robin arm with gripper.jpg
Robin, one of the most complex stationary robot arm systems Amazon has ever built, brings many core technologies to new levels and acts as a glimpse into the possibilities of combining vision, manipulation and machine learning.
Credit: F4D Studio

Amazon’s robot arms break ground in safety and technology

While these systems look like other robot arms, they embed advanced technologies that will shape Amazon's robot fleet for years to come.

Inside an Amazon facility, employees and robots work together to ready products for customers. On one side of the building, yellow tote bins bearing partially completed orders ride down a conveyor. At the end of the conveyor, a robot arm called a palletizer/depalletizer stacks them on a pallet as if playing a three-dimensional game of Tetris.

When an employee sees a pallet is complete, they approach the immobilized robot, slip a motorized hand truck under the pallet, and route it to shipping. From there, a truck takes it to another facility. There, a different palletizer/depalletizer places the totes on conveyors that guide them to employees who complete the order. On another side of the facility, a jumbled pile of soft mailers and boxes roll down a conveyor belt. Robin, a smaller robot arm, grabs one and rotates the parcel to scan the label. Once it knows the ZIP code, it sorts the package onto a robotic carrier for processing. If it sees any rips, tears, or illegible addresses, Robin transfers the package, via either conveyor or mobile robot, for employees to handle.

Robots are common in Amazon facilities, where more than 200,000 mobile units aid the flow of goods from inventory to shipping. Stationary robotic arms, however, are relatively new. Yet they play an important role in the company's drive to safely deliver the right goods to the right customers at the right time.

“A real gain for the overall system”

Although Robin and the palletizer/depalletizer look like other robot arms, they embed advanced technologies that will shape Amazon's robot fleet for years to come.

Conventional robots often do a single job — welding a section of a vehicle frame or screwing a part into place — whereas for robotic arms like Robin, few tasks are ever precisely the same.

Robin, for example, must calculate how to identify, move, and sort parcels that may rest atop one another as they are presented via a conveyor. The palletizer/depalletizer must calculate how to stack a stable pallet on the fly. To do it, they use both cutting-edge AI algorithms that make decisions in fractions of a second and high-tech cameras, sensors, and grippers.

Watch Robin deftly handle packages

While the robotic arms aid in the operation of Amazon facilities, they also improve the employee experience by eliminating repetitive lifting, stacking, and turning. In turn, this allows employees to focus on the kinds of assignments that leave robots struggling.

"Eliminating tasks that are repetitious and dull lets employees focus on things that are really important," Tye Brady, chief technologist for Amazon Robotics, observed. "If we can elevate our employees to do higher-level tasks that require common sense — something computers are not good at — that's a real gain for the overall system."

This intricate collaboration of people and machines has helped Amazon to deliver goods with fewer mistakes, Brady said. It has also fueled growth and jobs. Since 2012, when Amazon first began deploying robots within its fulfillment centers, the company’s facility workforce added hundreds of thousands of new employees, even before its massive COVID-19 hiring efforts in 2020.

"Amazon could not have achieved what it has done without robotics, nor could we have done it without the amazing skills of our employees," Brady said. "They go hand in hand. If you try to separate one from another, you are going down a failed path."

@F4DStudio_AmazonScience_RoboticArm-00947 (1).jpg
Robin must calculate how to identify, move, and sort parcels that may rest atop one another as they are presented via a conveyor.
Credit: F4D Studio

But before Amazon could blaze that path, it first had to make sure its new robots were safe.

Safety first (and always)

"We don't just build a robot and then say, 'Hey, safety people, I want you to get involved now,'" Brady said. "Instead, safety engineers are there every step of the way, from design and deployment to maintenance and operation. They're at the table talking with us about how we can make it a better experience for our employees."

Clay Flannigan, senior manager, advanced robotics, and the technical lead in the Robin program noted that when robot and safety team members assess the flow of work in Amazon facilities, they insist on solutions that will not compromise safety.

"We work hard to identify any potential hazards," Flannigan said. "That could be anything from limiting any risk for contact between people and the robot, tripping on a floor cable, or a sharp edge on a barrier. Ideally, we can eliminate them with multiple engineering mitigations.”

This is especially important when working with large industrial robots: the best approach is to ensure appropriate access controls are implemented. This starts with fences. To enter the robot area, employees gain access through a secured gate, which positively disables the robot. There is only one gate, which provides strict control over who can access the robot.

Watch a hardware engineer operate Robin

In addition to the gate, a light curtain protects the opposite side of the robot. If an employee breaks the plane of the curtain, the robot automatically stops. These safety features ensure that the robot can do its job while permitting safe access to the area for employees to perform maintenance.

Amazon also brings in independent experts to assess the industrial designs. "They ask a lot of good questions,” Brady said. "'Can I approach the station from a weird angle? Could I open the door without the sensors tripping? Can I break the light curtain somehow without the system noticing?'"

Engineers then build and test physical prototypes, monitoring them to see if workers could potentially interact with them in ways that might cause usability issues. They also track metrics about how the machines behave within facilities, which permits continued improvement of their performance.

Robin as an evolutionary step

Robin, one of the most complex stationary robot arm systems Amazon has ever built, brings many core technologies to new levels and acts as a glimpse into the possibilities of combining vision, package manipulation and machine learning, said Will Harris, principal product manager of the Robin program.

Those technologies can be seen when Robin goes to work. As soft mailers and boxes move down the conveyor line, Robin must break the jumble down into individual items. This is called image segmentation. People do it automatically, but for a long time, robots only saw a solid blob of pixels.

Robin robotic arms sort and move packages
Robots are common in Amazon facilities, where more than 200,000 mobile units aid the flow of goods from inventory to shipping. Stationary robotic arms, however, are relatively new. Yet they play an important role in company's drive to safely deliver the right goods to the right customers at the right time.
Credit: F4D Studio

Over many years, AI algorithms have learned to break up that blob into individual objects by recognizing things like color or significant features, such as the edge of a mailer. More recently, neural networks have improved enough to do this well. The neural networks are aided in this task by training to segment mailers in a virtual world.

Engineers start by creating a virtual model of the arm and an ever-changing jumble of packages moving down a virtual conveyor belt. In the model, the robot’s AI attempts to segment and grab the items, iterating on each success and failure, and slowly learning to recognize mailers, even when they are obscured or in odd positions. After each session, the model reshuffles the packages randomly and the training begins again.  

After thousands of virtual model-training iterations, Amazon tests a prototype at its facilities. "We put together a 1,000-package test set that mirrors the profile of mail we expect to see in the building and run it through multiple times," Harris said. "This gives us good predictive data about how it will perform in the field. Then we test it operationally at select sites, before rolling it out to the entire installed base."

Pallet Tetris

The palletizer/depalletizer is a larger and more powerful machine than Robin, and a marvel of technology in its own right. It also plays a critical role in Amazon’s fulfillment operations.

See a palletizer/de-palletizer in action — skip ahead to the 24 second mark

At Amazon, Brady explains, product always flows toward employees. When someone places an order, a mobile robot brings the goods to an employee. If the order is complete, it is sent to the conveyer to be packed out and shipped to customers’ doors. If not — because no single facility contains the millions of products Amazon sells — the order goes to another facility to be completed.

The best way to ship totes is to put them on a pallet. The palletizer/depalletizer’s job is to stack totes on the pallet when they leave the facility and take them off the pallet and place them on conveyors when they come in. Brady likens the process to playing Tetris.

The palletizing starts with yellow totes parked at the end of a conveyor. All are the same size and oriented in the same direction, and they have been scanned to make sure the correct products are in the tote and the tote itself is in good shape.

New Amazon program offers free career training in robotics

The Mechatronics and Robotics Apprenticeship program gives employees the opportunity to apply for an apprenticeship that will train them on the skills and technical knowledge needed to fulfill technical maintenance roles. Find out more.

The palletizer/depalletizer has a two-dimensional camera at its tip, which it uses to rapidly position its arm over the tote. At the end is a custom gripper with four moveable L-shaped elements on each side that slip under the tote's raised upper perimeter. Once it has secured the tote, the robot lifts, pivots, and places the tote on a pallet, using a three-dimensional camera. As it does this, the AI system calculates where to place the tote so that the pallet is evenly balanced and stable. The robot builds six pallets at a time, three on each side, and it moves quickly.

"As the robot builds the pallets, people monitor several robots to make sure everything is going well," Brady said. "When the pallets are complete, they move them out of the cage with a motorized hand truck. You have this rhythm, this dynamic, between our employees and the palletizer/depalletizer, and this keeps all our operations running smoothly."

A dynamic partnership

The increasing reliance on systems like Robin and the palletizer/depalletizer also serves to highlight the symbiotic nature of the partnership between people and robots.

"There's a misconception about the sort of things we can achieve with robotic systems of this type," Flannigan answered. "There's a whole lot of tasks that we just can't solve today with robots alone and they tend to be ones that require higher levels of cognition or dexterity."

In fact, Brady noted, Amazon's facilities work best when people and machines work together: “There's a lot of productivity that involves people and machines working together, and I'm not just talking about one machine. I'm talking about an array of machines in our facilities and how we design those machines to interface with people. We use those machines to help people identify inventory, move inventory, store inventory, and source inventory. That's crucial to our job. Our employees are the backbone of our fulfillment process and we want to empower them with better machines.”

The result, says Brady, is an intricate dance, with people and machines each doing what they do best. It is one of the key reasons why Amazon continues to operate so smoothly and add tens of thousands of new jobs every year. And it’s why Amazon can deliver the right goods to the right customers at the right time.

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

Research areas

Related content

US, CA, Santa Clara
Job summaryAmazon is looking for a passionate, talented, and inventive Applied Scientist with a strong machine learning background to help build industry-leading language technology.Our mission is to provide a delightful experience to Amazon’s customers by pushing the envelope in Natural Language Processing (NLP), Natural Language Understanding (NLU), Dialog management, conversational AI and Machine Learning (ML).As part of our AI team in Amazon AWS, you will work alongside internationally recognized experts to develop novel algorithms and modeling techniques to advance the state-of-the-art in human language technology. Your work will directly impact millions of our customers in the form of products and services, as well as contributing to the wider research community. You will gain hands on experience with Amazon’s heterogeneous text and structured data sources, and large-scale computing resources to accelerate advances in language understanding.We are hiring primarily in Conversational AI / Dialog System Development areas: NLP, NLU, Dialog Management, NLG.This role can be based in NYC, Seattle or Palo Alto.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 fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.Mentorship & Career GrowthOur team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
US, NY, New York
Job summaryAmazon is looking for a passionate, talented, and inventive Applied Scientist with a strong machine learning background to help build industry-leading language technology.Our mission is to provide a delightful experience to Amazon’s customers by pushing the envelope in Natural Language Processing (NLP), Natural Language Understanding (NLU), Dialog management, conversational AI and Machine Learning (ML).As part of our AI team in Amazon AWS, you will work alongside internationally recognized experts to develop novel algorithms and modeling techniques to advance the state-of-the-art in human language technology. Your work will directly impact millions of our customers in the form of products and services, as well as contributing to the wider research community. You will gain hands on experience with Amazon’s heterogeneous text and structured data sources, and large-scale computing resources to accelerate advances in language understanding.We are hiring primarily in Conversational AI / Dialog System Development areas: NLP, NLU, Dialog Management, NLG.This role can be based in NYC, Seattle or Palo Alto.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 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, CA, Santa Clara
Job summaryAWS AI/ML is looking for world class scientists and engineers to join its AI Research and Education group working on building automated ML solutions for planetary-scale sustainability and geospatial applications. Our team's mission is to develop ready-to-use and automated solutions that solve important sustainability and geospatial problems. We live in a time wherein geospatial data, such as climate, agricultural crop yield, weather, landcover, etc., has become ubiquitous. Cloud computing has made it easy to gather and process the data that describes the earth system and are generated by satellites, mobile devices, and IoT devices. Our vision is to bring the best ML/AI algorithms to solve practical environmental and sustainability-related R&D problems at scale. Building these solutions require a solid foundation in machine learning infrastructure and deep learning technologies. The team specializes in developing popular open source software libraries like AutoGluon, GluonCV, GluonNLP, DGL, Apache/MXNet (incubating). Our strategy is to bring the best of ML based automation to the geospatial and sustainability area.We are seeking an experienced Applied Scientist for the team. This is a role that combines science knowledge (around machine learning, computer vision, earth science), technical strength, and product focus. It will be your job to develop ML system and solutions and work closely with the engineering team to ship them to our customers. You will interact closely with our customers and with the academic and research communities. You will be at the heart of a growing and exciting focus area for AWS and work with other acclaimed engineers and world famous scientists. You are also expected to work closely with other applied scientists and demonstrate Amazon Leadership Principles (https://www.amazon.jobs/en/principles). Strong technical skills and experience with machine learning and computer vision are required. Experience working with earth science, mapping, and geospatial data is a plus. Our customers are extremely technical and the solutions we build for them are strongly coupled to technical feasibility.About the teamInclusive Team CultureAt 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 scientist and enable them to take on more complex tasks in the future.Interested in this role? Reach out to the recruiting team with questions or apply directly via amazon.jobs.
US, CA, Santa Clara
Job summaryAWS AI/ML is looking for world class scientists and engineers to join its AI Research and Education group working on building automated ML solutions for planetary-scale sustainability and geospatial applications. Our team's mission is to develop ready-to-use and automated solutions that solve important sustainability and geospatial problems. We live in a time wherein geospatial data, such as climate, agricultural crop yield, weather, landcover, etc., has become ubiquitous. Cloud computing has made it easy to gather and process the data that describes the earth system and are generated by satellites, mobile devices, and IoT devices. Our vision is to bring the best ML/AI algorithms to solve practical environmental and sustainability-related R&D problems at scale. Building these solutions require a solid foundation in machine learning infrastructure and deep learning technologies. The team specializes in developing popular open source software libraries like AutoGluon, GluonCV, GluonNLP, DGL, Apache/MXNet (incubating). Our strategy is to bring the best of ML based automation to the geospatial and sustainability area.We are seeking an experienced Applied Scientist for the team. This is a role that combines science knowledge (around machine learning, computer vision, earth science), technical strength, and product focus. It will be your job to develop ML system and solutions and work closely with the engineering team to ship them to our customers. You will interact closely with our customers and with the academic and research communities. You will be at the heart of a growing and exciting focus area for AWS and work with other acclaimed engineers and world famous scientists. You are also expected to work closely with other applied scientists and demonstrate Amazon Leadership Principles (https://www.amazon.jobs/en/principles). Strong technical skills and experience with machine learning and computer vision are required. Experience working with earth science, mapping, and geospatial data is a plus. Our customers are extremely technical and the solutions we build for them are strongly coupled to technical feasibility.About the teamInclusive Team CultureAt 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 scientist and enable them to take on more complex tasks in the future.Interested in this role? Reach out to the recruiting team with questions or apply directly via amazon.jobs.
US, WA, Seattle
Job summaryHow can we create a rich, data-driven shopping experience on Amazon? How do we build data models that helps us innovate different ways to enhance customer experience? How do we combine the world's greatest online shopping dataset with Amazon's computing power to create models that deeply understand our customers? Recommendations at Amazon is a way to help customers discover products. Our team's stated mission is to "grow each customer’s relationship with Amazon by leveraging our deep understanding of them to provide relevant and timely product, program, and content recommendations". We strive to better understand how customers shop on Amazon (and elsewhere) and build recommendations models to streamline customers' shopping experience by showing the right products at the right time. Understanding the complexities of customers' shopping needs and helping them explore the depth and breadth of Amazon's catalog is a challenge we take on every day. Using Amazon’s large-scale computing resources you will ask research questions about customer behavior, build models to generate recommendations, and run these models directly on the retail website. You will participate in the Amazon ML community and mentor Applied Scientists and software development engineers with a strong interest in and knowledge of ML. Your work will directly benefit customers and the retail business and you will measure the impact using scientific tools. We are looking for passionate, hard-working, and talented Applied scientist who have experience building mission critical, high volume applications that customers love. You will have an enormous opportunity to make a large impact on the design, architecture, and implementation of cutting edge products used every day, by people you know.Key job responsibilitiesScaling state of the art techniques to Amazon-scaleWorking independently and collaborating with SDEs to deploy models to productionDeveloping long-term roadmaps for the team's scientific agendaDesigning experiments to measure business impact of the team's effortsMentoring scientists in the departmentContributing back to the machine learning science community
US, NY, New York
Job summaryAmazon Web Services is looking for world class scientists to join the Security Analytics and AI Research team within AWS Security Services. This group is entrusted with researching and developing core data mining and machine learning algorithms for various AWS security services like GuardDuty (https://aws.amazon.com/guardduty/) and Macie (https://aws.amazon.com/macie/). In this group, you will invent and implement innovative solutions for never-before-solved problems. If you have passion for security and experience with large scale machine learning problems, this will be an exciting opportunity.The AWS Security Services team builds technologies that help customers strengthen their security posture and better meet security requirements in the AWS Cloud. The team interacts with security researchers to codify our own learnings and best practices and make them available for customers. We are building massively scalable and globally distributed security systems to power next generation services.Inclusive Team Culture Here 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 Balance Our 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 Growth Our 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 and enable them to take on more complex tasks in the future.A day in the lifeAbout the hiring groupJob responsibilities* Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both quantitative and business judgment.* Collaborate with software engineering teams to integrate successful experiments into large scale, highly complex production services.* Report results in a scientifically rigorous way.* Interact with security engineers, product managers and related domain experts to dive deep into the types of challenges that we need innovative solutions for.
US, NY, New York
Job summaryAmazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day!The Advertising Modeling, Optimization and Data Science team enhances Advertising teams’ decision-making by providing an exhaustive suite of analytics and automation products, and by extracting meaning from Amazon Advertising’s global operations. We own and operate a large-scale AWS-based data infrastructure that acts as a pivot to Worldwide operations, enabling critical downstream applications in ad management, design, billing, as well as customer feedback, software infrastructure, and more. The team consists of Business Intelligence Engineers, Data Scientists, and Data Engineers, who work together to improve our Advertisers' and Shoppers' experience with Amazon Advertising by accompanying and supporting the analytical needs of our partner teams.As a Senior Data Scientist on this team you will:Lead Data Science solutions from beginning to end.Deliver with independence on challenging large-scale problems with complexity and ambiguity.Write code (Python, R, Scala, SQL, etc.) to obtain, manipulate, and analyze data.Build Machine Learning and statistical models to solve specific business problems.Retrieve, synthesize, and present critical data in a format that is immediately useful to answering specific questions or improving system performance.Analyze historical data to identify trends and support optimal decision making.Apply statistical and machine learning knowledge to specific business problems and data.Formalize assumptions about how our systems should work, create statistical definitions of outliers, and develop methods to systematically identify outliers. Work out why such examples are outliers and define if any actions needed.Given anecdotes about anomalies or generate automatic scripts to define anomalies, deep dive to explain why they happen, and identify fixes.Build decision-making models and propose effective solutions for the business problems you define.Conduct written and verbal presentations to share insights to audiences of varying levels of technical sophistication.Why you will love this opportunity: Amazon has invested heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate.Impact and Career Growth: You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding.Team video ~ https://youtu.be/zD_6Lzw8raE
US, CA, Palo Alto
Job summaryAmazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. Our products are strategically important to our businesses driving long term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day!The Machine Learning Optimization (MLO) team develops algorithms and systems that improve the performance and delivery of Amazon’s Display Advertising campaigns and automates campaign management using machine learning techniques. The team develops and deploys machine learning solutions that drive ad selection, bidding, user response prediction, and automated campaign management. Customers are advertisers and publishers who do business with Amazon.We own the system for batch training of user response prediction models, while the ad serving engineering team owns the real-time model scoring component. This teams owns the system for automated management of advertising campaigns, which can dynamically adjust parameters such as budget, bid prices, and targeting to optimize for campaign performance.As an Applied Scientist on this team, you will: Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity.Perform hands-on analysis and modeling of enormous data sets to develop insights that increase traffic monetization and merchandise sales, without compromising the shopper experience.Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models.Run A/B experiments, gather data, and perform statistical analysis.Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.Research new and innovative machine learning approaches.Recruit Applied Scientists to the team and provide mentorship.Why you will love this opportunity: Amazon is investing heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate.Impact and Career Growth: You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding.Team video https://youtu.be/zD_6Lzw8raE Advanced degree in Computer Science, Mathematics, Statistics, Economics, or related quantitative field.Published research work in academic conferences or industry circles.Experience in building large-scale machine-learning models and infra for online recommendation, ads ranking, personalization, or search, etc.Effective verbal and written communication skills with non-technical and technical audiences.Experience working with large real-world data sets and building scalable models from big data.Thinks strategically, but stays on top of tactical execution.Exhibits excellent business judgment; balances business, product, and technology very well.Experience in computational advertising.Key job responsibilitiesYou will work on the next generation of our real-time pricing systems. These systems are optimizing the price of every individual opportunity on behalf of Amazon Advertising advertisers. A day in the lifeConduct offline analysis of data to guide design decisions with the product teamConduct A/B test setup and analyze results to guide rollout, go to market or development priority decisionsSuggest and implement models to sophisticate the advertising products we offer to our customersAbout the teamThe Ranking team is responsible for real-time pricing decisions on the Amazon RTB (Real-Time Bidding) system
US, WA, Seattle
Job summaryAre you excited about joining a team of scientists building lasting solutions for Amazon customers from the ground up? Our team is using machine learning, and statistical methods to take Amazon’s unique customer obsession culture to another level by designing solutions that change customers behavior when it comes to product search, discovery, and purchase. In order to achieve this, we need scientists who will help us build advanced algorithms that deliver first-rate user experience during customers’ shopping journeys on Amazon, and subsequently make Amazon their default starting point for future shopping journeys. These algorithms will utilize advances in Natural Language Understanding, and Computer Vision to source and understand contents that customers trust, and furnish customers with these contents in a way that is precisely tailored to their individual needs at any stage of their shopping journey. Key job responsibilitiesWe are looking for an Applied Scientist to join our rapidly growing Seattle team. As an Applied Scientist, you are able to use a range of science methodologies in NLP/CV to solve challenging business problems when the solution is unclear. For example, you may lead the development of reinforcement learning models such as MAB to rank content to be shown to customers based on their queries. 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 SageMaker, S3, and EC2 with a variety of skillsets in shallow and deep learning ML models, particularly in NLP and CV. You will bring knowledge in many of these domains along with your own specialties and skilset.Major responsibilities:Use statistical and machine learning techniques to create scalable and lasting systems.Analyze and understand large amounts of Amazon’s historical business data for Recommender/Matching algorithmsDesign, develop and evaluate highly innovative models for NLP.Work closely with teams of scientists and software engineers to drive real-time model implementations and new feature creations.Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and implementation.Research and implement novel machine learning and statistical approaches, including NLP and Computer VisionA day in the lifeIn this role, you’ll be utilizing your NLP or CV skills, and creative and critical problem-solving skills to drive new projects from ideation to implementation. Your science expertise will be leveraged to research and deliver often novel solutions to existing problems, explore emerging problems spaces, and create or organize knowledge around them. About the teamOur team puts a high value on your work and personal life happiness. 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 you. 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 establish your own harmony between your work and personal life.
US, WA, Seattle
Job summaryAre you excited about joining a team of scientists building lasting solutions for Amazon customers from the ground up? Our team is using machine learning, and statistical methods to take Amazon’s unique customer obsession culture to another level by designing solutions that change customers behavior when it comes to product search, discovery, and purchase. In order to achieve this, we need scientists who will help us build advanced algorithms that deliver first-rate user experience during customers’ shopping journeys on Amazon. These algorithms will utilize advances in Natural Language Understanding, and Computer Vision to source and understand content that customers trust, and furnish customers with the content in a way that meets their needs at any stage of their shopping journey. Key job responsibilitiesUse statistical and machine learning techniques to create scalable and lasting systems.Analyze and understand large amounts of Amazon’s historical business data for Recommender/Matching algorithmsDesign, develop and evaluate highly innovative - Work closely with teams of scientists and software engineers to drive real-time model implementationsEstablish scalable, efficient, automated processes for large scale data analyses, model development, model validation and implementation.Research and implement novel machine learning and statistical approaches, including NLP and Computer VisionA day in the lifeIn this role, you’ll be utilizing your NLP or CV skills, and creative and critical problem-solving skills to drive new projects from ideation to implementation. Your science expertise will be leveraged to research and deliver often novel solutions to existing problems, explore emerging problems spaces, and create or organize knowledge around them. About the teamOur 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.We put a high value on your work and personal life happiness. 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 you. 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 establish your own harmony between your work and personal life.