"This technology will be transformative in ways we can barely comprehend"

A judge and some of the finalists from the Alexa Prize Grand Challenge 3 talk about the competition, the role of COVID-19, and the future of socialbots.

Human beings are social creatures, and conversations are what connect us—they enable us to share everything from the prosaic to the profound with the people that matter to us. Living through an era marked by pandemic-induced isolation means many of those conversations have shifted online, but the connection they provide remains essential.

So what happens when you replace one of the human participants in a conversation with a socialbot? What does it mean to have an engaging conversation with an AI assistant? How can that kind of conversation prove to be valuable, and can it provide its own kind of connection?

Application period for next Alexa Prize challenge opens

The Amazon Alexa Prize team encourages all interested teams to apply for the Grand Challenge 4 by 11:59 p.m. PST on October 6, 2020.

The participants in this year’s Alexa Prize contest are driven by those questions. Amazon recently announced that a team from Emory University has won the 2020 Alexa Prize. We talked to that team, along with a judge from this year’s competition, as well as representatives from the other finalist teams at Czech Technical University, Stanford University, University of California, Davis, and University of California, Santa Cruz. We wanted to learn what drives them to participate, how COVID-19 has influenced their work and what they see as the possibilities and challenges for socialbots moving forward.

Alexa Prize Grand Challenge 3 winners share their work | Amazon Science

Q: What inspired you to participate in this year’s competition?

Sarah Fillwock, team leader, Emora, Emory University: We had a group of students who were interested in dialogue system research, some of whom had actually participated in the Alexa Prize in its previous years, and we all knew that the Alexa Prize offers a really unique opportunity for anyone interested in this type of work. It is really exciting to use the Alexa device platform to launch a socialbot, because we are able to get hundreds of conversations a day between our socialbot and human users, which really allows for quick turnaround time when assessing whether or not our hypotheses and strategies are improving the performance of our dialogue system.

Marilyn Walker, faculty advisor, Athena, University of California, Santa Cruz: In our Natural Language and Dialogue Systems lab, our main research focus is dialogue management and language generation. Conversational AI is a very challenging problem, and we felt like we could have a research impact in this area. The field has been developing extremely quickly recently, and the Alexa Prize offers an opportunity to try out cutting-edge technologies in dialogue management and language generation on a large Alexa user population.

Amazon Alexa Prize Finalists 2020
The five Alexa Prize finalist teams: Czech Technical University in Prague; Emory University; Stanford University; the University of California, Davis; and the University of California, Santa Cruz.

Vrindavan (Davan) Harrison, team leader, Athena, UCSC: As academics, our primary focus is on research. This year’s competition aimed at being more research-oriented, allowing the teams to spend more time on developing new ideas.

Kai-Hui Liang, team lead, Gunrock, University of California, Davis: Our experience in last year’s competition motivated us to join again as we realized there is still a large room for improvement. I’m especially interested in how to find topics that engage users the most, including trying different ways to elicit and reason about users’ interests. How can we retrieve content that is relevant and interesting, and make the dialog flow more naturally?

Jan Pichl, team leader, Alquist, Czech Technical University: Since the first year of the Alexa Prize competition, we have been developing Alquist to deliver a wide range of topics with a closer focus on the most popular ones. The first Alquist guided a user through the conversation quite strictly. We learned quickly that we needed to introduce more flexibility and let the user be "in charge". With that in mind, we have been pushing Alquist in that direction. Moreover, we want Alquist to manage dialogue utilizing the knowledge graph, and suggest relevant information based on the previously discussed topics and entities.

Christopher D. Manning, faculty advisor, Chirpy Cardinal, Stanford University: It was our first time doing the Alexa Prize, and the team really hadn’t done advance preparation, so it’s all been a wild ride—by which I mean a lot of work and stress for everyone on the team. But it was super exciting that we were largely able to catch up with other leading teams who have been doing the competition for several years.

Hugh Howey, judge and science fiction author: Artificial intelligence is a passionate interest of mine. As a science fiction author, I have the freedom to write about most anything, but the one topic I keep coming back to is the impact that thinking machines already have on our lives and how that impact will only expand in the future. So any chance to be involved with those doing work and research in the field is a no-brainer for me. I leapt at the chance like a Boston Dynamics dog.

Q: What excites you about the potential of socialbots?

Hugh Howey (Judge): This technology will be transformative in ways we can barely comprehend. Right now, the human/computer interface is a bottleneck. It takes a long time for us to tell our computers what we want them to do, and they'll generally only do that thing the one time and forget what it learned. In the future, more and more of the trivial will be automated. This will free up human capital to tackle larger problems. It will also bring us together by removing language barriers, by helping those with disabilities, and eventually this technology will be available to anyone who needs it.

Jinho D. Choi, faculty advisor, Emory: It has been reported that more than 44 million adults in US have mental health issues such as anxiety or depression. We believe that developing an innovative socialbot that comforts people can really help those with mental health conditions, who are generally afraid of talking to other human beings. You may wonder how artificial intelligence can convey a human emotion such as caring. However, humans have used their own creations, such as arts and music, to comfort themselves. It is our vision to advance AI, the greatest invention of humankind, to help individuals learn more about their inner selves so they can feel more positive about themselves, and have a bigger impact in the world.

Ashwin Paranjape, co-team leader, Stanford: As socialbots become more sophisticated and prevalent, increasing numbers of people are chatting with them regularly. As the name suggests, socialbots have the potential to fulfill social needs, such as chit-chatting about everyday life, or providing support to a person struggling with mental health difficulties. Furthermore, socialbots could become a primary user interface through which we engage with the world—for example, chatting about the news, or discussing a book.

Sarah Fillwock, Emory: Our experience in this competition has really solidified this idea of the potential of socialbots being value to people who need support and are in troubling situations. I think that the most compelling role for socialbots in global challenges is to provide a supportive environment to allow people to express themselves, and explore their feelings with regard to whatever dramatic event is going on. This is especially important for vulnerable populations, such as those who do not have a strong social circle or have reduced social contact with others, prohibiting them from being able to achieve the feeling of being valued and understood.

Q: What are the main challenges to realizing that potential?

Abigail See, co-team leader, Stanford: Currently, socialbots struggle to make sense of long, involved conversations, and this limits their ability to talk about any topic in depth. To do this better, socialbots will need to understand what a particular user wants—not only in terms of discussion topics, but also what kind of conversation they want to have. Another important challenge is to allow users to take more initiative, and drive the conversation themselves. Currently, socialbots tend to take more initiative, to ensure the conversation stays within their capabilities. If we can make our socialbots more flexible, they will be much more useful and engaging to people.

Sarah Fillwock, Emory: One major challenge facing the field of dialogue system research is establishing a best practice for evaluation of the performance of dialogue approaches. There is currently a diverse set of evaluation strategies that the research community uses to determine how well their new dialogue approach performs. Another challenge is that dialogues are more than just a pattern-matching problem. Having a back-and-forth dialogue on any topic with another agent tends to involve planning towards achieving specific goals during the conversation as new information about your speaking partner is revealed. Dialogues also rely a lot on having a foundation of general world knowledge that you use to fully understand the implications of what the other person is saying.

Amazon releases Topical Chat dataset

The text-based collection of more than 235,000 utterances will help support high-quality, repeatable research in the field of dialogue systems.

Marilyn Walker, UCSC: There’s a shortage of large annotated conversational corpora for the task of open-domain conversation. For example, progress in NLU has been supported by large annotated corpora, such as Penn Treebank, however, there are currently no such publicly available corpora for open-domain conversation. Also, a rich model of individual users would enable much more natural conversations, but privacy issues currently make it difficult to build such models.

Hugh Howey (Judge): The challenge will be for our ethics and morality to keep up with our gizmos. We will be far more powerful in the future. I only hope we'll be more responsible as well.

Q: What role has the COVID-19 pandemic played in your work?

Jurik Juraska, team member, UCSC: The most immediate effect the onset of the pandemic had on our socialbot was, of course, that it could not just ignore this new dynamic situation. Our socialbot had to acknowledge this new development, as that was what most people were talking about at that point. We would thus have Athena bring up the topic at the beginning of the conversation, sympathizing with the users' current situation, but avoiding wallowing in the negative aspects of it. In the feedback that some users left, there were a number of expressions of gratitude for the ability to have a fun interaction with a socialbot at a time when direct social interaction with friends and family was greatly restricted.

Kai-Hui Liang, UC Davis: We noticed an evident difference in the way Alexa users reacted to popular topics. For example, before COVID-19, many users gave engaging responses when discussing their favorite sports to watch, their travel experiences, or events they plan to do over the weekend. After the breakout of COVID-19, more users replied saying there’s no sports game to watch or they are not able to travel. Therefore, we adapted our topics to better fit the situation. We added discussion about their life experience during the quarantine (eg. how their diet has changed or if they walk outside daily to stay healthy). We also observed more users having negative feelings potentially due to the quarantine. For instance, some users said they feel lonely and they miss their friends or family. Therefore, we enhanced our comforting module that expresses empathy through active listening.

Abigail See, Stanford: As the pandemic unfolded, we saw in real time how users changed their expectations of our socialbot. Not only did they want our bot to deliver up-to-date information, they also wanted it to show emotional understanding for the situation they were in.

Sarah Fillwock, Emory: When COVID became a significant societal issue, we tried two things: we had an experience-oriented COVID topic where our bot discussed with people how they felt about COVID in a sympathetic and reassuring atmosphere, and we had a fact-oriented COVID topic that gave objective information. What we observed was that people had a much stronger positive reaction to the experience-oriented COVID-19 approach than the fact-oriented COVID-19 approach, and seemed to prefer it when talking. This really gave us some empirical evidence that social agents have a strong potential to be helpful in times of turmoil by giving people a safe and caring space to talk about these major events in their life since people responded positively to our approach at doing this.

Q: Lastly, are there any particular advancements in the fields of NLU, dialogue management, conversational AI, etc., that you find promising?

Jan Pichl, Czech Technical University: It is exciting to see the capabilities of the Transformer-based models these days. They are able to generate large articles or even whole stories that are coherent. However, they demand a lot of computation power during the training phase and even during the runtime. Additionally, it is still challenging to use them in a socialbot when you need to work with constantly changing information about the world.

Abigail See, Stanford: As NLP researchers, we are amazed by the incredible pace of progress in the field. Since the last Alexa Prize in 2018, there have been game-changing advancements, particularly in the use of large pretrained language models to understand and generate language. The Alexa Prize offers a unique opportunity for us to apply these techniques, which so far have mostly been tested only on neat, well-defined tasks, and put them in front of real people, with all the messiness that entails! In particular, we were excited to explore the possibility of using neural generative models to chat with people. As recently as the 2018 Alexa Prize, these models generally performed poorly, and so were not used by any of the finalist teams. However, this year, these systems became an important backbone of our system.

Sarah Fillwock, Emory: The work people have been putting into incorporating common sense knowledge and common sense reasoning into dialogue systems is one of the most interesting directions of the current conversational AI field. A lot of the common sense knowledge we use is not explicitly detailed in any type of data set as people have learned them through physical experience or inference over time, so there isn’t necessarily any convenient way to currently accomplish this goal. There have been a lot of attempts to see how far a language modeling approach to dialogue agents can go, but even using huge dialogue data sets and highly complex models still results in hit-and-miss success at common sense information. I am really looking forward to the dialogue approaches and dialogue resources that more explicitly try to model this type of common sense knowledge.


View from space of a connected network around planet Earth representing the Internet of Things.
Get more from Amazon Science
Sign up for our monthly newsletter

Work with us

See more jobs
US, WA, Seattle
Amazon AI is looking for an Applied Scientist to join ourscience team in the area of Speech Processing and Conversational AI.Our organization develops the science that drives the cloud-based AIservices of AWS. Our mission is to put the power of AI into the handsof every developer. We seek to advance the state of the art in machinelearning to create services that delight our customers and meetreal-world business needs.As an Applied Scientist you will partner with talentedscientists and engineers to design, train, test, and deploy machinelearning models. You will contribute to innovative features, improveour services based on customer requirements and help maintain a highlyscalable data and model management infrastructure that supportscutting-edge research. You will be responsible for translatingbusiness and engineering requirements into deliverables and softwareproducts.We are looking for candidates who thrive in an exciting,fast-paced environment and who have a strong personal interest inlearning, researching, and creating new technologies with highcustomer impact.Prior domain knowledge in speech, natural language processing, orconversational AI is strongly preferred; solid knowledge of fundamentalsof statistics, machine learning, and deep learning isrequired. Candidates should possess strong software engineeringskills and several years of industry experience.About UsInclusive Team CultureHere at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.Work/Life BalanceOur team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.Mentorship & Career GrowthOur team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
US, NY, New York
Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products.Worldwide Ad Success team (WASE) is at the forefront of our amazing growth machine enabling our teams to deliver at scale. Our goal is to scale account management multifold by investing in strategic self-service applications that improve productivity of external advertising customers and internal account management executives. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities.As part of our team evolution we are investing in improving our understanding of the advertisers on Amazon through advanced ML modeling and building an ML service that delivers recommendations to advertisers and solves the prioritization and selection of most optimum recommendations and measure impact with explain-ability.We are moving fast and have the ability to shape our tech infrastructure that will combine science and scalable engineering at a rapid pace. We are looking for a senior Applied Scientist to join the team to drive key science methods and delivery of the project, working closely with product and engineering leads, as well as our leadership. This is a relatively new team, with a focused initiative. We’re a fast-growing team with high visibility from the leadership team and lots of new opportunities.As Senior Applied Scientist for this role you are:· Highly analytical: You solve problems in ways that can be backed up with verifiable data. You focus on driving processes, tools, and statistical methods which support rational decision-making.· Technically fearless: You aren't satisfied by performing 'as expected' and push the tech teams past conventional boundaries. Your dial goes to '11'.· Team obsessed: You help grow your team members to achieve outstanding results. You foster the creative atmosphere to let engineers and other PMs innovate, while holding them accountable for making smart decisions and delivering results.· Humbitious: You’re ambitious, yet humble. You recognize that there’s always opportunity for improvement and use introspection and feedback from teammates and peers to raise the bar for your team.· Engaged by ambiguity: You're able to explore new problem spaces with unique constraints and thus non-obvious solutions; you’re quick to identify any gaps in the team and the right person to fill them to best deliver value to customers.Why you love this opportunityAmazon is investing heavily in building a world-class advertising business. We are responsible for defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long-term growth. We deliver billions of ad impressions and millions of clicks daily and break fresh ground to create world-class products. We are highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit. With a broad mandate to experiment and innovate.Impact and Career GrowthYou will invent new shopper and advertiser experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon. Define a long-term science vision for our advertising business, driven fundamentally from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding.Team video https://youtu.be/zD_6Lzw8raEAmazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us
US, NY, New York
Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class productsThe Worldwide Ad Success team is at the head of this growth machine enabling our teams to deliver at scale. Our goal is to scale account management multifold by investing in strategic self-service applications that improve productivity of external advertising customers and internal account management executives. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities.As part of our team evolution we are investing to improve our understanding of the Advertisers on Amazon through advanced machine learning modeling and building an ML service that deliver optimum recommendations (to our Ad customers) and measure impact with explain-ability.As a Senior Data Scientist on this team you will:· Translate business questions and concerns into specific quantitative questions that can be answered with available data using sound methodologies. In cases where questions cannot be answered with available data, work with engineers to produce the required data.· Deliver with independence on challenging large scale problems with ambiguity.· Manage and drive the technical and analytical aspects of Advertiser segmentation; continually advance approach and methods.· Retrieve, synthesize, and present critical data in a format that is immediately useful to answering specific questions or improving system performance.· Analyze historical data to identify trends and support decision making.· Improve upon existing methodologies by developing new data sources, testing model enhancements, and fine-tuning model parameters.· Provide requirements to develop analytic capabilities, platforms, and pipelines.· Apply statistical or machine learning knowledge to specific business problems and data.· Formalize assumptions about how our systems are expected to work, create statistical definition of the outlier, and develop methods to systematically identify these outliers. Work out why such examples are outliers and define if any actions needed.· Given anecdotes about anomalies or generate automatic scripts to define anomalies, deep dive to explain why they happen, and identify fixes.· Build decision-making models and propose solution for the business problem you defined· Conduct written and verbal presentation to share insights and recommendations to audiences of varying levels of technical sophistication.· Utilize code (python or another object oriented language) for data analyzing and modeling algorithms.Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us
US, WA, Seattle
AWS Machine Learning product teams are responsible for identifying customer needs and building products and services to meet those needs. At AWS, you will work side-by-side with product teams to build products and services designed with fairness and explainability in mind.As a scientist on this team, you will:· understand in depth the technical and scientific issues related to ML fairness and explainability,· develop new solutions to solve problems in ML fairness and explainability,· help define the strategies, priorities and metrics for ML fairness and explainability,· help build and develop the AWS team, as needed, and· liase with internal and external stakeholders.About UsInclusive Team CultureHere at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences.Work/Life BalanceOur team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.Mentorship & Career GrowthOur team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
US, WA, Seattle
Are you passionate about applying formal verification, program analysis, constraint-solving, and theorem proving to real world problems? Do you want to create products that reduce complexity for customers, increase customer security posture, and are provably correct? If so, then we have an exciting opportunity for you. The EC2 Networking team at Amazon.com is looking for a passionate and innovative Applied Scientist.In this role, you will interact with internal teams and external customers to understand their networking requirements. You will apply your knowledge to propose solutions, create software prototypes, and productize prototypes into production systems using software development tools and methodologies. In addition, you will support and scale your solutions to meet the ever growing demand of customer use.Inclusive Team CultureHere at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.Work/Life BalanceOur team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.This position involves on-call responsibilities, typically for one week every two months. We don’t like getting paged in the middle of the night or on the weekend, so we work to ensure that our systems are fault tolerant. When we do get paged, we work together to resolve the root cause so that we don’t get paged for the same issue twice.Mentorship & Career GrowthOur team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
US, CA, Santa Clara
MULTIPLE POSITIONS AVAILABLEEntity: Amazon Development Center U.S., Inc., an Amazon.com CompanyTitle: Applied Scientist IILocation: Santa Clara, CAPosition Responsibilities:Participate in the design, development, evaluation, deployment and updating of data-driven models and analytical solutions for machine learning (ML) and/or natural language (NL) applications. Develop and/or apply statistical modeling techniques (e.g. Bayesian models and deep neural networks), optimization methods, and other ML techniques to different applications in business and engineering. Routinely build and deploy ML models on available data. Research and implement novel ML and statistical approaches to add value to the business. Mentor junior engineers and scientists.Amazon.com is an Equal Opportunity-Affirmative Action Employer - Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation.#0000
US, WA, Seattle
Amazon is building a world class advertising business and defining and delivering a collection of self-service performance advertising products that drive discovery and sales of merchandise. Our products are strategically important to our Retail and Marketplace businesses driving long term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities.Sponsored Products helps merchants, retail vendors, and brand owners succeed via native advertising that grows incremental sales of their products sold through Amazon. The Sponsored Products Ad Marketplace organization optimizes the systems and ad placements to match advertiser demand with publisher supply using a combination of machine learning, big data analytics, ultra-low latency high-volume engineering systems, and quantitative product focus. Our systems and algorithms operate on one of the world's largest product catalogs, matching shoppers with products - with a high relevance bar and strict latency constraints. Our goals are to help buyers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and to build a major, sustainable business that helps Amazon continuously innovate on behalf of all customers.As an Applied Scientist for the Sponsored Products Detail Page Allocation and Pricing team, you develop systems which make the final decision on which ads to show, where to place them on the page and how many ads to place. This also includes selection of various themes that would appear in detail pages. This is a challenging technical and business problem, which requires us to balance the interests of advertisers, shoppers, and Amazon. You'll develop a data-driven product strategy to define the right quantitative measures of shopper impact, using this to evaluate decisions and opportunities. You'll balance a portfolio of pragmatic and long-term investments to drive long term growth of the ads and retail businesses. You'll develop real-time algorithms to allocate billions of ads per day in advertising auctions.Job Responsibilities:· Build machine learning models and utilize data analysis to deliver scalable solutions to business problems.· Run A/B experiments, gather data, and perform statistical analysis.· Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.· Work closely with software engineers on detailed requirements, technical designs and implementation of end-to-end solutions in production.· Research new machine learning approaches.Impact and Career Growth:In this role you will have significant impact on this team as well as drive cross team projects that consist of Applied Scientists, Data Scientists, Economists, and Software Development Engineers. This is a highly visible role that will help take our products to the next level. You will work alongside many of the best and brightest science and engineering talent and the work you deliver will have a direct impact on customers and revenue!Why you love this opportunity:Amazon is investing heavily in building a world class advertising business and we are responsible for defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities.Team video ~ https://youtu.be/zD_6Lzw8raE
US, MA, Cambridge
Are you a passionate scientist in the area of computer vision and machine learning who is aspired to develop new and innovative technologies to new product categories? Are you interested in applying your deep knowledge to new and challenging areas? Are you looking to scale capabilities computer vision and machine learning capabilities to new workload sizes? Are you up to the task of delivering innovative and scalable technology that manages automated recognition of millions of items?You will be part of a passionate team whose missions is to push the frontier of computer vision and machine learning technology into the smart home application area. This is a great opportunity for you to innovate in this space by developing algorithms at the edge and in the cloud, and integrating them into consumer services to enable a premium customer experience. In this role, you will be an owner of the full algorithm development cycle, from sensor evaluation and data engineering to algorithm design, implementation, optimization and deployment. This position also requires experience with developing efficient software components on resource-constrained computing platforms on the edge. You will collaborate with different Amazon teams to make informed decisions on the best practices in machine learning to build highly-optimized integrated hardware and software platforms.Main Responsibilities· Apply best practices to investigate, acquire, process and analyze data sources for algorithm development.· Research and implement the state-of-the-art methods in computer vision and machine learning to deliver algorithms that meets product specifications.· Design, build algorithm evaluation frameworks, schedule and report algorithm performance on a regular basis.· Optimize and deploy algorithms on target hardware platforms.· Establish, develop and maintain frameworks and procedures for image sensor selection and evaluation and image quality monitoring.· Influence system design by making informed decisions on the selection of data sources, algorithms and sensors.
US, MA, Cambridge
Are you a passionate scientist in the area of computer vision and machine learning who is aspired to develop new and innovative technologies to new product categories? Are you interested in applying your deep knowledge to new and challenging areas? Are you looking to scale capabilities computer vision and machine learning capabilities to new workload sizes? Are you up to the task of delivering innovative and scalable technology that manages automated recognition of millions of items?You will be part of a passionate team whose missions is to push the frontier of computer vision and machine learning technology into the smart home application area. This is a great opportunity for you to innovate in this space by developing algorithms at the edge and in the cloud, and integrating them into consumer services to enable a premium customer experience. In this role, you will be an owner of the full algorithm development cycle, from sensor evaluation and data engineering to algorithm design, implementation, optimization and deployment. This position also requires experience with developing efficient software components on resource-constrained computing platforms on the edge. You will collaborate with different Amazon teams to make informed decisions on the best practices in machine learning to build highly-optimized integrated hardware and software platforms.Main Responsibilities· Apply best practices to investigate, acquire, process and analyze data sources for algorithm development.· Research and implement the state-of-the-art methods in computer vision and machine learning to deliver algorithms that meets product specifications.· Design, build algorithm evaluation frameworks, schedule and report algorithm performance on a regular basis.· Optimize and deploy algorithms on target hardware platforms.· Establish, develop and maintain frameworks and procedures for image sensor selection and evaluation and image quality monitoring.· Influence system design by making informed decisions on the selection of data sources, algorithms and sensors.
US, MA, Cambridge
Amazon Device team is looking for a Senior Applied Science Manager to lead the development of computer vision algorithm on the Edge. In this role, you will be the leader of our passionate, talented, and inventive scientists, to develop industry-leading Computer Vision (CV), and drive them successfully to production for the benefit of millions of Amazon Devices users.You will be our leader in our Boston office, and provide thought leadership to scientists and engineers to help invent and implement computer vision and machine learning algorithms. This is a unique, high visibility opportunity for a leader who wants to have business impact, and dive deep into computer vision problems. We are particularly interested in candidates with experience productizing edge-based computer vision systems.As a Senior Manager, Applied Science, you bring structure to ambiguous business problems and use science, logic, and practical experience to decompose them into straightforward, scalable solutions. You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems; you're interested in learning; and you acquire skills and expertise as needed.The ideal candidate is a strong, creative and highly-motivated Scientist with hands-on experience in leading multiple research and engineering initiatives. You balance technical leadership with strong business judgment to make the right decisions about technology, tools, and methodologies.
DE, BE, Berlin
Would you like to join the team that protects the global AWS platform from fraud? Do you enjoy thinking like a fraudster and using your technical skills to help detect & mitigate AWS accounts from being compromised? If so, AWS Fraud Prevention has an exciting opportunity for you.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. AWS Platform is the glue that holds the AWS ecosystem together. Whether its Identity features such as access management and sign on, cryptography, console, builder & developer tools, and even 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.The AWS Fraud Prevention Compromise vertical is responsible for detecting & mitigating AWS account compromise. You’ll be part of a team of Data Scientists, Investigations Analysts, and Technical & non-Technical Program Managers. The team’s goal is to identify and neutralize fraudsters from compromising AWS customers’ accounts.As a Data Scientist, you will work directly with Business Analysts and Software Development Engineers to monitor the flavor/ trend of compromise on AWS worldwide and design appropriate solutions to respond in a collaborative environment. There are no walls, and success is determined by your ability to dive deep, and understand the subtle demands new and complex services will place upon systems and teams.As a Data Scientist your responsibilities will include:· Apply state-of-the-art Machine Learning methods to large amounts of data from different sources to build and productionalize fraud prevention, detection and mitigation solutions· Deep dive on the problems using SQL and scripting languages like Python/R to drive short term and long term solutions leveraging Statistical Analysis· Analyze data (past customer behavior, sales inputs, and other sources) to figure out trends, create compromise prevention and mitigation solutions and output reports with clear recommendations· Collaborate closely with the development team to recommend and build innovations based on Data Science· Manage your own process: identify and execute on high impact projects, triage external requests, and make sure you bring projects to conclusion in time for the results to be usefulLearn 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.Learn more about Amazon on our Day 1 Blog: https://blog.aboutamazon.com
US, NY, New York
Excited by the disruptive potential of quantum technology? Want to innovate on behalf of our customers to build quantum computing tools for the cloud? Thrilled to be key part of Amazon, who has been investing in disruptive innovation for decades, pioneering and shaping the world’s technology?Amazon Braket is looking for Applied Scientists in quantum computing to join an exceptional team of researchers and engineers. Quantum computing is rapidly emerging from the realms of science-fiction, and our customers can the see the potential it has to address their challenges. One of our missions at AWS is to give customers access to the most innovative technology available and help them continuously reinvent their business. Quantum computing is a technology that holds promise to be transformational in many industries, and with Amazon Braket we are adding quantum computing resources to the toolkits of every researcher and developer.As an Applied Scientist in the Amazon Braket team, you will develop advanced software solutions for construction, compilation, simulation, and optimization of quantum computing programs in the cloud. You will play a key role in shaping the development roadmap of the service, and evangelizing new features and capabilities. You will also have the opportunity to create white papers, write blogs, build demos and generate other reusable collateral that can be used by our customers. Most importantly, you will work closely with our quantum computing research teams, as well as industry and academic partners. Our team collaborates across the entire AWS organization to get drive innovation and deliver the right solutions to our customers.A successful candidate will be a person who enjoys diving deep into customer problems, conducting independent research and development, working across teams with academic and industry experts, and shaping the long-term QC strategy for AWS and its customers. It will be a person who likes to have fun, loves to learn, and wants to innovate in the world of QC.
US, WA, Seattle
Excited by the disruptive potential of quantum technology? Want to innovate on behalf of our customers to build quantum computing tools for the cloud? Thrilled to be key part of Amazon, who has been investing in disruptive innovation for decades, pioneering and shaping the world’s technology?Amazon Braket is looking for Applied Scientists in quantum computing to join an exceptional team of researchers and engineers. Quantum computing is rapidly emerging from the realms of science-fiction, and our customers can the see the potential it has to address their challenges. One of our missions at AWS is to give customers access to the most innovative technology available and help them continuously reinvent their business. Quantum computing is a technology that holds promise to be transformational in many industries, and with Amazon Braket we are adding quantum computing resources to the toolkits of every researcher and developer.As an Applied Scientist in the Amazon Braket team, you will develop advanced software solutions for construction, compilation, simulation, and optimization of quantum computing programs in the cloud. You will play a key role in shaping the development roadmap of the service, and evangelizing new features and capabilities. You will also have the opportunity to create white papers, write blogs, build demos and generate other reusable collateral that can be used by our customers. Most importantly, you will work closely with our quantum computing research teams, as well as industry and academic partners. Our team collaborates across the entire AWS organization to get drive innovation and deliver the right solutions to our customers.A successful candidate will be a person who enjoys diving deep into customer problems, conducting independent research and development, working across teams with academic and industry experts, and shaping the long-term QC strategy for AWS and its customers. It will be a person who likes to have fun, loves to learn, and wants to innovate in the world of QC.
US, CA, Sunnyvale
Are you a passionate scientist in the area of computer vision and machine learning who is aspired to develop new and innovative technologies to new product categories? Are you interested in applying your deep knowledge to new and challenging areas? Are you looking to scale capabilities computer vision and machine learning capabilities to new workload sizes? Are you up to the task of delivering innovative and scalable technology that manages automated recognition of millions of items?You will be part of a passionate team whose missions is to push the frontier of computer vision and machine learning technology into the smart home application area. This is a great opportunity for you to innovate in this space by developing algorithms at the edge and in the cloud, and integrating them into consumer services to enable a premium customer experience. In this role, you will be an owner of the full algorithm development cycle, from sensor evaluation and data engineering to algorithm design, implementation, optimization and deployment. This position also requires experience with developing efficient software components on resource-constrained computing platforms on the edge. You will collaborate with different Amazon teams to make informed decisions on the best practices in machine learning to build highly-optimized integrated hardware and software platforms.Main Responsibilities· Apply best practices to investigate, acquire, process and analyze data sources for algorithm development.· Research and implement the state-of-the-art methods in computer vision and machine learning to deliver algorithms that meets product specifications.· Design, build algorithm evaluation frameworks, schedule and report algorithm performance on a regular basis.· Optimize and deploy algorithms on target hardware platforms.· Establish, develop and maintain frameworks and procedures for image sensor selection and evaluation and image quality monitoring.· Influence system design by making informed decisions on the selection of data sources, algorithms and sensors.
US, WA, Seattle
Amazon is looking for a passionate, talented, and inventive Machine Learning Scientist with a strong machine learning background to help build industry-leading Alexa Speech and Language technology. Our mission is to push the envelope in Deep Learning, Automatic Speech Recognition (ASR) and Language Modeling in Natural Language Processing (NLP), in order to provide the best-possible experience for our customers.Our Machine Learning Scientists, work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art in spoken language. Your work will directly impact our customers in speech and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in spoken language understanding. Candidates can work in Seattle OR Sunnyvale.
GB, London
Amazon Softlines Private Brands (SPB) is looking for a data scientist to steer the direction of a global project in partnership with a technology teams across Amazon. This role will be a part of a global product team that works on programmatic solutions to improve WW SPB Catalog Quality to offer the best search, browse and detail page experience to our customers. This team comprises of three product managers in London, one product manager in US, one product manager in JP. In addition, we fund SDE resources in our partner teams to drive our automation agenda.Our strategy involves:1) Defect elimination: we partner with technology teams within Amazon such as ASIN localization, Amazon Selection and Catalog System, Private Brands Central to fix root causes prevent defects generation at creation.2) Defect remediation: using image based Machine Learning and other logic based/deterministic rules which cause a bad customer experience.We are seeking a highly motivated Data Scientist with a passion to work on complex strategic problems that ultimately raise the bar for our customers, while maximizing business impact. You are passionate about providing insights from data and have experience in working with large data sets. You are organized, efficient and insist on the highest standards. You are an independent self-starter who thrives on owning projects. You will be required to make important decisions on the technical structure of the project from data pipelines, data models and roadmaps.Sound like you? We'd love to hear from you.The primary responsibilities include:· Help answers fundamental questions of correlation between input and outputs, investment opportunities given limited resources.· Lead the thinking on Python rule writing for deterministic checks. You will have dotted lining reporting of a Research Analyst to do the actual rule writing· Lead the data flow to collect the defects identified from ML and deterministic rule and pass to dashboard and remediation teams· Translate the requirements of the project into technical requests to the partner tech teams
US, WA, Seattle
Amazon is looking for an ASR/NLP domain expert, someone who will contribute to our long-term research efforts.Our mission is to push the envelope in Automatic Speech Recognition (ASR), NLP, Audio Signal Processing and Dialog Management, in order to provide the best-possible experience for our customers. Candidates can work in Seattle OR Sunnyvale!As a Senior Speech and Language Scientist, you will work with talented peers to research ASR/NLP and contribute to our long-term research efforts. Your work will directly impact our customers in the form of products and services that make use of speech and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in spoken language understanding.
US, WA, Seattle
Are you interested in playing a pivotal role in building innovative technology that protects Amazon’s customers? Threat Detection Technologies team, in Customer Engagement Technologies (CET) group, is responsible for automating detection of cyber-security threats in Amazon's global contact center network. Among other things, we build monitoring systems that collect data at scale, and use machine learning (ML) to detect adversarial action in our systems.We are looking for a Data Scientist to join our Threat Engineering and Development team. As a Data Scientist, you will complement our strengths and apply your data science skills, and tradecraft, to analyze terabytes of user behavior data, to detect threatening behaviors. You will build threat detection models and algorithms, which will be used to detect attacks and raise security investigations. You need to be highly motivated, eager to learn and be curious, and resourceful in finding novel ways to analyze data in order to produce actionable threat indicators.This is a highly visible role that requires partnering with multiple organizations, security, and technology teams in order to extract the intelligence and effect change. You must have the experience and capability to create and present documentation to champion security causes. Excellent written and verbal communication skills are essential. You must be experienced in working with data to analyze and detect trends, outliers, and have advanced analytical, mathematical, and quantitative abilities.Amazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation.
US, CA, Sunnyvale
Do you want to join Alexa AI -- the science team behind Amazon’s intelligence voice assistance system? Do you want to utilize cutting-edge deep-learning and machine learning algorithms to delight millions of Alexa users around the world?If your answers to these questions are “yes”, then come join the Alexa Artificial Intelligence team. We are responsible for the deep learning technology that is central to the automated ranking and arbitration to optimize for end-to-end customer satisfaction.As a Senior Applied Scientist you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art in spoken language understanding. Your work will directly impact our customers in the form of products and services that make use of speech and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in spoken language understanding.
US, CA, Palo Alto
Are you ready to drive the next generation of shopping innovations at Amazon? When words just aren’t enough to describe what customers are looking for, they often turn to other methods such as camera-based search, or using the picture of a celebrity to find inspiration for their fashion purchases. When images aren’t enough to convince customers that a piece of furniture will look good, they want to turn to Augmented Reality to envision how that furniture item would match their living room décor.Starting in 2009, the Visual Search & Augmented Reality team has thus far launched many visual search solutions on the Amazon App that use computer vision and machine learning/deep learning to help customers complete their shopping missions more easily; multiple internal teams at Amazon (devices, Kindle, Seller services, etc.) also use our libraries and APIs to deliver solutions to their own customers. We are a full stack shop, and our team capabilities cover the whole solution spectrum, ranging across applied science (Computer Vision and Deep Learning), large scale engineering services, product management, UX design, and mobile app development for iOS and Android. However, it’s still Day 1, and this is your chance to make history in the new era of shopping.As an Applied Scientist on the VS&AR team, you will:· Investigate and solve exciting and difficult challenges in image recognition, classification, segmentation, 3D computer vision, augmented reality and deep learning.· Research and develop scalable computer vision and machine learning solutions to hard problems.· Design, implement, and deploy full-stack computer vision solutions for millions of Amazon customers.· Build on core technology in Visual Search and Augmented Reality.· Use the latest advances in neural networks and machine learning to bring new experiences for our customers.You are going to love this job because you will:· Be immersed in a "critical mass” of innovative and top caliber computer vision experts in a collegial and fun environment.· Work on incredibly hard problems in computer vision that are of value in the real world.· Create world-class computer vision products.· Build on Amazon’s tools and vast technical resources.· Work in a dynamic team that provides continuous opportunities for learning and growth.Please visit https://www.amazon.science for more information