Bill Smart, far right, Oregon State University professor of robotics, and an Amazon Scholar, demonstrates an experiment simulating how robots might be used during Ebola outbreaks.
In this 2019 photo, Bill Smart, far right, an Oregon State University professor of robotics, demonstrates how robots might be used during Ebola outbreaks. Today, he is an Amazon Scholar and is teaming up with Amazon to study how robots and people interact over prolonged periods of time.
Credit: Oregon State University

Amazon Scholar has his eyes on the future of robot movement

Learn how Bill Smart wants to simplify the ways that robots and people work together — and why waiting on a date one night changed his career path.

Mobile robots are popping up all around us. They check inventory while rolling down supermarket aisles, clean airport floors at night, supply and sanitize hospital rooms, and check petrochemical pipes for corrosion. Amazon uses more than 200,000 robots in its operations.  

People and robots are increasingly learning to live and work together. Bill Smart wants to simplify the interactions between them. Smart, a professor of robotics and associate director of the Collaborative Robotics and Intelligent Systems Institute at Oregon State University, is teaming with Amazon to study how robots and people interact over prolonged periods of time.

Working with robots at Amazon, it’s possible to think on a larger scale for months and years at a time. This lets you ask questions that you just can’t as an academic.
Bill Smart

In academia, a typical study might include 30 people. Researchers bring the participants into a room, one at a time, where they interact with a robot in a variety of ways. This may yield some insights, Smart said, but these studies take place in isolation — just one person and one robot the person has never seen before. This scenario does not really duplicate the emerging robot-people world.

“As an academic, I can run a few robots for a few days, and do what essentially amounts to proof-of-concept studies,” he said. “Working with robots at Amazon, it’s possible to think on a larger scale for months and years at a time. This lets you ask questions that you just can’t as an academic.”

And that scale, over time, is extraordinarily valuable to Smart. "I want to know what these contacts look like over a month or over a year," Smart said. "Your interaction in that first hour is going to be a lot different than your interaction at the end of a month or a year. I'm interested in how people work with robots, and also what they do when they are not working with them, but sharing the same space."

The desire to run more robust experiments led Smart to Amazon, where he is an Amazon Scholar. He plans to study how people and robots interact with one another over the long term. Smart said his familiarity with Amazon Robotics, and the people who work there, also drove his interest.

“The thing that really got me to think about joining the Scholars’ program is the people that I knew who were already at Amazon,” he said. “I knew Tye Brady [Amazon Robotics’ chief technology officer] from MARS, and I’ve known Sidd [Siddhartha Srinivasa, director of Amazon Robotics] for years. The fact that Sidd, in particular, had moved to Amazon carried a lot of weight, and gave it a lot of credibility in the AI and robotics space.”

An Amazon robot on the fulfillment center floor
One of the advantages of conducting robotics research at Amazon is scale. "You can gather statistics on things you just could not learn in a smaller setting," Bill Smart said.

Smart is not just focused on people-robot interfaces. He also works on machine learning and public policy. He has a lot on his plate for someone whose career in robotics began while waiting for a date.

From math to robots

Smart grew up in Scotland, just south of the Highlands, in "a tiny little town of 7,000 people in the middle of nowhere." His father was a factory worker, his mother did piecework, and growing up, he spent his holidays picking fruit and working in a cannery.

If he had been a little older, he likely would never have furthered his education. Instead, educational reforms at the time enabled him to become the first of his family to go to university.

Smart started in mathematics at University of Dundee, but had a realization. "Math was very abstracted from reality," he recalled. "I could push the symbols around the page, but I didn't see how it affected the world. So I switched to computer science, which used some math, but I got to apply it to problems, which was really cool."

Smart thought his career path was set. Then, one night, he went to pick up the woman he was dating. She was not ready, so he started reading a magazine article about the robots that pioneering roboticist Rodney Brooks was building at MIT. That was all it took. “I looked at one and thought, ‘Wow. That's really cool,’” he said. He was hooked.

Nearby Edinburgh University offered one of the world's first master's degrees in robotics. That eventually led to a PhD in computer science at Brown University and a thesis on machine learning in robots. He set up his own lab at Washington University in St. Louis and later took a sabbatical year at Willow Garage, a California-based robotics incubator that was developing the open source Robot Operating System (ROS) at the time. In 2012, he decamped for Oregon State University.

Working together

Smart's research involves expanding on ways for people and robots to work together over the long term. One particular area he wants to expand on is the ways in which a robot signals what it is about to do and where it intends to go next.

canvas robot.jpg
“Currently, the robots we're working with have a set of indicator lights, similar to a car, that show the intent of the robot,” Bill Smart observed. “The ultimate goal is to have the robots be ‘invisible in use’, so that the employees don’t have to think about them any more than they think about the actions of their human colleagues.”

“Currently, the robots we're working with have a set of indicator lights, similar to a car, that show the intent of the robot,” Smart observed. “The underlying safety systems on the robot will cause it to slow or stop. But the ultimate goal is to have the robots be ‘invisible in use’, so that the employees don’t have to think about them any more than they think about the actions of their human colleagues.”

One of the advantages of conducting this research at Amazon is scale. This is important for two reasons. First, it enables Smart to gather data on variations in robot behavior, like testing which side of an aisle a robot should use or how fast it should go.

"You can gather statistics on things you just could not learn in a smaller setting," he said. It also provides a more realistic framework for measuring those changes. Working at Amazon means Smart has access to the kind of scale that makes it easier to extrapolate useful results.

Large numbers also matter for machine learning. Smart's work involves turning sensor information into actionable intelligence. He views machine learning as a tool, and one that is highly effective. "That's really important in a production environment,” Smart said

Evolving robot policy

Smart, who was selected as an AAAS Leshner Leadership Institute Public Engagement Fellow in artificial intelligence, also has an interest in policy. While policy concerns stretch back over his career, his journey really began in 2011. That is when a colleague at Washington University, law professor Neil Richards, whose scholarship involves technology, suggested that Smart attend We Robot, then a new conference on the legal and policy aspects of robots and AI. Smart wound up giving the conference's first-ever presentation.

The conference was an eye-opener for Smart. It was begun by lawyers who were involved with internet law, which was written largely after the internet had already exploded into the world. The conference hoped to work through the legal implications of a world coinhabited by robots and people before those robots appeared on the scene. Smart was one of the few technologists there.

"Most of the scholarship came from the legal and policy side, and it was not strongly anchored to what the technology could actually do," he said. "They were talking about things that might become problems in decades and not things that were a problem today. This is because they misunderstood where the technology sits today."

There's still a lot of work to do, and the hard bit is where robots intersect with human activities. In five years, I think we'll still be trying to figure that out.
Bill Smart

After interacting with roboticists for years, Smart found the conference exposed him to a different set of perspectives. He wanted to contribute by helping to explain robotics without the hype. The more people understand about robots, he said, the better decisions they will make.

Smart said he is also concerned about over-reliance on the idea that robots or AI can act as a panacea, rather than providing tools to address problems. Yet he remains excited. After 20 years in the field, he is finally seeing robots in the world. Even Oregon State has begun using delivery robots, doing useful jobs that make people's lives better.

"We're still in the early days, equivalent to where computers were before Apple and IBM," he said. "There's still a lot of work to do, and the hard bit is where robots intersect with human activities. In five years, I think we'll still be trying to figure that out."

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Job summaryMachine learning (ML) has been strategic to Amazon from the early years. We are pioneers in areas such as recommendation engines, product search, eCommerce fraud detection, and large-scale optimization of fulfillment center operations.The Amazon ML Solutions Lab team helps AWS customers accelerate the use of machine learning to solve business and operational challenges and promote innovation in their organization. We are looking for a passionate, talented, and inventive Applied Scientist with a strong machine learning background to help develop solutions by pushing the envelope in Time Series, Automatic Speech Recognition (ASR), Natural Language Understanding (NLU), Machine Learning (ML) and Computer Vision (CV).As a ML Solutions Lab Applied Scientist, you are proficient in designing and developing advanced ML models to solve diverse challenges and opportunities. You will be working with terabytes of text, images, and other types of data and develop novel models to solve real-world problems. You'll design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. You will apply classical ML algorithms and cutting-edge deep learning (DL) and reinforcement learning approaches to areas such as drug discovery, customer segmentation, fraud prevention, capacity planning, predictive maintenance, pricing optimization, call center analytics, player pose estimation, event detection, and virtual assistant among others.The primary responsibilities of this role are to:· Design, develop, and evaluate innovative ML/DL models to solve diverse challenges and opportunities across industries· Interact with customer directly to understand their business problems, and help them with defining and implementing scalable ML/DL solutions to solve them· Work closely with account teams, research scientist teams, and product engineering teams to drive model implementations and new algorithmsThis position requires travel of up to 25%.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.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, TX, Austin
Job summaryMachine learning (ML) has been strategic to Amazon from the early years. We are pioneers in areas such as recommendation engines, product search, eCommerce fraud detection, and large-scale optimization of fulfillment center operations.The Amazon ML Solutions Lab team helps AWS customers accelerate the use of machine learning to solve business and operational challenges and promote innovation in their organization. We are looking for a passionate, talented, and inventive Applied Scientist with a strong machine learning background to help develop solutions by pushing the envelope in Time Series, Automatic Speech Recognition (ASR), Natural Language Understanding (NLU), Machine Learning (ML) and Computer Vision (CV).As a ML Solutions Lab Applied Scientist, you are proficient in designing and developing advanced ML models to solve diverse challenges and opportunities. You will be working with terabytes of text, images, and other types of data and develop novel models to solve real-world problems. You'll design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. You will apply classical ML algorithms and cutting-edge deep learning (DL) and reinforcement learning approaches to areas such as drug discovery, customer segmentation, fraud prevention, capacity planning, predictive maintenance, pricing optimization, call center analytics, player pose estimation, event detection, and virtual assistant among others.The primary responsibilities of this role are to:· Design, develop, and evaluate innovative ML/DL models to solve diverse challenges and opportunities across industries· Interact with customer directly to understand their business problems, and help them with defining and implementing scalable ML/DL solutions to solve them· Work closely with account teams, research scientist teams, and product engineering teams to drive model implementations and new algorithmsThis position requires travel of up to 25%.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.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, MI, Detroit
Job summaryMachine learning (ML) has been strategic to Amazon from the early years. We are pioneers in areas such as recommendation engines, product search, eCommerce fraud detection, and large-scale optimization of fulfillment center operations.The Amazon ML Solutions Lab team helps AWS customers accelerate the use of machine learning to solve business and operational challenges and promote innovation in their organization. We are looking for a passionate, talented, and inventive Applied Scientist with a strong machine learning background to help develop solutions by pushing the envelope in Time Series, Automatic Speech Recognition (ASR), Natural Language Understanding (NLU), Machine Learning (ML) and Computer Vision (CV).As a ML Solutions Lab Applied Scientist, you are proficient in designing and developing advanced ML models to solve diverse challenges and opportunities. You will be working with terabytes of text, images, and other types of data and develop novel models to solve real-world problems. You'll design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. You will apply classical ML algorithms and cutting-edge deep learning (DL) and reinforcement learning approaches to areas such as drug discovery, customer segmentation, fraud prevention, capacity planning, predictive maintenance, pricing optimization, call center analytics, player pose estimation, event detection, and virtual assistant among others.The primary responsibilities of this role are to:· Design, develop, and evaluate innovative ML/DL models to solve diverse challenges and opportunities across industries· Interact with customer directly to understand their business problems, and help them with defining and implementing scalable ML/DL solutions to solve them· Work closely with account teams, research scientist teams, and product engineering teams to drive model implementations and new algorithmsThis position requires travel of up to 25%.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.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, 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
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.
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.
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.
LU, Luxembourg
Job summaryWould you like to pioneer new technologies in machine learning while leveraging Amazon's heterogenous data sources and large-scale computing resources?As a data scientist, your work will help Amazon raise the bar on customer obsession by providing our Sellers with the best customized experiences.We are looking for a passionate, talented, and inventive Scientist with a strong machine learning background to join us to build industry-leading technology.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 in sourcing processes. Excellent business and communication skills are a must to develop and define key business questions and to build data sets 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.
US, WA, Seattle
Come join the AWS Marketplace Team in our mission to change the way enterprise software is bought and sold! AWS Marketplace enables software sellers to reach all AWS customers, and it enables software buyers to easily discover, purchase and consume software. Our goals include enriching the platform to support more diverse selection, improving buyer and seller experience, and supporting co-sell opportunities between AWS and our partners. Our vision is to make AWS Marketplace the one stop shop for buying and selling software - we're building the app store for AWS.A day in the lifeIn this role, you’ll be utilizing your creative and critical problem solving skills to drive new projects from ideation to implementation. You will improve and innovate on existing high impact analytical projects. Your outputs will focus on our team’s critical goals and help influence decision makers.About the hiring groupAbout 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 16 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. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded professional and enable them to take on more complex tasks in the future.Job responsibilitiesWe are looking for a Data Scientist to join our rapidly growing Seattle team. As a Data Scientist, you are able to use a range of data science methodologies to solve challenging business problems when the solution is unclear. You have a combination of business acumen, broad knowledge of statistics, deep understanding of ML algorithms, and an analytical mindset. You thrive in a collaborative environment, and are passionate about learning. Our team utilizes a variety of AWS tools such as Redshift, Sagemaker, Lambda, S3, and EC2 with a variety of skillsets in Tabular ML, NLP, Forecasting, Probabilistic ML and Causal ML. You will bring knowledge in many of these domains along with your own specialties and skillsets.
DE, BE, Berlin
Machine Learning (ML) has been strategic to Amazon from the early years. We are pioneers in areas such as recommendation engines, product search, eCommerce fraud detection, and large-scale optimization of fulfillment center operations.Machine Learning University’s (MLU) mission is to teach people to apply ML to business and operational challenges. In service of this goal, we are growing our presence outside the US, and are looking to hire in EMEA region. We believe strongly that a practical knowledge of ML can be taught broadly, and is a key skill for many builders to learn. Come join Amazon’s Machine Learning University and help spread knowledge of ML!We have built a team of passionate science educators with the demonstrated ability to explain ML to an audience of technical professionals, enhance curriculum, and collaborate with scientists across the company. You will teach practitioners how to train, tune, and deploy ML models to solve challenges in customer segmentation, fraud prevention, capacity planning, predictive maintenance, pricing optimization, call center analtyics, and event detection among others. Practical experience with machine learning is key to ensure content is up-to-date, practical and engaging. This is a full-time role where you will constantly be challenged to learn and be curious about ML.As a Sr. MLU Applied Scientist on our team, you would have the following responsibilities:· Teach customers directly to understand their business problems, and help them with defining and implementing scalable ML/DL solutions to solve them· Develop open-source curriculum designed to provide a practical knowledge of ML. This includes lectures, videos, demos, and coding notebook assignments (find an article about our largest release here: https://www.amazon.science/latest-news/machine-learning-course-free-online-from-amazon-machine-learning-university)· Collaborate with scientists across Amazon to continuously understand and integrate advances in ML into the curriculum· Help drive high-level curriculum decisions to ensure alignment with students’ needs and the state-of-the-art domains of advancement in ML· Consult with customers on model development and deployment best practices by using computer science fundamentals· Engage in the interview process and otherwise develop, grow, and mentor junior scientistsThis team is comprised of Data Scientists, Applied Scientists and Instructional Designers to create first-in-class courses and learning assets in practical ML. The role may require travel up to 40% of the time (pending safety protocols and travel restrictions). We are currently recruiting for talented individuals for this role in the following cities: London, Cambridge, Tuebingen, Dublin, Amsterdam, Berlin, Paris, or Gdansk. Let’s bring ML to everyone and demystify and democratize technology together!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.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 fulfilment. 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. We Hire and Develop the best so you can expect support in advancing your career ambitions and projects which will help you grow and develop your skills.
DE, BE, Berlin
Machine Learning (ML) has been strategic to Amazon from the early years. We are pioneers in areas such as recommendation engines, product search, eCommerce fraud detection, and large-scale optimization of fulfillment center operations.Machine Learning University’s (MLU) mission is to teach people to apply ML to business and operational challenges. In service of this goal, we are growing our presence outside the US, and are looking to hire in EMEA region. We believe strongly that a practical knowledge of ML can be taught broadly, and is a key skill for many builders to learn. Come join Amazon’s MLU and help spread knowledge of ML!We have built a team of passionate science educators with the demonstrated ability to explain ML to an audience of technical professionals, enhance curriculum, and collaborate with scientists across the company. You will teach practitioners how to train, tune, and deploy ML models to solve challenges in customer segmentation, fraud prevention, capacity planning, predictive maintenance, pricing optimization, call center analtyics, and event detection among others. Practical experience with machine learning is key to ensure content is up-to-date, practical and engaging. This is a full-time role where you will constantly be challenged to learn and be curious about ML.As a MLU Applied Scientist on our team, you would have the following responsibilities:· Teach customers directly to understand their business problems, and help them with defining and implementing scalable ML/DL solutions to solve them· Develop open-source curriculum designed to provide a practical knowledge of ML. This includes lectures, videos, demos, and coding notebook assignments (find an article about our largest release here: https://www.amazon.science/latest-news/machine-learning-course-free-online-from-amazon-machine-learning-university)· Collaborate with scientists across Amazon to continuously understand and integrate advances in ML into the curriculum· Help drive high-level curriculum decisions to ensure alignment with students’ needs and the state-of-the-art domains of advancement in ML· Consult with customers on model development and deployment best practices by using computer science fundamentalsThis team is comprised of Data Scientists, Applied Scientists and Instructional Designers to create first-in-class courses and learning assets in practical ML. The role may require travel up to 40% of the time (pending safety protocols and travel restrictions). We are currently recruiting for talented individuals for this role in the following cities: London, Cambridge, Tuebingen, Dublin, Amsterdam, Berlin, Paris, or Gdansk. Let’s bring ML to everyone and demystify and democratize technology together!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.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 fulfilment. 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. We Hire and Develop the best so you can expect support in advancing your career ambitions and projects which will help you grow and develop your skills.
US, WA, Seattle
Job summaryThe AWS Cryptography Group is looking for an Applied Scientist with knowledge of cryptographic computing technologies such as privacy preserving machine learning, fully and partially homomorphic encryption, secure multiparty computation, private information retrieval, and related technologies. You will use this knowledge to conceptualize how this technology can be integrated into internal infrastructure and public AWS services, develop prototypes, and provide customers with world-class security. The ideal candidate will have a strong understanding of cryptography, the ability to prototype solutions, and a passion to realize these technologies in AWS products and services. We encourage research and publication of results that apply to our customers most complex initiatives.We are seeking a candidate who is innovative, looking for new ideas everywhere. They should think big, and have bold ideas for new ways to serve customers.About UsAWS 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.A Culture of InclusionHere 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 BalanceWe put 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. We provide both the opportunity to be mentored by seasoned leaders and to mentor junior researchers. We care about your career growth and strive to give you challenging responsibilities that will help you develop into a better-rounded applied scientist and give you the opportunity to advance your career to the next level.Learn more about Amazon on our Day 1 Blog: https://blog.aboutamazon.com/
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.