazon shipments annually; our algorithms are key to reducing CO2 emissions, protecting sites from being overwhelmed during peak days, and ensuring a smile on Amazon’s customer lips. We do not shy away from responsibility. Our mathematical algorithms provide confidence in leadership to invest in programs of several hundreds millions euros every year. Above all, we are having fun solving real-world problems, in real-world speed, while failing & learning along the way. We employ the most sophisticated tools: We use modular algorithmic designs in the domain of combinatorial optimization, solving complicated generalizations of core OR problems with the right level of decomposition, employing parallelization and approximation algorithms. We use deep learning, bandits, and reinforcement learning to put data into the loop of decision making. We like to learn new techniques to surprise business stakeholders by making possible what they cannot anticipate. For this reason, we work closely with Amazon scholars and experts from Academic institutions. We are open to hiring candidates to work out of one of the following locations: London, GBR
US, MA, Boston
The Artificial General Intelligence (AGI) team is looking for a highly-skilled Senior Applied Scientist, to lead the development and implementation of cutting-edge algorithms and push the boundaries of efficient inference for Generative Artificial Intelligence (GenAI) models. As a Senior Applied Scientist, you will play a critical role in driving the development of GenAI technologies that can handle Amazon-scale use cases and have a significant impact on our customers' experiences. Key job responsibilities - Design and execute experiments to evaluate the performance of different decoding algorithms and models, and iterate quickly to improve results - Develop deep learning models for compression, system optimization, and inference - Collaborate with cross-functional teams of engineers and scientists to identify and solve complex problems in GenAI - Mentor and guide junior scientists and engineers, and contribute to the overall growth and development of the team We are open to hiring candidates to work out of one of the following locations: Bellevue, WA, USA | Boston, MA, USA | New York, NY, USA
US, WA, Bellevue
We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to work with large and complicated data sets. Knowledge of econometrics, and basic familiarity with Python or R, is necessary. Experience with SQL is a plus. These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis. You will learn how to build data sets and apply econometric methods to support business decisions, collaborating with economists, scientists, and product managers. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with placement. Roughly 85% of previous cohorts have converted to full time economics employment at Amazon. If you are interested, please send your CV to our mailing list at econ-internship@amazon.com. Key job responsibilities Collaborate with business and science colleagues to understand the business problem and collect relevant data. Provide statistically rigorous analysis of data that contributes to business decision-making. Effectively communicate your results to colleagues and business leaders. A day in the life Meet with colleagues to discuss how the business currently works. Discuss ways in which the customer experience could be improved, and what data you'd need to test your hypotheses. Meet with data and business intelligence engineers to build an efficient data pipeline using SQL, spark and other big data tools. Propose and execute a plan to analyze your data, working closely with your econ colleagues. Use Amazon's development tools, coding your estimators in Python or R. Draft your findings for an internal knowledge sharing session. Iterate to improve your work and communicate your final results in a business document. About the team We are a team of four economists that works within the delivery experience org. Our goal is to improve the delivery experience for our customers while reducing costs. This mission puts us in a unique position to influence both the front end customer experience and the supply chain that ultimately places constraints on that experience. This means we often work with and influence teams outside of our own organization. As a result, we have the privilege of working with a diverse group of experts, including those in supply chain, operations, capacity management, and user experience. We are open to hiring candidates to work out of one of the following locations: Bellevue, WA, USA
ES, B, Barcelona
"Are you a MS or PhD student interested in the fields of Computer Science or Operational Research? Do you enjoy diving deep into hard technical problems and coming up with solutions that enable successful products? If this describes you, come join our research teams at Amazon. " Key job responsibilities The candidate will be responsible for the design and implementation of optimization algorithms. The candidate will translate high-level business problems into mathematical ones. Then, they will design and implement optimization algorithms to solve them. The candidate will be responsible also for the analysis and design of KPIs and input data quality. About the team ATS stands for Amazon Transportation Service, we are the middle-mile planners: we carry the packages from the warehouses to the cities in a limited amount of time to enable the “Amazon experience”. As the core research team, we grow with ATS business to support decision making in an increasingly complex ecosystem of a data-driven supply chain and e-commerce giant. We take pride in our algorithmic solutions: We schedule more than 1 million trucks with Amazon shipments annually; our algorithms are key to reducing CO2 emissions, protecting sites from being overwhelmed during peak days, and ensuring a smile on Amazon’s customer lips. We do not shy away from responsibility. Our mathematical algorithms provide confidence in leadership to invest in programs of several hundreds millions euros every year. Above all, we are having fun solving real-world problems, in real-world speed, while failing & learning along the way. We employ the most sophisticated tools: We use modular algorithmic designs in the domain of combinatorial optimization, solving complicated generalizations of core OR problems with the right level of decomposition, employing parallelization and approximation algorithms. We use deep learning, bandits, and reinforcement learning to put data into the loop of decision making. We like to learn new techniques to surprise business stakeholders by making possible what they cannot anticipate. For this reason, we work closely with Amazon scholars and experts from Academic institutions. We are open to hiring candidates to work out of one of the following locations: Barcelona, B, ESP
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 - 3+ 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 We are open to hiring candidates to work out of one of the following locations: Chennai, TN, IND
US, VA, Arlington
Machine learning (ML) has been strategic to Amazon from the early years. We are pioneers in areas such as recommendation engines, product search, eCommerce fraud detection, and large-scale optimization of fulfillment center operations. The Generative AI team helps AWS customers accelerate the use of Generative AI to solve business and operational challenges and promote innovation in their organization. As an applied scientist, you are proficient in designing and developing advanced ML models to solve diverse challenges and opportunities. You will be working with terabytes of text, images, and other types of data to solve real-world problems. You'll design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. We’re looking for talented scientists capable of applying ML algorithms and cutting-edge deep learning (DL) and reinforcement learning approaches to areas such as drug discovery, customer segmentation, fraud prevention, capacity planning, predictive maintenance, pricing optimization, call center analytics, player pose estimation, event detection, and virtual assistant among others. AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector. The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success. AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services. Key job responsibilities The primary responsibilities of this role are to: - Design, develop, and evaluate innovative ML models to solve diverse challenges and opportunities across industries - Interact with customer directly to understand their business problems, and help them with defining and implementing scalable Generative AI solutions to solve them - Work closely with account teams, research scientist teams, and product engineering teams to drive model implementations and new solution About the team About AWS Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the preferred 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. We are open to hiring candidates to work out of one of the following locations: Arlington, VA, USA | Atlanta, GA, USA | Austin, TX, USA | Houston, TX, USA | New York, NJ, USA | New York, NY, USA | San Francisco, CA, USA | Santa Clara, CA, USA | Seattle, WA, USA
US, WA, Seattle
Prime Video offers customers a vast collection of movies, series, and sports—all available to watch on hundreds of compatible devices. U.S. Prime members can also subscribe to 100+ channels including Max, discovery+, Paramount+ with SHOWTIME, BET+, MGM+, ViX+, PBS KIDS, NBA League Pass, MLB.TV, and STARZ with no extra apps to download, and no cable required. Prime Video is just one of the savings, convenience, and entertainment benefits included in a Prime membership. More than 200 million Prime members in 25 countries around the world enjoy access to Amazon’s enormous selection, exceptional value, and fast delivery. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video technologist, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! Key job responsibilities As a Data Scientist at Amazon Prime Video, you will work with massive customer datasets, provide guidance to product teams on metrics of success, and influence feature launch decisions through statistical analysis of the outcomes of A/B experiments. You will develop machine learning models to facilitate understanding of customer's streaming behavior and build predictive models to inform personalization and ranking systems. You will work closely other scientists, economists and engineers to research new ways to improve operational efficiency of deployed models and metrics. A successful candidate will have a strong proven expertise in statistical modeling, machine learning, and experiment design, along with a solid practical understanding of strength and weakness of various scientific approaches. They have excellent communication skills, and can effectively communicate complex technical concepts with a range of technical and non-technical audience. They will be agile and capable of adapting to a fast-paced environment. They have an excellent track-record on delivering impactful projects, simplifying their approaches where necessary. A successful data scientist will own end-to-end team goals, operates with autonomy and strive to meet key deliverables in a timely manner, and with high quality. About the team Prime Video discovery science is a central team which defines customer and business success metrics, models, heuristics and econometric frameworks. The team develops, owns and operates a suite of data science and machine learning models that feed into online systems that are responsible for personalization and search relevance. The team is responsible for Prime Video’s experimentation practice and continuously innovates and upskills teams across the organization on science best practices. The team values diversity, collaboration and learning, and is excited to welcome a new member whose passion and creativity will help the team continue innovating and enhancing customer experience. We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA
US, NJ, Newark
Employer: Audible, Inc. Title: Data Scientist II Location: 1 Washington Street, Newark, NJ, 07102 Duties: Design and implement scalable and reliable approaches to support or automate decision making throughout the business. Apply a range of data science techniques and tools combined with subject matter expertise to solve difficult business problems and cases in which the solution approach is unclear. Acquire data by building the necessary SQL/ETL queries. Import processes through various company specific interfaces for accessing RedShift, and S3/edX storage systems. Build relationships with stakeholders and counterparts, and communicate model outputs, observations, and key performance indicators (KPIs) to the management to develop sustainable and consumable products. Explore and analyze data by inspecting univariate distributions and multivariate interactions, constructing appropriate transformations, and tracking down the source and meaning of anomalies. Build production-ready models using statistical modeling, mathematical modeling, econometric modeling, machine learning algorithms, network modeling, social network modeling, natural language processing, or genetic algorithms. Validate models against alternative approaches, expected and observed outcome, and other business defined key performance indicators. Implement models that comply with evaluations of the computational demands, accuracy, and reliability of the relevant ETL processes at various stages of production. Position reports into Newark, NJ office; however, telecommuting from a home office may be allowed. Requirements: Requires a Master’s in Statistics, Computer Science, Data Science, Machine Learning, Applied Math, Operations Research, Economics, or a related field plus two (2) years of Data Scientist or other occupation/position/job title with research or work experience related to data processing and predictive Machine Learning modeling at scale. Experience may be gained concurrently and must include: Two (2) years in each of the following: - Building statistical models and machine learning models using large datasets from multiple resources - Non-linear models including Neural Nets or Deep Learning, and Gradient Boosting - Applying specialized modelling software including Python, R, SAS, MATLAB, or Stata. One (1) year in the following: - Using database technologies including SQL or ETL. Alternatively, will accept a Bachelor's and five (5) years of experience. Multiple positions. Apply online: www.amazon.jobs Job Code: ADBL135. We are open to hiring candidates to work out of one of the following locations: Newark, NJ, USA
US, WA, Bellevue
The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Applied Scientist with a strong deep learning background, to help build industry-leading technology with Large Language Models (LLMs) and multimodal systems. Key job responsibilities As an Applied Scientist with the AGI team, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art with LLMs. Your work will directly impact our customers in the form of products and services that make use of audio technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in AGI in audio domain. About the team Our team has a mission to push the envelope of AGI in audio domain, in order to provide the best-possible experience for our customers. We are open to hiring candidates to work out of one of the following locations: Bellevue, WA, USA | Boston, MA, USA
DE, BE, Berlin
Are you fascinated by revolutionizing Alexa user experience with LLM? The Artificial General Intelligence (AGI) team is looking for an Applied Scientist with background in Large Language Model, Natural Language Process, Machine/Deep learning. You will be at the heart of the Alexa LLM transition working with a team of applied and research scientists to bring classic Alexa features and beyond into LLM empowered Alexa. You will interact in a cross-functional capacity with science, product and engineering leaders. Key job responsibilities * Work on core LLM technologies (supervised fine tuning, prompt optimization, etc.) to enable Alexa use cases * Research and develop novel metrics and algorithms for LLM evaluation * Communicating effectively with leadership team as well as with colleagues from science, engineering and business backgrounds. We are open to hiring candidates to work out of one of the following locations: Berlin, BE, DEU