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Amazon and the Massachusetts Institute of Technology announced the establishment of the Science Hub, a collaboration that will focus on areas of mutual interest, beginning with artificial intelligence and robotics. Amazon will provide funding to support research and academic fellowships.
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Robotics

Amazon and MIT establish Science Hub

The collaboration will support research, education, and outreach efforts in areas of mutual interest, beginning with artificial intelligence and robotics.

By Staff writer
October 04, 2021
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Amazon and MIT today announced the establishment of the Science Hub, a collaboration that will focus on areas of mutual interest, beginning with artificial intelligence and robotics in the first year. To get the hub started, Amazon will provide gift and sponsored research funding over the next five years to support research and academic fellowships on campus.

The primary goals of the hub are to ensure the benefits of AI and robotics innovations are shared broadly — both through education and by advancing research — and to broaden participation in the research from diverse, interdisciplinary scholars, and other innovators.

Aude Oliva, a senior research scientist and director of strategic industry engagement in the MIT Schwarzman College of Computing
Aude Oliva, a senior research scientist and director of strategic industry engagement in the MIT Schwarzman College of Computing

“AI and robotics have an enormous impact on every aspect of our lives, fundamentally changing how we work, learn, access resources and services, and connect to one another — so it’s critical we conduct research that advances the field in ways that are responsible, effective, and beneficial to society,” said Aude Oliva, a senior research scientist and director of strategic industry engagement in the MIT Schwarzman College of Computing. “We take an expansive view of AI and robotics to include expertise from across all five of the Institute’s schools. We’re excited by the potential of collaborations with industry leaders who bring their insights to the research, want to support the next generation of talent, and are best positioned to implement what is learned.”

Oliva will serve as the principal investigator for the Science Hub, which will be administered at MIT by the Schwarzman College of Computing, a cross-cutting entity with education and research links across MIT to increase connections in computing and AI.

Amazon’s support of the new Science Hub underscores a continuing commitment to collaborating with academia on research efforts as well as helping to fund the education and training of future scientists who reflect the diversity of perspectives and expertise at Amazon, MIT, and around the world.

Tye Brady, MIT alumni and Amazon Robotics chief technologist, noted that Amazon’s existing relationship with a number of MIT faculty helped lay the groundwork for the collaboration.

“Over the years we’ve worked with great people at MIT like Russ Tedrake, Alberto Rodriguez, Daniela Rus, Julie Shah, and Nicholas Roy,” Brady said. “Their hard work and ability to perform world class research is a model for what is possible when industry and academia work together.”

We are particularly keen to utilize the breadth of collaboration mechanisms available in the new hub, including sponsored research which could lead to open-source publications and community outreach.
Siddhartha Srinivasa

The gift will enable a broad set of programs across MIT, including fellowships that will be awarded annually to graduate students and postdoctoral researchers, as well as support for events and activities that accelerate AI and robotics research in ways to make it more accessible, such as research symposia that are open to other academic institutions and the public. Additional sponsored research funds will support research projects led by MIT faculty members.

“We are delighted to join forces with MIT, bringing together top scientists and engineers from our two organizations in a joint endeavor to find solutions to the most challenging problems in AI and robotics,” Brady said. “MIT’s well-established record of conducting leading-edge, multi-disciplinary research paired with Amazon’s emphasis on translating research into applied science will help ensure the new hub results in practical solutions whose benefits extend beyond industry and academia.”

“We are particularly keen to utilize the breadth of collaboration mechanisms available in the new hub, including sponsored research which could lead to open-source publications and community outreach that will broaden participation in the research process,” added Siddhartha Srinivasa director, Amazon Robotics AI. “These mechanisms are now open to all the business areas of Amazon beyond Robotics too, so we are excited to see the breadth of innovation to come from this collaboration in the coming years.”

Amazon in Massachusetts

The Science Hub complements existing collaborations between Amazon and MIT, and Amazon’s research presence in the Boston area, including an Alexa science team in Cambridge.

Dating back to 2003, Amazon has had a longstanding engagement with the MIT Leaders for Global Operations, focusing on data analytics, supply chain and systems optimization research.

Earlier this year, the Amazon Last Mile team announced a collaboration with MIT’s Center for Transportation & Logistics (MIT CTL) with the aim of incorporating driver know-how into route optimization models. The two groups sponsored a competition, called the Amazon Last Mile Routing Research Challenge, in which academic teams trained machine learning models to predict the delivery routes chosen by experienced drivers. The winners of that competition were announced recently.

In addition, Amazon’s Core AI team in Boston features three MIT faculty currently working as Amazon Scholars: Victor Chernozhukov, the International Ford Professor in the MIT Department of Economics and Statistics and Data Science Center; Yury Polyanskiy, associate professor in the MIT Department of Electrical Engineering and Computer Science, Institute for Data, Systems, and Society, Laboratory for Information and Decision Systems, and Statistics and Data Center; and Alexander Rakhlin, professor in the MIT Department of Brain and Cognitive Sciences and Statistics and Data Science Center.

Amazon is also building a new state-of-the-art robotics innovation center in Westborough, Mass. Opening this fall, the company is investing more than $40 million in the new site to allow Amazon Robotics to continue to grow its engineering, manufacturing, support and test teams in the state. The new 350,000 square feet facility will feature corporate offices, research and development labs, and manufacturing space and will be in addition to Amazon Robotics’ current site in North Reading — together serving as the company’s epicenter of robotics innovation.

Amazon also announced plans earlier this year to expand its Boston Tech Hub. The expansion will create 3,000 jobs which will include technology roles in software development, artificial intelligence, and machine learning, along with non-tech corporate roles in product management, HR, finance, and more. Amazon has invested more than $10 billion in Massachusetts over the past decade, including opening five fulfillment and sortation centers, 13 delivery stations, and 33 Whole Foods Market locations. Those investments have helped to create more than 20,000 full- and part-time jobs across the state.

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Applied Scientist, LakeFormation
US, VA, Arlington
Job summaryThe Group:The Database Services group provides rapidly growing, industry acclaimed cloud services in areas of big data platforms, data warehouses, analytics, and operational databases. The group is at the forefront of innovation in these areas producing world-class cloud services, which while large profitable businesses, are also in their infancy. They represent a large fraction of the AWS business, and continue to accelerate.The Team:Lake Formation is our fully managed service to simplify building and securing data lakes. It features Blueprints to ingest data from commons sources, ML transforms to clean and de-duplicate data and a unified security model with fine-grained permissions (at the database, table, and column level) that are applicable across a wide range of AWS analytic and ML services (Redshift Spectrum, Glue, EMR Spark, QuickSight).The Lake Formation team is looking for an Applied Scientist with experience in building secure, scalable solutions that delight customers. 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. You have strong verbal and written communication skills, are self-driven and deliver high quality results in a fast-paced environment.Technical Responsibilities:· Interact with various teams to develop an understanding of their security and safety requirements.· Apply the acquired knowledge to build tools find problems, or show the absence of security/safety problems.· Implement these tools through the use of SAT, SMT, BDDs, and various concepts from programming languages, theorem proving, formal verification and constraint solving.· Perform analysis of the customer systems using tools developed in-house or externally provided· Create software prototypes to verify and validate the devised solutions methodologies; integrate the prototypes into production systems using standard software development tools and methodologies.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 we 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.
Applied Scientist, TMT - Outbound
US, WA, Seattle
Job summaryAre you passionate about big data and machine learning? Do you enjoy solving complex analytical problems, build predictive analytics models and develop insights and recommendations at web scale? Do you want to make an impact in Amazon’s multi-billion-dollar Messaging business? Amazon’s Outbound Communication Services, OCS, owns foundational systems that power all of Amazon's customer-facing communication on Email, SMS, Push channels, and other emerging messaging applications. In 2020, we sent over 100 billion messages to our global customers on these channels! OCS builds self-governing and message-optimizing engines that leverage integrated Machine Learning, massive data processing and adaptive algorithms to deliver the best messages to Amazon’s customers, over the best channel, and at the right time. Our systems ensure best-in-class engagement experience, which spans transactional and marketing communications. We're building a top-notch team of engineers, applied scientists, data engineers, and engineering leaders. The problems we face are complex and interesting including information engineering, data mining of Big Data sets, and governing real-time messages at scale. We build large scale, distributed systems using multiple AWS services that we designed from the ground up.We are looking for a strong Applied Scientist to work backwards from customers, create models and develop insights, deliver impact, and drive growth of the OCS worldwide. As a Senior Applied Scientist on our team, you will be working with business stakeholders, product/program managers, developers and executives to deeply understand customer problems and priorities. You will form hypotheses, analyze the corpus of Outbound and Amazon data using statistical methods, build predictive models, generate recommendations to address a range of problems to optimize the value of the messages we send to our customers. These span developing insights on customer engagement trends, building models to inform message rates, channel selection, and defining segmentation for marketing, etc. Your expertise will enable us to enable new customer experiences while maintaining best-in-class customer experience. You will be comfortable with big data systems, intimately familiar with advanced machine learning and statistical methods, and experienced in applying these to solve business problems. You will have a strong bias towards customer obsession and delivering results while dealing with ambiguity in fast-paced dynamic environments.Roles and Responsibilities· Work with business teams, product/program managers, engineers and leadership to identify and prioritize customer and business problems· Translate these problems into specific analytical questions and form hypotheses that can be answered with available data using statistical methods or identify additional data needed in the master datasets to fill any gaps· Perform hand-on data analyses and modeling with huge datasets to develop insights and recommendations to inform decisions across the program· Design and run A/B experiments to validate the hypotheses and evaluate the impact of your optimizations and communicate your results to various stakeholders· Collaborate with engineers and product managers to build scalable solutions and new capabilities· Help on projects of high visibility across the organization and deliver business impact
Applied Scientist, Alexa AI
US, MA, Cambridge
Job summaryThe Alexa Artificial Intelligence (AI) team is looking for a passionate, talented, and inventive Applied Scientist with a strong machine learning background to help build industry-leading Speech and Language technology. Our mission is to push the envelope in Automatic Speech Recognition (ASR), Natural Language Understanding (NLU), and Audio Signal Processing, in order to provide the best-possible experience for our customers.Key job responsibilitiesAs an 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.
Principal Research Scientist, Modeling and Optimization
US, WA, Bellevue
Job summaryAmazon’s Modeling and Optimization Team is looking for a senior science leader (Principal Research Scientist) to drive the development and optimization of the most complex transportation and fulfillment network in the world.The team is responsible for optimizing the global transportation and fulfillment network for Amazon.com and ensuring that the company is able to deliver our customers’ products to them as quickly, accurately, and cost effectively as possible. We design the network that delivers packages from fulfillment centers (FCs) to end customers, through both Amazon’s internal network as well as external partners, using ground and air methods. Optimizing these package flows requires designing the structure and operating parameters of the network, optimizing operations such as linehaul movements and sortation scheduling, and making the right capital investments in technology, buildings and equipment. It also requires partnering with peer research and product teams that drive inventory placement, selection, and forecasting, and incorporating information and algorithmic interfaces with those systems.We are seeking an experienced multi-disciplinary science leader, to lead the science development on projects in both developing algorithmic tools and driving long-term network strategy. In this role, you will work with and advise other research scientists in the team, develop your own scientific approaches, and partner with software and product teams as they deploy algorithmic solutions to our stakeholders. You will also partner with business leaders on projects that evaluate long-term strategic network choices, and present strategy papers to our senior-most leaders to drive long-term impact.To accomplish this, we expect you to have a strong research background in at least one of the following disciplines: operations research, computer science, operations management, statistics, or applied mathematics. You should also have business domain knowledge in transportation and distribution operations, along with some knowledge of inventory management theory and practice. You should have a strong publication record that demonstrates technical depth as well as consideration of practical aspects in your work. Experience partnering with companies on high-stakes R&D or consulting is a plus, but not a necessity.
Applied Scientist - AWS ML Platforms
US, VA, Arlington
Job summaryInterested in machine learning and AI? Can you envision a future where technology is driven primarily by smarter machines?The mission of AWS AI is to make machine learning easy, fast, and universal across all of our customers. Our world class platform provides the services that runs 85% of all on-cloud machine learning through performance optimizations, machine learning tools, and SDKs to democratize machine learning. Our customers include scientists, data analysts, and ML engineers all building and deploying models through either SageMaker or self-managed instances on EC2/EKS.The AWS Machine Learning Services group in Amazon AI is seeking applicants for an applied scientist position in the areas of fairness, bias, explainability, privacy, and model understanding in ML. As an applied scientist in AWS AI, you will be driving many scientific breakthroughs to help our customers understand and trust ML-based outcomes, and also working with software engineers to deploy these solutions to AWS customers. You will be working on the ML platforms and services that power over 85% of machine learning in the cloud, and help make machine learning fast, accessible, universal, and trustworthy for all our customers.We look for candidates with PhD in a relevant technical field (such as Algorithms, Machine Learning, AI, and Mathematics), preferably with interest / experience in explainability, fairness, privacy, and model understanding. We also encourage graduating PhD students as well as recent PhD graduates to apply. You will be working closely with software engineers so experience with cloud systems is a benefit. Our customers are deeply technical and the solutions we build for them are strongly coupled to technical feasibility. You must be able to thrive and succeed in an entrepreneurial environment, and not be hindered by ambiguity or competing priorities. This means you are not only able to develop and drive high-level strategic initiatives, but can also roll up your sleeves, dig in and get the job done. Ownership, high judgment, negotiation skills, ability to influence, analytical talent and leadership are essential to success in this role.For more information about AWS AI team, please see https://aws.amazon.com/machine-learning and https://aws.amazon.com/sagemaker.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. 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.
Applied Scientist II
US, WA, Seattle
The Team: Amazon Go is a new kind of store with no lines and no checkout—you just grab and go! Customers simply use the Amazon Go app to enter the store, take what they want from our selection of fresh, delicious meals and grocery essentials, and go!Our checkout-free shopping experience is made possible by our Just Walk Out Technology, which automatically detects when products are taken from or returned to the shelves and keeps track of them in a virtual cart. When you’re done shopping, you can just leave the store. Shortly after, we’ll charge your Amazon account and send you a receipt. Check it out at amazon.com/go. Designed and custom-built by Amazonians, our Just Walk Out Technology uses a variety of technologies including computer vision, sensor fusion, and advanced machine learning. Innovation is part of our DNA! Our goal is to be Earths’ most customer centric company and we are just getting started. We need people who want to join an ambitious program that continues to push the state of the art in computer vision, machine learning, distributed systems and hardware design.The Role: Everyone on the team needs to be entrepreneurial, wear many hats and work in a highly collaborative environment that’s more startup than big company. We’ll need to tackle problems that span a variety of domains: computer vision, image recognition, machine learning, real-time and distributed systems.As a Computer Vision Research Scientist, you will help solve a variety of technical challenges and mentor other engineers. You will tackle challenging, novel situations every day and given the size of this initiative, you’ll have the opportunity to work with multiple technical teams at Amazon in different locations. You should be comfortable with a degree of ambiguity that’s higher than most projects and relish the idea of solving problems that, frankly, haven’t been solved at scale before - anywhere. Along the way, we guarantee that you’ll learn a ton, have fun and make a positive impact on millions of people.
Sr. Data Scientist, Selling Partner Development Science
US, WA, Seattle
Job summaryJoin us in the evolution of Amazon’s consumer business!The Brand Program and Selling Partner Development organization is the growth and development engine for our Store. Our business grows when our Selling Partners (SPs) businesses’ grow. We aspire to make Amazon the best place for Selling Partners to sell and measure our progress towards this goal through a combination of metrics. We make it easy and predictable for Selling Partners to achieve a great Customer Experience. We believe all motivated Selling Partners that provide a great Customer Experience should be able to grow their business on Amazon either guided by unambiguous self-service tools or by a named Account Manager (AM) working from the same set of recommendations and insights. By ensuring that the same set of recommendations and insights are used, we democratize growth, increase predictability and build trust with our SPs. Our front line AMs drive a virtuous flywheel of learning, experimentation, development and scale that accelerates our store and improves the Customer Experience.We have numerous, durable, deep, technical and interesting problems for Sr. Data Scientist to own. We are looking for a Sr. Data Scientist to design and implement deep tools, insights, metrics and models (inclusive of AI) to lead our systems and tools. You will work with a range of strategic functions within the consumer organization. Our broader org. certainly embodies a start-up mentality. You will work closely with data engineers, software developers, product managers to come up with solution end-to-end with cutting edge machine learning and AI technologies.
Applied Scientist II - AMZ5545
US, CA, Sunnyvale
MULTIPLE POSITIONS AVAILABLEEntity: Amazon.com Services LLC, an Amazon.com CompanyTitle: Applied Scientist IILocation: Sunnyvale, CAPosition Responsibilities:Use expertise in physical sciences as well as theoretical, numerical or empirical techniques to create scalable models representing response of physical systems or devices. Develop innovative analyses and tests to study viability of new materials, designs and processes. Work closely with engineering teams to drive validation, optimization and implementation of hardware designs and software algorithmic solutions to improve product and reduce customer risks. Establish scalable, efficient, automated processes to handle large-scale design and data analysis. Conduct research on user behavior, materials and analysis techniques. Track general business activity including device health in field and provide clear, compelling reports to management on a regular basis. Develop and implement guidelines to continually optimize design processes. Perform structural tests on materials and components used in consumer electronics systems to drive design and materials recommendations in consumer electronics systems. Implement experimental engineering techniques to validate and address structural design risks in consumer electronic systems.Amazon.com is an Equal Opportunity-Affirmative Action Employer - Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation. #0000
Applied Scientist, CloudTune, CloudTune Forecasting
US, TX, Austin
Job summaryAmazon's CloudTune group is looking for an experienced Applied Scientist to join our forecasting team. The team develops large-scale scale models to inform team-level budget allocations and procurement/allocation of compute capacity for Amazon businesses during new product launches, high velocity events and non-peak periods. This role will be contributing to a managed service that uses historical data and business signals to deliver time series forecasting for specialized use cases. The service combines a variety of distinct forecasting models, including neural networks, to produce highly accurate forecasts.As a scientist in the CloudTune team you'll also partner with technology and business teams to build new services that surprise and delight our customers. We develop sophisticated algorithms that involve learning from large amounts of past data. These forecasts are used to determine the level of investment in capital expenditures, promotional activity, engineering efficiency projects and determining financial performance.You will work on mathematical problems with a high level of ambiguity. You will analyze and process large amounts of data, develop new algorithms and improve existing approaches based on statistical models, machine learning algorithms and big data solutions to automatically scale Amazon’s compute infrastructure, optimizing the balance between availability risk and cost efficiency for all of Amazon businesses.We are looking for top scientists capable of using ML and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems. We're an agile team with significant impact. If you can think big and want to be a part of a fast moving team breaking new ground at Amazon.com, and you meet the qualifications, we would like to speak with you!Key job responsibilities· Process and analyze large data sets, mining additional data sources as needed· Analyze compute scaling metrics to identify business drivers that influence infrastructure expenditures· Build mathematical models to represent demand forecasting at various levels.· Prototype these models by using high-level modeling languages such as R or in software languages such as Python. A software team will be working with you to transform prototypes into production.· Create, enhance, and maintain technical documentation, and present to other scientists and business leaders.
Applied Scientist, Alexa Invocations team
US, CA, Sunnyvale
Job summaryAlexa is the groundbreaking voice service that powers Echo and other devices designed around your voice. Our team is creating the science and technology behind Alexa. We’re working hard, having fun, and making history. Come join our team! You will have an enormous opportunity to impact the customer experience, design, architecture, and implementation of a cutting edge product used every day by people you know.We’re looking for a passionate, talented, and inventive scientist to help build industry-leading conversational technologies that customers love. As an Applied Scientist, you will work with talented peers to develop novel machine learning algorithms and modeling techniques to advance the state of the art in speech and audio processing. Your work will directly impact our customers in the form of novel 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. You will mentor junior scientists, create and drive new initiatives.
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