Modeling context in answer sentence selection systems on a latency budget

2021
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Abstract
Answer Sentence Selection (AS2) is an efficient approach for the design of open-domain Question Answering (QA) systems. In order to achieve low latency, traditional AS2 models score question-answer pairs individually, ignoring any information from the document each potential answer was extracted from. In contrast, more computationally expensive models designed for machine reading comprehension tasks typically receive one or more passages as input, which often results in better accuracy. In this work, we present an approach to efficiently incorporate contextual information in AS2 models. For each answer candidate, we first use unsupervised similarity techniques to extract relevant sentences from its source document, which we then feed into an efficient transformer architecture fine-tuned for AS2. Our best approach, which leverages a multi-way attention architecture to efficiently encode context, improves 6% to 11% over noncontextual state of the art in AS2 with minimal impact on system latency. All experiments in this work were conducted in English.
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US, NY, New York
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US, CA, San Diego
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US, VA, Arlington
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US, WA, Seattle
Job summaryAre you passionate to join an innovative team of scientists who use machine learning and statistical techniques to create state-of-the-art solutions to help Selling Partners and Customers on Amazon? Want to work on the business that is the lifeblood of Amazon? Selling on Amazon is one of the fastest growing businesses at Amazon.com and empowers millions of entrepreneurs worldwide. Our team will invent and innovate across technology, processes and people to grow the program, improve engagement and satisfaction and enable scalable solutions.We are looking for an Economist to lead us to identify data-driven insight and opportunities to improve our seller recruitment strategy and drive new seller success. As a successful economist on our talented team of scientists and engineers, you will solve complex problems to identify actionable opportunities, and collaborate with engineering, research, and business teams for future innovation. You need to be a sophisticated user of econometric models and advanced quantitative techniques for answering specific business questions, and an expert at synthesizing and communicating insights and recommendations to audiences of varying levels of technical sophistication. You will continue to contribute to the research community, by working with economists and scientists across Amazon, as well as collaborating with academic researchers and publishing papers (www.aboutamazon.com/research).What you'll do:· Provide data-driven guidance and recommendations on strategic questions posed by the NSS leadership.· Design and analysis of account coverage experiments and define and analyze success metrics across sales team optimization, marketing and new seller education and recommendation programs.. Conduct, direct, and coordinate all phases of research projects, demonstrating skill in all stages of the analysis process, including defining key research questions, recommending measures, working with multiple data sources, evaluating methodology and design, executing analysis plans, interpreting and communicating results.· Provide technical and scientific guidance to your team members, both junior and senior.· Communicate effectively with senior management as well as with colleagues from science, engineering, and business backgrounds.
GB, London
Are you interested in delighting Alexa customers around the world? We have a unique position in the Alexa AI Knowledge team to solve interesting problems related to speech recognition and question-answering, across the languages we support.Our challenge is to ensure Alexa answers every question in any language, on any topic, at any time. "Who won the football match?", "How long till Diwali?", "How old is Dresden Cathedral?" We aim to answer these questions the first time they are asked in a way that’s natural, engaging and fun.We’re looking for an Applied Science Manager to lead a cross-functional team in developing novel techniques (e.g. deep neural network architectures) and deploying them to production toward our end goal of reducing the friction customers feel when Alexa doesn’t understand a user’s spoken question or when it requires repeating or rephrasing to get an answer. The ideal candidate has the requisite background and experience in building high-performing, collaborative teams. This person is versed in cutting-edge research and has an eye for hiring and developing talent.We have an opportunity to make a large and long-lasting impact for our customers. This job will test your skills across the board. Interesting problems? Check. Collaborative, curious and caring team? Check. Opportunities to invent at scale? Check. Opportunities to grow our exceptional talent? Check.Our challenges are big and the pace is fast. We provide a high-energy, empathetic, and supportive environment. Come join us if you like to put the customer at the center, invent, and think long-term. At Amazon, it's still Day 1.This position is based in London.
US, NY, New York City
Job summaryIn the Amazon Product Knowledge Team, we are building comprehensive schematic and semantic constructs to understand customer intent, in order to provide a delightful experience that feels targeted to their shopping mission. It expands beyond factual product characteristics (e.g. resolution of a TV) to additional dimensions used in customer shopping missions: what the product is used for (e.g. baby-proofing), where the product is used (e.g. kitchen), who uses the product (e.g. teenager), when the product is used (e.g. thanksgiving), and opinions about the product (e.g. cute t-shirt). We build scalable solutions that are partially or entirely powered by AI and ML to discover Product Knowledge by mining seller signals and customer engagements (e.g. search queries, customer reviews, web pages, etc).We have multiple positions for applied scientists who are excited to work on big data challenges including; web scale data integration, natural language processing, discovery of new relationships along with their semantics, knowledge inferencing and enhancement, knowledge embedding, entity recognition, and improving data quality to support strategic and tactical decision-making in building Product Knowledge.We are looking for applied scientists with experience in building practical solutions who can work closely with software engineers to ship and automate solutions in production. Our applied scientists also collaborate and partner with teams across Amazon to understand and reflect on how to create benefit for every customer.
US, CA, Pasadena
Job summaryJoin us in a historic endeavor to make Computer Vision accessible to the world with breakthrough research! The AWS AI Labs Computer Vision team has a world-leading team of researchers and academics. We develop the algorithms and models that power AWS computer vision services, such as Amazon Rekognition, Amazon Textract, and Amazon Lookout for Vision, and we conduct and publish long-term research in broad areas of computer vision.We are looking for a senior applied science manager to join us and make the AI revolution happen through innovative research inspired by customer needs. As a Senior Applied Science Manager, you will identify research directions, create and execute roadmaps for forward-looking research and communicate them to senior leadership. You will partner with product teams to define what’s feasible while pushing the envelope on what’s possible. You will work closely with engineering teams to bring research to production. You will manage and lead multiple teams of talented scientists and science leaders, and grow the team by attracting the best scientists in computer vision and deep learning. You are expected to develop innovative solutions to hard problems, and lead your teams to publish your research results at peer reviewed conferences and workshops.AWS, the world-leading provider of cloud services, has fostered the creation and growth of countless new businesses, and is a positive force for good. Our customers bring problems which will give scientists endless opportunities to see their research have a positive and immediate impact in the world. You will have the opportunity to partner with technology and business teams to solve real-world problems, have access to virtually endless data and computational resources, and to world-class engineers and developers that can help bring your ideas into the world.Our research themes include, but are not limited to: few-shot learning, transfer learning, unsupervised and semi-supervised methods, multimodal learning, semi-automated data annotation, large scale image and video recognition, face detection and recognition, document OCR and scene text recognition, document understanding, and geometric computer vision.We are currently located in the US (Seattle, Pasadena, and Bay Area) and Israel (Haifa and Tel Aviv). We are open to candidates interested in working either virtually or remotely from another Amazon location. Additional locations include San Diego and New York City.About Us 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.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, TN, Nashville
Job summaryAmazon’s vision is to be Earth’s safest place to work. As part of the vision to be Earth’s safest place to work, we are undertaking a multi-year initiative to reduce musculoskeletal disorders in our operations by 40% by 2025. The practice of Human Factors/Ergonomics within our company is key to achieving this goal. We are seeking a Human Factors and Ergonomics (HFE) Research Science Leader to spearhead applied research projects using advanced technologies that will translate to real world solutions and define industry leading best practices. We are looking for an exceptional researcher, someone that is excited to work on complex challenges for which a comprehensive scientific approach is necessary to drive solutions. Your investigations will define human factor /ergonomic thresholds resulting in design and implementation of safe and efficient workspaces and processes for our associates, and beyond.Key job responsibilitiesYour responsibilities include:1. Identifying cross organizational challenges for which a rigorous research approach is necessary to invent and simplify.2. Working with senior leadership to determine research strategy and direction.3. Initiating, leading, and managing complex laboratory and field-studies using state-of-the-art methodologies, including.a. Managing and mentoring of assigned project personnel.b. Developing of custom data acquisition and analysis software solutions.c. Seeding the translation of research findings to cross functional stakeholders in design, engineering, safety, and operational groups.4. Develop programs to ensure senior executives and decision makers in the organization are up to speed on important trends, tools, and technologies and how these may positively affect our operations.5. Expand our global focus by supporting distributed teams and building a global research presence.6. Enable learning and application of research skills by designers, engineers, and operational personnel by building programs, platforms, and toolkits that empower them to effectively conduct quality research.7. Travel to our various sites globally to lead and perform studies and gain in-depth operational feedback, up to 40% of your time.
US, WA, Virtual Location - Washington
Job summaryAmazon’s Employee Relations (ER) team is looking for a Data Scientist (DS) with a demonstrated passion for building innovative new analytics, models, tools and processes for our Employees and Leaders. Are you looking for an opportunity to build in a completely new space that will stretch you and force you to demonstrate your mastery of data science, data analytics, problem solving and enterprise wide deployments? This DS will lead new pioneering ideas from concept to reality and in this role—new bold ideas are always welcome. This DS will obsess over the Amazon employee experience and the employee voice across the organization. This DS will directly apply their knowledge to dig deep and help Amazon leaders gain actionable insights. Finding, prioritizing and resolving employee experience defects will be the mission every day. Thus, the challenge of this role is that it is never complete; we will always strive to push Amazon to be the Earth’s best employer.The Data Scientist will play a critical role in advancing our mission. You will join a tight-knit team of ER professionals, including HR, operational, program, product, tech and legal leaders. You will be supporting Amazon's World Wide Corporate, Consumer and Operations (WWCC & Ops) portfolio, and have direct impact on the daily work of over 1.3M+ Amazonians.Our projects span multiple organizations and require coordination of experimentation, economic and causal analysis, forecasting, dashboarding and predictive machine learning tools. We’re looking for an enthusiastic technical expert and storyteller to explore the world of Amazon data to generate insights—connecting employee experiences to decision makers in a compelling way backed by data. Your focus will cover all aspects of how we learn more about our employees, uncover problems that need to be solved, and validate the impact of our solutions. You will work with other thinkers, creators, and communicators to build the skills of the entire team to create a research-driven organization. You will invent, refine solutions from start to finish—data sets, queries, models, reports, dashboards, analyses—to answer business questions while ensuring we are meeting the needs of the business and team goals. You will draw on your knowledge of data science best practices, big data management fundamentals, and analysis principles to build solutions that enable effective, data-driven business decisions. You will learn the business context and technologies behind your team’s data infrastructure and work with customers (e.g., researchers, economists, data engineers, business intelligence engineers, product managers) and other internal partners to ensure deliverables are aligned with expectations.If you love getting to the “a-ha” moment, when the solution to a customer or employee problem reveals itself in the data— let’s talk!Key job responsibilities• Own the design, development, and maintenance of scalable solutions for analyses and models.• Create innovative, sophisticated analytic models to address critical issues but also meet key business criteria (cost/risk/business impact) and key technical criteria (reliability/validity/predictability)• Lead technical aspects of experiment design in collaboration with the greater ER team.• Find and create ways to measure the workforce experience at multiple levels in the organization.• Identify and advocate for technical options related to machine learning, data mining, and other statistical approaches• Document feasibility requirements, code comments and other technical documentation required to transfer knowledge to other technical staff and management• Write queries and have in-depth knowledge of the data available in area of responsibility.• Troubleshoot operational data-quality issues and review/audit existing ETL jobs and queries.• Collaborate on developing effective Dashboards to surface insights to senior leadership• Communicate pros and cons of analytic frameworks to the development team• Uncover drivers, impacts, and key influences on productivity and innovation outcomes• Develop predictive and optimization models for key applications• Navigate a variety of data sources, such as open text comments, survey results and free text fields inputs• Ability to work in a highly collaborative environment with peers that have a range of technical aptitudes• Maintain an understanding of the latest trends in data science and machine learning• Recommend improvements to back-end data sources for increased accuracy and simplicity.About the teamThe Employee Relations team is responsible for the identification of defects in our employee experience across all roles in the WWC & Ops organization and beyond. Finding these defects is not enough though; we are tasked with building and deploying products, tools and solutions to remove these defects. Our products and programs are always changing and we continually innovate to transform and improve the employee experience.
US, WA, Bellevue
Job summaryThe Amazon Air Science and Technology team is seeking an Applied Scientist to be part of a team solving complex aviation operations problems to reduce cost and improve performance. This is a blue-sky role that gives you a chance to bring optimization modeling, statistical modeling, machine learning advancements to data analytics for customer-facing solutions in complex industrial settings.You will work closely with product, research science and technical leaders throughout Amazon Air, Amazon Delivery Technology and Supply Chain Optimization and will be responsible for influencing funding decisions in areas of investment that you identify as critical future product offerings. You will partner with software developers and data scientists to build end-to-end data pipelines and production code, and you will have exposure to senior leadership as we communicate results and provide scientific guidance to the business. You will analyze large amounts of business data, build the machine learning or optimization models that will enable us to continually delight our customers worldwide.The ideal candidate will have extensive experience in Science work, business analytics and have the aptitude to incorporate new approaches and methodologies while dealing with ambiguities. Excellent business and communication skills are a must to develop and define key business questions and build models that answer those questions. You should have a demonstrated ability to think strategically and analytically about business, product, and technical challenges. Further, you must have the ability to build and communicate compelling value propositions, and work across the organization to achieve consensus. This role requires a strong passion for customers, a high level of comfort navigating ambiguity, and a keen sense of ownership and drive to deliver results.Tasks/ Responsibilities:· Partnership with the engineering and operations to drive modeling and design for complex business problems.· Design and prototype decision support tools (product) to automate standardized processes and optimize trade-offs across the full decision space.· Contribute to the mid- and long-term strategic planning studies and analysis.· Lead complex transportation modeling analyses to aid management in making key business decisions and set new policies.
US, WA, Seattle
Job summaryThe F3 (Fresh, Food, Fast) organization enables customers to buy fresh groceries, household essentials, and most popular products from Amazon.com. Our business is global and we lead the innovation in ultra-fast grocery delivery and physical stores experience (Just Walk Out technology) to delight customers more than ever before. As our business is rapidly scaling up, we need to continue developing and improving scalable economic and science solutions to support business growth and better customer experience.We are looking for an economist manager to build a team of scientist and determine the long-term vision for how we set prices in F3. In this cross-functional role, you will partner and work closely with SDEs, business stakeholders, finance, BIEs, and product managers to determine and execute on optimal pricing online and in stores. As a thought leader, you will clearly communicate your vision, models, and results to influence a variety of senior stakeholders. You and your team will apply a battery of economic (demand estimation, casual inference, time series forecasting, etc.) and ML (prediction, outlier detection, cluster analysis, NLP/NLU, etc.) methods. You will own the whole cycle of model development including ideation, prototyping, validation, experimentation, and integrating models into production systems while working with a dedicated team of SDEs.Key job responsibilities· Lead strategic vision for product pricing, define roadmaps, and write PRFAQs, while balancing multiple business objectives.· Build, manage, and coach a high-performing team of economists and scientists; review and audit modeling processes and results.· Set team priorities and help the team to choose the right science methods while balancing delivering high impact with raising the science bar at Amazon.· Lead global complex product launches from a scientific perspective including identifying key milestones, potential risks, and paths to mitigate risks.· Partner and work closely with a dedicated team of engineers to put scientific solutions in a production system.· Write technical and business-facing documents to clearly explain complex technical concepts to audiences with diverse business/scientific backgrounds.