On the left is the logo for the Alexa Prize Socialbot Grand Challenge 4. On the right is a group photo of Team Alquist from Czech Technical University which won the Alexa Prize SocialBot Grand Challenge 4 competition.
Team Alquist from Czech Technical University has won the Alexa Prize SocialBot Grand Challenge 4 competition. The team, which was awarded the $500,000 first prize for earning the top score in the finals competition, already is looking forward to the next challenge says its faculty advisor, Jan Sedivy (far right).
Credit: Glynis Condon

Czech Technical University team wins Alexa Prize SocialBot Grand Challenge 4

Team Alquist awarded $500,000 prize for top score in finals competition; teams from Stanford University and the University of Buffalo place second and third.

The Czech Republic captured four gold medals at the 2021 summer Olympics in Japan, quite a feat for the Central European country with a population of just over 10 million people.

The country now has another gold-medal-winning team — Alquist from Czech Technical University (CTU) in Prague, which today learned it is the winner of the 2021 Alexa Prize SocialBot Grand Challenge.

“We are incredibly excited to learn that we have won this year’s competition,”said Jakub Konrád, a CTU PhD student and Alquist’s team leader. “I am delighted and proud of our entire team for building a bot that managed to reach the finals for the fourth consecutive year. This year we strove to create a system capable of flexible conversation by synthesizing generative approaches with prepared scenarios that could adjust to users’ needs.”

Faculty advisors provide their perspectives

Faculty advisors to each of the finalists provided their perspectives on the Alexa Prize Socialbot Grand Challenge 4 competition. Learn more about their insights, and read the teams' research papers.

The team’s faculty advisor, Jan Sedivy, added that this year’s team had great fun designing “catchy and attractive dialogues”, and that the team already is looking forward to joining the next challenge.

The Alexa Prize SocialBot Grand Challenge, launched in 2016, is a competition for university students dedicated to advancing the field of conversational AI. Teams are challenged to design socialbots that Alexa customers can interact with via Alexa-enabled devices. The ultimate goal: meet the Grand Challenge by earning a composite score of 4.0 or higher (out of 5) from competition judges. Additionally, the finals’ judges must determine that at least two-thirds of their interactions with the socialbot were coherent and engaging for a minimum of 20 minutes. The first team to meet the Grand Challenge will win a $1 million research grant for its university.

Although none of this year’s teams met the Grand Challenge, each finalist demonstrated impressive progress toward the goal. Alquist, the socialbot from CTU, earned first place with a 3.28 average rating, and an average finals’ competition interaction duration of 14 minutes and 14 seconds. For the second consecutive year, Stanford University’s Chirpy Cardinal socialbot earned second-place honors and a $100,000 prize by achieving a 3.25 average rating, and an average of 13 minutes and 25 seconds of interaction duration. PROTO, the socialbot from the University of Buffalo team, earned third-place honors with an average rating of 3.16, and an average of 14 minutes and 45 seconds of interaction duration.

Stanford University Alexa Prize team
Stanford University's Chirpy Cardinal team earned second place and a $100,000 prize.
Credit: Stanford

“Team Chirpy Cardinal really enjoyed participating in the Alexa Prize for the second time,” said Ethan Chi, a research assistant within Stanford’s NLP Group, and team leader. “Throughout this experience, we've learned so much about real-world dialogue. We almost completely rebuilt our system from the ground up, allowing us to handle a greatly expanded variety of user comments and interjections, and we developed new neural techniques to blend factual knowledge fluidly into our conversations. We even integrated news from The Guardian into our system, allowing us to build common ground with our users over recent events. Compared to our socialbot's previous incarnation, we more than doubled our average finals conversation length, bringing us closer to our shared goal of fluent conversational AI.”

“From an innovation perspective, our aim was to create an agent that wouldn’t restrict interaction to a defined set of topics,” said Sougata Saha, a PhD student at the University of Buffalo, and PROTO’s team lead. “Our use of an ensemble of factual and chit-chat neural generators, coupled with a robust dialogue manager, helped us achieve our third-place finish.”

University of Buffalo Alexa Prize team
The PROTO team from the University of Buffalo earned third place in the competition, and a $50,000 prize.
Credit: University of Buffalo

Last November, nine teams were selected to participate in the competition, and in July five finalists were selected to compete in the finals competition, which took place July 27-29. The finals competition also included teams from Emory University, and The University of California, Santa Cruz.

“Building open-domain conversational systems that allow customers to engage on topics ranging from sports and entertainment, to politics and technology is an incredibly challenging task,” said Prem Natarajan, Alexa AI vice president of Natural Understanding. “Creating socialbots that can conduct these kinds of multi-turn, open-domain interactions is still far from a solved problem. The fact that the top teams participating in this year’s finals competition more than doubled the average duration of interactions over the previous challenge demonstrates that we continue to make impressive progress toward that goal.”

Each of the nine teams participating in Alexa Prize Grand Challenge 4 has published a research paper outlining their approaches to this year’s competition. The papers are now available on the Alexa Prize website.

Since 2017, Alexa customers have engaged with Alexa Prize socialbots for more than 900,000 hours. Alexa customers can continue to engage with the winning teams’ socialbots simply by saying, “Alexa, let’s chat.” 

Previous challenge winners include teams from the University of Washington, the University of California, Davis, and Emory University.  

Alexa Prize SocialBot Grand Challenge 4

Alexa Prize program expands

The Alexa Prize program has expanded to include another competition, as well. Earlier this year, Amazon launched the Alexa Prize TaskBot Challenge, in which 10 participating teams are competing to develop agents that assist customers in completing tasks that require multiple steps and decisions. It is the first conversational AI challenge to incorporate multimodal (voice and vision) and interactive customer experiences. The year-long competition concludes in May 2022, with winners announced the following month.

More information about the challenge is available on the competition’s frequently asked questions page. Alexa customers will have the opportunity to interact with the taskbots beginning in October 2021.

In the coming months, Amazon Science will have details on the forthcoming Alexa Prize Socialbot Grand Challenge 5.

Research areas

Latest news

The latest updates, stories, and more about Alexa Prize.
US, WA, Seattle
The Automated Reasoning Group in AWS Platform is looking for an Applied Scientist with experience in building scalable solver solutions that delight customers. You will be part of a world-class team building the next generation of automated reasoning tools and services. AWS has the most services and more features within those services, than any other cloud provider–from infrastructure technologies like compute, storage, and databases–to emerging technologies, such as machine learning and artificial intelligence, data lakes and analytics, and Internet of Things. You will apply your knowledge to propose solutions, create software prototypes, and move prototypes into production systems using modern software development tools and methodologies. In addition, you will support and scale your solutions to meet the ever-growing demand of customer use. You will use your strong verbal and written communication skills, are self-driven and own the delivery of high quality results in a fast-paced environment. Each day, hundreds of thousands of developers make billions of transactions worldwide on AWS. They harness the power of the cloud to enable innovative applications, websites, and businesses. Using automated reasoning technology and mathematical proofs, AWS allows customers to answer questions about security, availability, durability, and functional correctness. We call this provable security, absolute assurance in security of the cloud and in the cloud. See https://aws.amazon.com/security/provable-security/ As an Applied Scientist in AWS Platform, you will play a pivotal role in shaping the definition, vision, design, roadmap and development of product features from beginning to end. You will: - Define and implement new solver applications that are scalable and efficient approaches to difficult problems - Apply software engineering best practices to ensure a high standard of quality for all team deliverables - Work in an agile, startup-like development environment, where you are always working on the most important stuff - Deliver high-quality scientific artifacts - Work with the team to define new interfaces that lower the barrier of adoption for automated reasoning solvers - Work with the team to help drive business decisions The AWS Platform is the glue that holds the AWS ecosystem together. From identity features such as access management and sign on, cryptography, console, builder & developer tools, to projects like automating all of our contractual billing systems, AWS Platform is always innovating with the customer in mind. The AWS Platform team sustains over 750 million transactions per second. Learn and Be Curious. We have a formal mentor search application that lets you find a mentor that works best for you based on location, job family, job level etc. Your manager can also help you find a mentor or two, because two is better than one. In addition to formal mentors, we work and train together so that we are always learning from one another, and we celebrate and support the career progression of our team members. Inclusion and Diversity. Our team is diverse! We drive towards an inclusive culture and work environment. We are intentional about attracting, developing, and retaining amazing talent from diverse backgrounds. Team members are active in Amazon’s 10+ affinity groups, sometimes known as employee resource groups, which bring employees together across businesses and locations around the world. These range from groups such as the Black Employee Network, Latinos at Amazon, Indigenous at Amazon, Families at Amazon, Amazon Women and Engineering, LGBTQ+, Warriors at Amazon (Military), Amazon People With Disabilities, and more. Key job responsibilities Work closely with internal and external users on defining and extending application domains. Tune solver performance for application-specific demands. Identify new opportunities for solver deployment. About the team Solver science is a talented team of scientists from around the world. Expertise areas include solver theory, performance, implementation, and applications. Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Hybrid Work We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices. We are open to hiring candidates to work out of one of the following locations: Portland, OR, USA | Seattle, WA, USA
CN, 11, Beijing
Amazon Search JP builds features powering product search on the Amazon JP shopping site and expands the innovations to world wide. As an Applied Scientist on this growing team, you will take on a key role in improving the NLP and ranking capabilities of the Amazon product search service. Our ultimate goal is to help customers find the products they are searching for, and discover new products they would be interested in. We do so by developing NLP components that cover a wide range of languages and systems. As an Applied Scientist for Search JP, you will design, implement and deliver search features on Amazon site, helping millions of customers every day to find quickly what they are looking for. You will propose innovation in NLP and IR to build ML models trained on terabytes of product and traffic data, which are evaluated using both offline metrics as well as online metrics from A/B testing. You will then integrate these models into the production search engine that serves customers, closing the loop through data, modeling, application, and customer feedback. The chosen approaches for model architecture will balance business-defined performance metrics with the needs of millisecond response times. Key job responsibilities - Designing and implementing new features and machine learned models, including the application of state-of-art deep learning to solve search matching, ranking and Search suggestion problems. - Analyzing data and metrics relevant to the search experiences. - Working with teams worldwide on global projects. Your benefits include: - Working on a high-impact, high-visibility product, with your work improving the experience of millions of customers - The opportunity to use (and innovate) state-of-the-art ML methods to solve real-world problems with tangible customer impact - Being part of a growing team where you can influence the team's mission, direction, and how we achieve our goals We are open to hiring candidates to work out of one of the following locations: Beijing, 11, CHN | Shanghai, 31, CHN
US, WA, Seattle
Are you interested in building, developing, and driving the machine learning technical vision, strategy, and implementation for AWS Hardware? AWS Hardware is hiring a Senior Applied Scientist (AS) to lead the definition and prioritization of our customer focused technologies and services. AWS Hardware is responsible for designing, qualifying, and maintaining server solutions for AWS and its customers as well as developing new cloud focused hardware solutions. You will be a senior technical leader in the existing Data Sciences and Analytics Team, build, and drive the data science and machine learning needed for our product development and operations. As a Senior AS at Amazon, you will provide technical leadership to the teams, organization and products for machine learning. Senior AS’s are specialists with deep expertise in areas such as machine learning, speech recognition, large language models (LLMs), natural language processing, computer vision, and knowledge acquisition, and help drive the ML vision for our products. They are externally aware of the state-of-the-art in their respective field of expertise and are constantly focused on advancing the state-of-the-art for improving Amazon’s products and services. The ideal candidate will be an expert in the areas of data science, machine learning, and statistics; specifically in recommendation systems development, classification, and LLMs. You will have hands-on experience leading multiple simultaneous product development and operations initiatives as well as be able to balance technical leadership with strong business judgment to make the right decisions about technology, infrastructure, methodologies, and productionizing models and code. You will strive for simplicity, and demonstrate significant creativity and high judgment backed by statistical proof. Key job responsibilities MS in Data Science, Machine Learning, Statistics, Computer Science, Applied Math or equivalent highly technical field. 10+ years of hands-on experience working in data science and/or machine learning using models and methods such as neural networks, random forests, SVMs or Bayesian classification. 3+ years developing recommendation systems and/or LLMs. 3+ years of experience working in software development, machine learning engineering or ops. Have a history of building highly scalable systems that capture and utilize large data sets in order to quantify your products performance via metrics, monitoring, and alarming. Experience using R, Python, Java, or other equivalent statistics and machine learning tools. Experienced in computer science fundamentals such as object-oriented design, data structures and algorithm design. 3+ years of experience developing in a cloud environment. We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA
US, CA, San Diego
Do you want to join an innovative team of scientists who use deep learning, natural language processing, large language models to help Amazon provide the best seller experience across the entire Seller life cycle, including recruitment, growth, support and provide the best customer and seller experience by automatically mitigating risk? Do you want to build advanced algorithmic systems that help manage the trust and safety of millions of customer interactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data and creating state-of-the-art algorithms to solve real world problems? Are you excited by the opportunity to leverage GenAI and innovate on top of the state-of-the-art large language models to improve customer and seller experience? Do you like to build end-to-end business solutions and directly impact the profitability of the company? Do you like to innovate and simplify processes? If yes, then you may be a great fit to join the Machine Learning Accelerator team in the Amazon Selling Partner Services (SPS) group. Key job responsibilities The scope of an Applied Scientist III in the Selling Partner Services (SPS) Machine Learning Accelerator (MLA) team is to research and prototype Machine Learning applications that solve strategic business problems across SPS domains. Additionally, the scientist collaborates with engineers and business partners to design and implement solutions at scale when they are determined to be of broad benefit to SPS organizations. They develop large-scale solutions for high impact projects, introduce tools and other techniques that can be used to solve problems from various perspectives, and show depth and competence in more than one area. They influence the team’s technical strategy by making insightful contributions to the team’s priorities, approach and planning. They develop and introduce tools and practices that streamline the work of the team, and they mentor junior team members and participate in hiring. We are open to hiring candidates to work out of one of the following locations: San Diego, CA, USA
IN, KA, Bengaluru
How to use the world’s richest collection of e-commerce data to improve payments experience for our customers? Amazon Payments Global Data Science team seeks a Senior Data Scientist for building analytical and scientific solutions that will address increasingly complex business questions in the Gift-Cards space. Amazon.com has a culture of data-driven decision-making and demands intelligence that is timely, accurate, and actionable. This team operates at WW level and provides a fast-paced environment where every day brings new challenges and opportunities. As a Senior Data Scientist in this team, you will be driving the Data Science/ML roadmap for business continuity & growth. You will develop statistical and machine learning models to solve for complex business problems in Gift-Cards space, design and run global experiments, and find new ways to optimize the customer experience. You will need to collaborate effectively with internal stakeholders, cross-functional teams to solve problems, create operational efficiencies, and deliver successfully against high organizational standards. You will explore GenAI use-cases within Gift-Cards space and also work on cross-disciplinary efforts with other scientists within Amazon. Key job responsibilities - You should be detail-oriented and must have an aptitude for solving unstructured and ambiguous problems. You should work in a self-directed environment, own tasks and drive them to completion - You should be passionate about working with huge data sets and be someone who loves to bring datasets together to answer business questions - You should demonstrate thorough technical expertise on feature engineering of massive datasets, exploratory data analysis, and model building using state-of-art ML algorithms - Random Forest, Gradient Boosting, SVM, Neural Nets, DL, Reinforcement Learning etc. You should be aware of automating feedback loops for algorithms in production - You should work closely with internal stakeholders like the business teams, engineering teams and partner teams and align them with respect to your focus areas - You should have excellent business and communication skills to be able to work with business owners to develop and define key business questions and build mechanisms that answer those questions We are open to hiring candidates to work out of one of the following locations: Bengaluru, KA, IND
IN, KA, Bangalore
Are you interested in changing the Digital Reading Experience? We are from Kindle Books Team looking for a set of Scientists to take the reading experience in Kindle to next level with a set of innovations! We envision Kindle as the place where readers find the best manifestation of all written content optimized with features that enable them to get the most out of reading, and creators are able to realize their vision to customers quickly and at scale. Every time customers open their content, regardless of surface, they start or restart their reading in a familiar, useful and engaging place. We achieve this by building a strong foundation of core experiences and act as a force multiplier and partner for content creators (directly or indirectly) to easily innovate on top of Kindle's purpose built content experience stack in a simple and extensible way. We will achieve this by providing a best-in-class reading experience, unique content experiences, and remaining agile in meeting the evolving needs and preferences of our users. Our goal is to foster long-lasting reading habits and make us the preferred destination for enriching literary experiences. We are building a In The Book Science team and looking for Scientists, who are passionate about Reading and are willing to take Reading to the next level. Every Book is a complex structure with different entities, layout, format and semantics, with more than 17MM eBooks in our catalog. We are looking for experts in all domains like core NLP, Generative AI, CV and Deep Learning Techniques for unlocking capabilities like analysis, enhancement, curation, moderation, translation, transformation and generation in Books based on Content structure, features, Intent & Synthesis. Scientists will focus on Inside the book content and semantically learn the different entities to enhance the Reading experience overall (Kindle & beyond). They have an opportunity to influence in 2 major phases of life-cycle - Publishing (Creation of Books process) and Reading experience (building engaging features & representation in the book thereby driving reading engagement). Key job responsibilities - 5+ years of building machine learning models for business application experience - PhD, or Master's degree and 6+ years of applied research experience - Knowledge of programming languages such as C/C++, Python, Java or Perl - Experience programming in Java, C++, Python or related language - You have expertise in one of the applied science disciplines, such as machine learning, natural language processing, computer vision, Deep learning - You are able to use reasonable assumptions, data, and customer requirements to solve problems. - You initiate the design, development, execution, and implementation of smaller components with input and guidance from team members. - You work with SDEs to deliver solutions into production to benefit customers or an area of the business. - You assume responsibility for the code in your components. You write secure, stable, testable, maintainable code with minimal defects. - You understand basic data structures, algorithms, model evaluation techniques, performance, and optimality tradeoffs. - You follow engineering and scientific method best practices. You get your designs, models, and code reviewed. You test your code and models thoroughly - You participate in team design, scoping and prioritization discussions. You are able to map a business goal to a scientific problem and map business metrics to technical metrics. - You invent, refine and develop your solutions to ensure they are meeting customer needs and team goals. You keep current with research trends in your area of expertise and scrutinize your results. - Experience in mentoring junior scientists A day in the life You will be working with a group of talented scientists on researching algorithm and running experiments to test solutions to improve our experience. This will involve collaboration with partner teams including engineering, PMs, data annotators, and other scientists to discuss data quality, model development and productionizing the same. You will mentor other scientists, review and guide their work, help develop roadmaps for the team. We are open to hiring candidates to work out of one of the following locations: Banagalore, KA, IND | Bangalore, IND | Bangalore, KA, IND
IN, KA, Bangalore
Are you interested in changing the Digital Reading Experience? We are from Kindle Books Team looking for a set of Scientists to take the reading experience in Kindle to next level with a set of innovations! We envision Kindle as the place where readers find the best manifestation of all written content optimized with features that enable them to get the most out of reading, and creators are able to realize their vision to customers quickly and at scale. Every time customers open their content, regardless of surface, they start or restart their reading in a familiar, useful and engaging place. We achieve this by building a strong foundation of core experiences and act as a force multiplier and partner for content creators (directly or indirectly) to easily innovate on top of Kindle's purpose built content experience stack in a simple and extensible way. We will achieve this by providing a best-in-class reading experience, unique content experiences, and remaining agile in meeting the evolving needs and preferences of our users. Our goal is to foster long-lasting reading habits and make us the preferred destination for enriching literary experiences. We are building a In The Book Science team and looking for Scientists, who are passionate about Reading and are willing to take Reading to the next level. Every Book is a complex structure with different entities, layout, format and semantics, with more than 17MM eBooks in our catalog. We are looking for experts in all domains like core NLP, Generative AI, CV and Deep Learning Techniques for unlocking capabilities like analysis, enhancement, curation, moderation, translation, transformation and generation in Books based on Content structure, features, Intent & Synthesis. Scientists will focus on Inside the book content and semantically learn the different entities to enhance the Reading experience overall (Kindle & beyond). They have an opportunity to influence in 2 major phases of life-cycle - Publishing (Creation of Books process) and Reading experience (building engaging features & representation in the book thereby driving reading engagement). Key job responsibilities - 3+ years of building machine learning models for business application experience - PhD, or Master's degree and 2+ years of applied research experience - Knowledge of programming languages such as C/C++, Python, Java or Perl - Experience programming in Java, C++, Python or related language - You have expertise in one of the applied science disciplines, such as machine learning, natural language processing, computer vision, Deep learning - You are able to use reasonable assumptions, data, and customer requirements to solve problems. - You initiate the design, development, execution, and implementation of smaller components with input and guidance from team members. - You work with SDEs to deliver solutions into production to benefit customers or an area of the business. - You assume responsibility for the code in your components. You write secure, stable, testable, maintainable code with minimal defects. - You understand basic data structures, algorithms, model evaluation techniques, performance, and optimality tradeoffs. - You follow engineering and scientific method best practices. You get your designs, models, and code reviewed. You test your code and models thoroughly - You participate in team design, scoping and prioritization discussions. You are able to map a business goal to a scientific problem and map business metrics to technical metrics. - You invent, refine and develop your solutions to ensure they are meeting customer needs and team goals. You keep current with research trends in your area of expertise and scrutinize your results. A day in the life You will be working with a group of talented scientists on researching algorithm and running experiments to test solutions to improve our experience. This will involve collaboration with partner teams including engineering, PMs, data annotators, and other scientists to discuss data quality, model development and productionizing the same. You will mentor other scientists, review and guide their work, help develop roadmaps for the team. We are open to hiring candidates to work out of one of the following locations: Bangalore, IND | Bangalore, KA, IND
US, WA, Seattle
Amazon is looking for a strategic, innovative science leader within the Global Talent and Compensation (GTMC) organization to lead an interdisciplinary team charged with developing data-driven solutions to model, automate, and inform high judgement decision making by bringing together science and technology in consumer grade internal talent products. GTMC delivers employee-focused experiences by providing scalable and responsive mechanisms for employees, as well as listening and signaling mechanisms for managers and leaders. They do this through intelligent, flexible, and extensible products and scalable data and science services. They set out to deliver a singular experience supporting multiple employee talent journeys (e.g., onboarding, evaluation, compensation, movement, promotion, exit), to generate and capture signals from product data, surface outliers, increase personalization, and improve the efficacy of “next best action” recommendations, for 1.6 million Amazonians around the world. In this role you will lead multiple research teams across the disciplines of Talent Management, Diversity Equity and Inclusion, and Compensation. You will interface with the most senior leaders at Amazon to develop and deliver on a strategic research roadmap that crosses all lines of Amazon businesses (e.g., Consumer, AWS, Devices, Advertising). This role will then partner with engineering and product management leader to deliver the outcomes of this research in production environments. Successful candidates will have an established background expertise in machine learning with some experience in applying this expertise to the fields of talent management, product management and/or software development. We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA
US, WA, Bellevue
Where will Amazon's growth come from in the next year? What about over the next five? Which product lines are poised to quintuple in size? Are we investing enough in our infrastructure, or too much? How do our customers react to changes in prices, product selection, or delivery times? These are among the most important questions at Amazon today. The Topline Forecasting team in the Supply Chain Optimization Technologies (SCOT) group is looking for innovative, passionate and results-oriented Principal Economist to provide thought-leadership to help answer these questions. You will have an opportunity to own the long-run outlook for Amazon’s global consumer business and shape strategic decisions at the highest level. The successful candidate will be able to formalize problem definitions from ambiguous requirements, build econometric models using Amazon’s world-class data systems, and develop cutting-edge solutions for non-standard problems. Key job responsibilities - You understand the state-of-the-art in time series and econometric modeling. - You apply econometric tools and theory to solve business problems in a fast moving environment. - You excel at extracting insights and correct interpretations from data using advanced modeling techniques. - You communicate insights in a digestible manner to senior leaders in Finance and Operations within the company. - You are able to anticipate future business challenges and key questions, and have the ability to design modeling solutions to tackle them. - You have broad influence over the Topline team’s scientific research agenda and deliverables. - You contribute to the broader Econ research community in Amazon. - You advise other economists on scientific best-practices and raise the bar of research. - You will actively mentor other scientists and contribute to their career development. We are open to hiring candidates to work out of one of the following locations: Bellevue, WA, USA | New York, NY, USA
US, WA, Seattle
Are you a scientist interested in pushing the state of the art in LLMs, ML or Computer Vision forward? Are you interested in working on ground-breaking research projects that will lead to great products and scientific publications? Do you wish you had access to large datasets? Answer yes to any of these questions and you’ll fit right in here at Amazon. We are looking for a hands-on researcher, who wants to derive, implement, and test the next generation of Generative AI algorithms (either LLMs, Diffusion Models, auto-regressors, VAEs, or other generative models). The research we do is innovative, multidisciplinary, and far-reaching. We aim to define, deploy, and publish cutting edge research. In order to achieve our vision, we think big and tackle technology problems that are cutting edge. Where technology does not exist, we will build it. Where it exists we will need to modify it to make it work at Amazon scale. We need members who are passionate and willing to learn. “Amazon Science gives you insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work.” Please visit https://www.amazon.science for more information #hltech #hitech Key job responsibilities - Derive novel ML or Computer Vision or LLMs and NLP algorithms - Design and develop scalable ML solutions - Work with very large datasets - Work closely with software engineering teams and Product Managers to deploy your innovations - Publish your work at major conferences/journals. - Mentor team members in the use of your Generative AI and LLMs. About the team We are a tight-knit group that shares our experiences and help each other succeed. We believe in team work. We love hard problems and like to move fast in a growing and changing environment. We use data to guide our decisions and we always push the technology and process boundaries of what is feasible on behalf of our customers. If that sounds like an environment you like, join us. We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA