The science behind visual ID

A new opt-in feature for Echo Show and Astro provides more-personalized content and experiences for customers who choose to enroll.

With every feature and device we build, we challenge ourselves to think about how we can create an immersive, personalized, and proactive experience for our customers. Often, our devices are used by multiple people in our homes, and yet there are times when you want a more personalized experience. That was the inspiration for visual ID. 

On the all-new Echo Show 15, Echo Show 8, and Echo Show 10, you and other members of your household will soon be able to enroll in visual ID, so that at a glance you can see personalized content such as calendars and reminders, recently played music, and notes for you. 

And with Astro, a new kind of household robot, enrolling in visual ID enables Astro to do things like find you to deliver something, such as a reminder or an item in Astro’s cargo bin.

Creating your visual ID

Visual ID is opt-in, so you must first enroll in the feature, much as you can enroll in voice ID (formerly Alexa voice profile) today. During enrollment, you will use the camera on your supported Echo Show device or Astro to take a series of headshots at different angles. For visual ID to accurately recognize you, we require five different angles of your face. 

During the enrollment process, the device runs algorithms to ensure that each of the images is of high enough quality. For example, if the room is too dark, you will see on-screen instructions to adjust the lighting and try again. You will also see on-screen notifications as an image of each pose is successfully captured. 

The images are used to create numeric representations of your facial characteristics. Called vectors (one for each angle of your face), these numeric representations are just that: a string of numbers. The images are also used to revise the vectors in the event of periodic updates to the visual ID model — meaning customers are not required to re-enroll in visual ID every time there is a model update. These images and vectors are securely stored on-device, not in Amazon’s cloud.

Up to 10 members of a household per account can enroll on each compatible Echo Show or Astro to enjoy more-personalized experiences for themselves. Customers with more than one visual-ID-compatible device will need to enroll on each device individually.

enrollment image_resized.png
A screenshot of the enrollment process, during which the device’s camera takes a series of headshots at different angles.

Identifying an enrolled individual

Once you’ve enrolled in visual ID, your device attempts to match people who walk into the camera’s field of view with the visual IDs of enrolled household members. There are two steps to this process, facial detection and facial recognition, and both are done through local processing using machine learning models called convolutional neural networks. 

To recognize a person, the device first uses a convolutional neural network to detect when a face appears in the camera’s field of view. If a person whom the device does not recognize as enrolled in visual ID walks into the camera’s field of view, the device will determine that there are no matches to the stored vectors. The device does not retain images or vectors from unenrolled individuals after processing. All of this happens in fractions of a second and is done securely on-device.

When your supported Echo Show device recognizes you, your avatar and a personalized greeting will appear in the upper right of the screen.

Echo Show 15_Visual ID.jpg
An example of what Echo Show 15 might show on its screen once an enrolled individual is recognized.

What shows on Astro’s screen will depend on what Astro is doing. For example, if you’ve enrolled in visual ID, and Astro is trying to find you, Astro will display text on its screen — “Looking for [Bob]”, followed by “Found [Bob]” — to acknowledge that it’s recognized you.

Looking for Bob.png
Astro will display text on its screen — “Looking for [Bob]”, followed by “Found [Bob]” — to acknowledge that it’s recognized you.

Enhancing fairness 

We set a high bar for equity when it came to designing visual ID. To clear that bar, our scientists and engineers built and refined our visual ID models using millions of images — collected in studies with participants’ consent — explicitly representing a diversity of gender, ethnicity, skin tone, age, ability, and other factors. We then set performance targets to ensure the visual ID feature performed well across groups.

In addition to consulting with several Amazon Scholars who specialize in computer vision, we also consulted with an external expert in algorithmic bias, Ayanna Howard, dean of the Ohio State University College of Engineering, to review the steps we took to enhance the fairness of the feature. We’ve implemented feedback from our Scholars and Dr. Howard, and we will solicit and listen to customer feedback and make improvements to ensure the feature continues to improve on behalf of our customers.

Privacy by design

As with all of our products and services, privacy was foundational to how we built and designed visual ID. As mentioned above, the visual IDs of enrolled household members are securely stored on-device, and both Astro and Echo Show devices use local processing to recognize enrolled customers. You can delete your visual ID from individual devices on which you’ve enrolled through on-device settings and, for Echo Show, through the Alexa app. This will delete the stored enrollment images and associated vectors from your device. We will also automatically delete your visual ID from individual devices if your face is not recognized by that device for 18 months.

It’s still day one for visual ID, Echo Show, and Astro. We look forward to hearing how our customers use visual ID to personalize their experiences with our devices.

Research areas

Related content

US, NY, New York
Amazon is looking for an Applied Scientist to help build the next generation of sourcing and vendor experience systems. The Optimal Sourcing Systems (OSS) owns the optimization of inventory sourcing and the orchestration of inbound flows from vendors worldwide. We source inventory from thousands of vendors for millions of products globally while orchestrating the inbound flow for billions of units. Our goals are to increase reliable access to supply, improve supply chain-driven vendor experience, and reduce end-to-end supply chain costs, all in service of maximizing Long-Term Free Cash Flow (LTFCF) for Amazon. As an Applied Scientist, you will work with software engineers, product managers, and business teams to understand the business problems and requirements, distill that understanding to crisply define the problem, and design and develop innovative solutions to address them. Our team is highly cross-functional and employs a wide array of scientific tools and techniques to solve key challenges, including optimization, causal inference, and machine learning/deep learning. Some critical research areas in our space include modeling buying decisions under high uncertainty, vendors' behavior and incentives, supply risk and enhancing visibility and reliability of inbound signals. Key job responsibilities You will be a science tech leader for the team. As a Applied Scientist you will: - Set the scientific strategic vision for the team. You - - lead the decomposition of problems and development of roadmaps to execute on it. - Set an example for other scientists with exemplary scientific analyses; maintainable, extensible, and well-tested code; and simple, intuitive, and effective solutions. - Influence team business and engineering strategies. - Exercise sound judgment to prioritize between short-term vs. long-term and business vs. technology needs. - Communicate clearly and effectively with stakeholders to drive alignment and build consensus on key initiatives. - Foster collaborations between scientists across Amazon researching similar or related problems. - Actively engage in the development of others, both within and outside the team. - Engage with the broader scientific community through presentations, publications, and patents.
US, CA, San Francisco
If you are interested in this position, please apply on Twitch's Career site https://www.twitch.tv/jobs/en/ About Us: Twitch is the world’s biggest live streaming service, with global communities built around gaming, entertainment, music, sports, cooking, and more. It is where thousands of communities come together for whatever, every day. We’re about community, inside and out. You’ll find coworkers who are eager to team up, collaborate, and smash (or elegantly solve) problems together. We’re on a quest to empower live communities, so if this sounds good to you, see what we’re up to on LinkedIn and X, and discover the projects we’re solving on our Blog. Be sure to explore our Interviewing Guide to learn how to ace our interview process. About the Role Data is central to Twitch's decision-making process, and data scientists are a critical component to evangelize data-driven decision making in all of our operations. As a data scientist at Twitch, you will be on the ground floor with your team, shaping the way product performance is measured, defining what questions should be asked, and scaling analytics methods and tools to support our growing business, leading the way for high quality, high velocity decisions for your team. For this role, we're looking for an experienced product data scientist who will help develop the strategy and evaluate/improve product initiatives within our Creator product team. You will be responsible to define and track KPIs, design experiments, evaluate A/B tests, implement data instrumentation, and inform on investment. Our ideal candidate is a "full-stack" data powerhouse who uses data to drive decision making to make the best products for our creators and their communities. Your input will be core to decision making across all major product strategies and initiatives that our team builds. You will work closely with product managers, technical program managers, engineering, data scientists, and organization leadership within and outside of the Creator organization. You Will - Inform product strategies by defining and updating core metrics for each initiative - Establish analytical framework for your team: ad-hoc analysis, automated dashboards, and self-service reporting tools to surface key data to stakeholders - Evaluate and forecast impact of product features on creators, viewers, and the entire Twitch ecosystem - Design A/B experiments to drive product direction with iterative innovation and measurement - Drive the team's analysis roadmap and prioritize the most valuable projects - Tackle complex and ambiguous analytic projects, resolve ambiguity and accurately identify the trade-offs between speed and quality and apply or route work as necessary - Dive deep into the data to understand how creator and viewer behaviors change with the evolution of our product - Act as our team's thought leader on best practices and move towards long-term vision of sustainable and thriving data processes - Own data collection and product instrumentation implementation and quality assurance - Work hand-in-hand with business, product, engineering, and design to proactively influence and inform teammates' decisions throughout the product life cycle - Distill ambiguous product or business questions, find clever ways to answer them, and to quantify the uncertainty Perks - Medical, Dental, Vision & Disability Insurance - 401(k) - Maternity & Parental Leave - Flexible PTO - Amazon Employee Discount About the team Twitch is all about community, and our Community Team is a core pillar of what makes Twitch, Twitch. Teams within Community are responsible for a myriad of product areas impacting the creator, viewer, and moderator journeys on our platform. As a member of our team, you'll build solutions that improve g the experience of millions of daily active users on our platform and create tools that keep both streamers and viewers engaged and connected on our platform.
AU, NSW, Sydney
AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector. The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success. AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services. The Generative Artificial Intelligence (AI) Innovation Center team at AWS provides opportunities to innovate in a fast-paced organization that contributes to game-changing projects and technologies leveraging cutting-edge generative AI algorithms. As an Applied Scientist, you'll partner with technology and business teams to build solutions that surprise and delight our customers. We’re looking for Applied Scientists capable of using generative AI and other ML techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems. Key job responsibilities - Collaborate with scientists and engineers to research, design and develop cutting-edge generative AI algorithms to address real-world challenges - Work across customer engagement to understand what adoption patterns for generative AI are working and rapidly share them across teams and leadership - Interact with customers directly to understand the business problem, help and aid them in implementation of generative AI solutions, deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and paths for generative AI - Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder - Provide customer and market feedback to Product and Engineering teams to help define product direction. A day in the life 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 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. About the team Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. What if I don’t meet all the requirements? That’s okay! We hire people who have a passion for learning and are curious. You will be supported in your career development here at AWS. You will have plenty of opportunities to build your technical, leadership, business and consulting skills. Your onboarding will set you up for success, including a combination of formal and informal training. You’ll also have a chance to gain AWS certifications and access mentorship programs. You will learn from and collaborate with some of the brightest technical minds in the industry today.
US, CA, San Francisco
The AWS Center for Quantum Computing is a multi-disciplinary team of scientists, engineers, and technicians, all working to innovate in quantum computing for the benefit of our customers. We are looking to hire a Research Scientist to design and model novel superconducting quantum devices, including qubits, readout and control schemes, and advanced quantum processors. Candidates with a track record of original scientific contributions and/or software development experience will be preferred. We are looking for candidates with strong engineering principles and resourcefulness. Organization and communication skills are essential. About the team AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services. Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
US, WA, Seattle
Amazon Prime is looking for an ambitious Economist to help create econometric insights for world-wide Prime. Prime is Amazon's premiere membership program, with over 200M members world-wide. This role is at the center of many major company decisions that impact Amazon's customers. These decisions span a variety of industries, each reflecting the diversity of Prime benefits. These range from fast-free e-commerce shipping, digital content (e.g., exclusive streaming video, music, gaming, photos), and grocery offerings. Prime Science creates insights that power these decisions. As an economist in this role, you will create statistical tools that embed causal interpretations. You will utilize massive data, state-of-the-art scientific computing, econometrics (causal, counterfactual/structural, time-series forecasting, experimentation), and machine-learning, to do so. Some of the science you create will be publishable in internal or external scientific journals and conferences. You will work closely with a team of economists, applied scientists, data professionals (business analysts, business intelligence engineers), product managers, and software engineers. You will create insights from descriptive statistics, as well as from novel statistical and econometric models. You will create internal-to-Amazon-facing automated scientific data products to power company decisions. You will write strategic documents explaining how senior company leaders should utilize these insights to create sustainable value for customers. These leaders will often include the senior-most leaders at Amazon. The team is unique in its exposure to company-wide strategies as well as senior leadership. It operates at the cutting-edge of utilizing data, econometrics, artificial intelligence, and machine-learning to form business strategies. A successful candidate will have demonstrated a capacity for building, estimating, and defending statistical models (e.g., causal, counterfactual, time-series, machine-learning) using software such as R, Python, or STATA. They will have a willingness to learn and apply a broad set of statistical and computational techniques to supplement deep-training in one area of econometrics. For example, many applications on the team use structural econometrics, machine-learning, and time-series forecasting. They rely on building scalable production software, which involves a broad set of world-class software-building skills often learned on-the-job. As a consequence, already-obtained knowledge of SQL, machine learning, and large-scale scientific computing using distributed computing infrastructures such as Spark-Scala or PySpark would be a plus. Additionally, this candidate will show a track-record of delivering projects well and on-time, preferably in collaboration with other team members (e.g. co-authors). Candidates must have very strong writing and emotional intelligence skills (for collaborative teamwork, often with colleagues in different functional roles), a growth mindset, and a capacity for dealing with a high-level of ambiguity. Endowed with these traits and on-the-job-growth, the role will provide the opportunity to have a large strategic, world-wide impact on the customer experiences of Prime members.
US, WA, Seattle
The CATALST NLP Services team within the Selling Partner Services (SPS) Core Services organization is responsible for simplifying multi-lingual experiences for our customers. We build and leverage various AI services to eliminate language barriers at scale through Machine Translation for Amazon Customers and Sellers WW across 30+ programs within SPS and customers outside of SPS. We leverage state-of-the-art NLP solutions including Large Language Models, Machine Translation, Language Detection, and OCR to provide a full suite of content analysis capabilities. Our customers include Selling Partners, Buyers, Amazon Associates, Amazon Investigators, and various Science teams. In this role, you will be a key owner within our cross-disciplinary team that includes Product Managers, Software Engineers, and Applied Scientists and execute on our 3 Year Plan. You will pioneer new technologies in NLP, machine translation, and machine learning. You will have ownership of the end-to-end development of solutions to complex problems from design to implementation and you will play an integral role in strategic decision-making. You will also work closely with other stakeholders such as engineers, operations teams and product owners to build ML pipelines, platforms and solutions that solve business problems. Key job responsibilities * Participate in the design, development, evaluation, deployment and updating of automated and scalable machine learning models, with a focus on machine translation * Develop and/or apply statistics, NLP and machine learning experiments and methodologies to different applications * Work closely with Scientists and Software Engineers on experimentations, evaluation and implementation * Work closely with business partners to understand the goals and develop solutions to achieve such goals
AU, VIC, Melbourne
Are you excited about leveraging state-of-the-art Computer Vision algorithms and large datasets to solve real-world problems? Join Amazon as an Applied Scientist Intern and be at the forefront of AI innovation! As an Applied Scientist Intern, you'll work in a fast-paced, cross-disciplinary team of pioneering researchers. You'll tackle complex problems, developing solutions that either build on existing academic and industrial research or stem from your own innovative thinking. Your work may even find its way into customer-facing products, making a real-world impact. Key job responsibilities - Develop novel solutions and build prototypes - Work on complex problems in Computer Vision and Machine Learning - Contribute to research that could significantly impact Amazon's operations - Collaborate with a diverse team of experts in a fast-paced environment - Collaborate with scientists on writing and submitting papers to Tier-1 conferences (e.g., CVPR, ICCV, NeurIPS, ICML) - Present your research findings to both technical and non-technical audiences Key Opportunities: - Collaborate with leading machine learning researchers - Access cutting-edge tools and hardware (large GPU clusters) - Address challenges at an unparalleled scale - Become a disruptor, innovator, and problem solver in the field of computer vision - Potentially deliver solutions to production in customer-facing applications - Opportunities to become an FTE after the internship Join us in shaping the future of AI at Amazon. Apply now and turn your research into real-world solutions!
US, WA, Seattle
AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we’re looking for talented people who want to help. You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion. In 2019, Amazon co-founded The Climate Pledge and made a commitment to achieve net-zero carbon by 2040 —10 years ahead of the Paris Agreement. We invited others to join us and there are now more than 300 businesses and organizations across 51 industries and 29 countries that have signed the Pledge, which means we are collectively coming at the climate crisis from nearly every sector and nearly every angle. As part of our efforts to decarbonize our business, we became the world’s largest corporate purchaser of renewable energy in 2020, and last year, we reached 85% renewable energy across our business, and are on a path to power our operations with 100% renewable energy by 2025. We recently announced that AWS will be water positive by 2030, returning more water to communities than it uses in its direct operations. The company also announced its 2021 global water use efficiency (WUE) metric of 0.25 liters of water per kilowatt-hour, demonstrating AWS’s leadership in water efficiency among cloud providers. To learn more about AWS’s water+ commitment visit: Water Stewardship. Come join the team that is building the tools and innovative technology to manage our growing portfolio of renewable energy investments, including solar, on-shore and off-shore wind farms. Key job responsibilities As an data scientist, you will employ machine learning and analytics to create scalable solutions for problems in sustainable energy space. You will dissect large historical business data sets to enhance and streamline essential processes. You will partner with data and software teams to create models for predictive insights and establish automated methods for large data analysis. A day in the life To learn more, you can visit: amazon sustainability in the cloud About the team Why AWS Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship and Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
US, CA, Santa Clara
Are you passionate about applying automated reasoning and program analysis to real world problems? Do you want to create products that help customers? If so, then we have an exciting opportunity for you. We’re looking for an Applied Scientist to help strengthen our customers' security with automation for managed controls. AWS Identity provides the bedrock for secure and continuous access to all AWS services. By quickly connecting millions of users, across the world we empower organizations and enterprises to accelerate their cloud and digital transformation. In this role, you will interact with internal teams and external customers to understand their requirements. You will apply your knowledge to propose innovative 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. Key job responsibilities * Interact with various teams to develop an understanding of their security and safety requirements. * Apply the acquired knowledge to build tools and algorithms, find problems, or show the absence of security/safety problems. * Implement these capabilities through the use of Automated Reasoning and various concepts from programming languages. * 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. About the team About AWS Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. This team is part of AWS Utility Computing: Utility Computing (UC) AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services.
US, NY, New York
Amazon is investing heavily in building a world class advertising business and developing a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses for driving long-term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities. We are seeking a technical leader for our Supply Science team. This team is within the Sponsored Product team, and works on complex engineering, optimization, econometric, and user-experience problems in order to deliver relevant product ads on Amazon search and detail pages world-wide. The team operates with the dual objective of enhancing the experience of Amazon shoppers and enabling the monetization of our online and mobile page properties. Our work spans ML and Data science across predictive modeling, reinforcement learning (Bandits), adaptive experimentation, causal inference, data engineering. Key job responsibilities Search Supply and Experiences, within Sponsored Products, is seeking an Applied Scientist to join a fast growing team with the mandate of creating new ads experience that elevates the shopping experience for our hundreds of millions customers worldwide. We are looking for a top analytical mind capable of understanding our complex ecosystem of advertisers participating in a pay-per-click model– and leveraging this knowledge to help turn the flywheel of the business. As an Applied Scientist on this team you will: --Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production. --Run A/B experiments, gather data, and perform statistical analysis. --Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving. --Work closely with software engineers to assist in productionizing your ML models. --Research new machine learning approaches. A day in the life The successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail, and with an ability to work in a fast-paced, high-energy and ever-changing environment. The drive and capability to shape the direction is a must. About the team We are a customer-obsessed team of engineers, technologists, product leaders, and scientists. We are focused on continuous exploration of contexts and creatives where advertising delivers value to customers and advertisers. We specifically work on new ads experiences globally with the goal of helping shoppers make the most informed purchase decision. We obsess about our customers and we are continuously innovating on their behalf to enrich their shopping experience on Amazon