TWIZ

This taskbot's vision is to move multimodal conversational AI closer to the way humans communicate and solve tasks.

Conversational assistants are constantly pushed to their limits supporting human daily routines. The constant demand to extend the reach of conversational assistants to many activities and tasks exposes the lack of General AI algorithms. Hence, our long-term vision is to move multimodal conversational AI closer to the way humans communicate and solve tasks. To achieve our long-term vision, we aim to make multimodal conversations human-like, stimulating, and resilient to user ramblings.

Team TWIZ (2022)

Rafael Ferreira - Team leader

Ferreira is a 2nd Year Computer Science PhD student at NOVA School of Science and Technology in Portugal. He concluded his master's thesis in 2021 in conversational search, and is currently working on the subject of dialogue policy for conversational task-oriented agents. With his research, he aims to improve the flow and naturalness of conversational agents with the aim of developing systems that exhibit a more human-like understanding. His interests include Conversational Agents, NLP, ML, and Multimodal-AI, with experience in working with Alexa and AWS from the previous TaskBot Edition.

Diogo Silva

Silva is a Ph.D. student on language generation for recommendation systems with a focus on politeness and empathy generation. Throughout his MSc and early stages of my Ph.D., he has acquired an extensive knowledge of state-of-the-art text generation and realization approaches. In 2019, he completed an internship where he integrated a team management platform with Alexa allowing team members to use their Echo devices to interact with the platform. In 2022 he was part of team TWIZ which won 2nd place in the Taskbot Challenge. His main interest remains in bridging the gap between human-machine communication towards creating natural conversational agents.

Diogo Tavares

Tavares is currently beginning the second year of his PhD, focusing on Natural Language Understanding in conversational agents. Currently, his research focus has been in zero and few-shot learning in dialogue state tracking and intent detection. His ultimate goal is to develop agents which feel human-like in their understanding of speech. In his free time, he enjoy developing simple computer games.

João Bordalo

Bordalo holds a BSc degree in CS and is currently a MSc CS student. He has focused his studies in the fields of Machine Learning and Deep Learning. Currently he's researching multimodal models with a focus on Visual Question-Answering, looking to leverage state-of-the-art models for different applications related to Conversational Agents.

Inês Simões

Simões is a final year masters student in computer science and engineering. She is focused towards software engineering and her main focus is on requirement analysis and building a flexible conversational agent platform with support for automated testing. She will start her masters' thesis which will be based on these topics.

Rodrigo Valério

Valério is currently pursuing a MSc on general purpose vision-language models capable of solving multiple tasks with a single model. He has previously worked with multi-modal models in the conversational domain and has done research on optimizing techniques for computer vision models. His main objective is to reduce the cost of running high-cost applications which require multiple models by replacing them with general purpose models.

João Magalhães - Faculty advisor


Magalhaes is an Associate Professor at the Department of Computer Science of the Universidade NOVA de Lisboa. He holds a Ph.D. degree (2008) in Computer Science from Imperial College London, UK. His research interests cover the different problems of vision and language understanding and multimodal conversational search and AI. He is actively engaged in industry funded R&I projects (e.g. Amazon, Farfetch, BBC, VisionBox). He was the Faculty Advisor of the 2021 Alexa TaskBot Challenge team TWIZ. He was the General Chair of ACM Multimedia 2022 and is one of the organizers of the ACM Workshop in Multimodal Conversational AI.

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US, WA, Virtual Contact Center-WA
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US, WA, Seattle
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US, WA, Seattle
This is a unique opportunity to build technology and science that millions of people will use every day. Are you excited about working on large scale Natural Language Processing (NLP), Machine Learning (ML), and Deep Learning (DL)? We are embarking on a multi-year journey to improve the shopping experience for customers globally. Amazon Search team creates customer-focused search solutions and technologies that makes shopping delightful and effortless for our customers. Our goal is to understand what customers are looking for in whatever language happens to be their choice at the moment and help them find what they need in Amazon's vast catalog of billions of products. As Amazon expands to new geographies, we are faced with the unique challenge of maintaining the bar on Search Quality due to the diversity in user preferences, multilingual search and data scarcity in new locales. We are looking for an applied researcher to work on improving search on Amazon using NLP, ML, and DL technology. As an Applied Scientist, you will lead our efforts in query understanding, semantic matching (e.g. is a drone the same as quadcopter?), relevance ranking (what is a "funny halloween costume"?), language identification (did the customer just switch to their mother tongue?), machine translation (猫の餌を注文する). This is a highly visible role with a huge impact on Amazon customers and business. As part of this role, you will develop high precision, high recall, and low latency solutions for search. Your solutions should work for all languages that Amazon supports and will be used in all Amazon locales world-wide. You will develop scalable science and engineering solutions that work successfully in production. You will work with leaders to develop a strategic vision and long term plans to improve search globally. We are growing our collaborative group of engineers and applied scientists by expanding into new areas. This is a position on Global Search Quality team in Seattle Washington. We are moving fast to change the way Amazon search works. Together with a multi-disciplinary team you will work on building solutions with NLP/ML/DL at its core. Along the way, you’ll learn a ton, have fun and make a positive impact on millions of people. Come and join us as we invent new ways to delight Amazon customers.
US, WA, Seattle
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US, CA, San Francisco
The retail pricing science and research group is a team of scientists and economists who design and implement the analytics powering pricing for Amazon's on-line retail business. The team uses world-class analytics to make sure that the prices for all of Amazon's goods and services are aligned with Amazon's corporate goals. We are seeking an experienced high-energy Economist to help envision, design and build the next generation of retail pricing capabilities. You will work at the intersection of statistical inference, experimentation design, economic theory and machine learning to design new methods and pricing strategies for assessing pricing innovations. Roughly 85% of previous intern cohorts have converted to full time scientist employment at Amazon. If you are interested, please send your CV to our mailing list at econ-internship@amazon.com. Key job responsibilities Amazon's Pricing Science and Research team is seeking an Economist to help envision, design and build the next generation of pricing capabilities behind Amazon's on-line retail business. As an economist on our team, you will will have the opportunity to work with our unprecedented retail data to bring cutting edge research into real world applications, and communicate the insights we produce to our leadership. This position is perfect for someone who has a deep and broad analytic background and is passionate about using mathematical modeling and statistical analysis to make a real difference. You should be familiar with modern tools for data science and business analysis. We are particularly interested in candidates with research background in experimentation design, applied microeconomics, econometrics, statistical inference and/or finance. A day in the life Discussions with business partners, as well as product managers and tech leaders to understand the business problem. Brainstorming with other scientists and economists to design the right model for the problem in hand. Present the results and new ideas for existing or forward looking problems to leadership. Deep dive into the data. Modeling and creating working prototypes. Analyze the results and review with partners. Partnering with other scientists for research problems. About the team The retail pricing science and research group is a team of scientists and economists who design and implement the analytics powering pricing for Amazon's on-line retail business. The team uses world-class analytics to make sure that the prices for all of Amazon's goods and services are aligned with Amazon's corporate goals.
US, WA, Bellevue
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US, WA, Seattle
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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. We are looking for a PhD candidate with exposure to Program Evaluation/Causal Inference. Some knowledge of econometrics, as well as basic familiarity with Stata or R is necessary, and experience with SQL, Hadoop, Spark and Python would be 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 perform applied econometric analysis at Internet speed 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 scientist employment at Amazon. If you are interested, please send your CV to our mailing list at econ-internship@amazon.com.
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