David Schuster and colleagues' Nature 2004 paper (left) "Strong coupling of a single photon to a superconducting qubit using circuit quantum electrodynamics" helped spawn a new field, circuit quantum electrodynamics. Schuster and colleagues' American Physical Society 2007 paper (right) "Charge-insensitive qubit design derived from the Cooper pair box", introduced a new type of superconducting quantum circuit.
David Schuster and colleagues' Nature, 2004, paper (left) "Strong coupling of a single photon to a superconducting qubit using circuit quantum electrodynamics" helped spawn a new field, circuit quantum electrodynamics. Schuster and colleagues' American Physical Society, 2007, paper (right) "Charge-insensitive qubit design derived from the Cooper pair box", introduced a new type of superconducting quantum circuit.

David Schuster’s quest to make practical quantum computers a reality

With quantum computers poised to take a big step forward, we speak to an Amazon Scholar who has spent two decades driving the technology to realize its enormous potential.

To become a foundational player in the creation of a potentially world-changing technology requires the happy conjunction of talent and timing. Both can be found in physicist David Schuster, who is pioneering the technology underpinning quantum computers.

Amazon Scholar David Schuster is seen inside his lab
Amazon Scholar David Schuster joined the AWS Center for Quantum Computing in October 2020.

Schuster became an Amazon Scholar in October 2020, joining the newly established AWS Center for Quantum Computing. Passionate about computers and physics, it was during Schuster’s undergrad studies at Brown University in the early 2000s that he became aware of the nascent field of quantum computing.

“As soon as I heard about it, I was taken with the idea that I could be involved in building a completely new type of computer,” says Schuster. He saw this chance for what it was, a colossal stroke of right-place-right-time good fortune. “The opportunity to make an impact at such a fundamental level was very exciting.”

To appreciate why quantum computing has such potential, compare it to regular, or “classical”, computers. A classical computer uses digital bits to perform computations, with each bit representing either 0 or 1 at any given time. In simplistic terms, increasing the number of bits available to interact with each other increases the computational power of a computer in an additive, linear fashion. A top-end laptop will boast 32 gigabytes of RAM, which is 256,000,000,000 bits.

Related content
New phase estimation technique reduces qubit count, while learning framework enables characterization of noisy quantum systems.

A quantum computer, by contrast, uses quantum bits (qubits) to perform calculations. Each qubit can be in a simultaneously 0 and 1 at any given time. As a result of this “quantum superposition” – which only occurs at the tiniest scales – increasing the qubits results in an exponential explosion in computational power. It is estimated that a fully functional quantum computer with as little as 100 qubits could outsmart today’s most powerful supercomputers for appropriately chosen problems.

Because of the tiny scale and extreme conditions at which qubits exist, it is very difficult to create and control them, but they can nevertheless be made by harnessing a variety of quantum particles, including charged atoms, the directional spin of electrons, and photons.

But it was an experiment published just as Schuster entered grad school at Yale University that demonstrated that a superconducting circuit could be turned into a qubit, though the quantum effect lasted for less than a nanosecond. “In those early days there was a small number of people working in the field,” he recalls, “and a fundamental question was whether you could even make a circuit quantum. They were able to see it as a direct observation!”

Our approach was unique in that we leveraged powerful ideas from atomic physics and mapped them onto circuits, to build circuits that behaved like atoms
David Schuster

Duly inspired, during his PhD research in physics at Yale, Schuster and his colleagues had bold ideas about how to improve the quantum circuit and create new ways of measuring its quantum state. “Our approach was unique in that we leveraged powerful ideas from atomic physics and mapped them onto circuits, to build circuits that behaved like atoms.”

The circuit-based qubit they created contained cavities and could trap and interact, or couple, with a single microwave photons to create a two-level quantum system, with the levels representing 0s and 1s. Published in Nature in 2004, the landmark paper helped to create a new field — circuit quantum electrodynamics.

Related content
New method enables entanglement between vacancy centers tuned to different wavelengths of light.

Using such circuits as the basis of a qubit has many benefits, says Schuster. One of those is that the cavities help to protect the fragile quantum state against external interference while also allowing the qubits to interact strongly with each other, which is essential for computation.

In 2007, Schuster and his colleagues published another landmark paper, this time in Physical Review A. In it, they introduced a new type of superconducting quantum circuit, coining the term “transmon”. More cunning physics had resulted in a drastic reduction in sensitivity to external noise and an increase in the qubit-photon coupling, while maintaining the ability to control the qubits. The relatively simple transmon has become an industry standard, forming the basis of efforts at Amazon and other computing giants. Some consider the transmon the “transistor” of superconducting quantum computers.

In 2010, Schuster moved to the University of Chicago, where he set up his lab, which explores and develops a range of quantum technologies. This year, for example, the Schuster Lab team published research revealing what they dubbed a “quantum flute”, a piece of hardware able to control multiple microwave photons simultaneously. The team called the work an important step towards efficient quantum RAM and quantum processors.

A tour of David Schuster's quantum computing lab

This year, Schuster is moving to the applied physics department at Stanford University, with the rest of his lab joining him there in 2023. For the rest of 2022, however, most of Schuster’s time will be spent working at the Center for Quantum Computing.

One of the key challenges of quantum systems is that quantum states are incredibly fragile. Consider a regular computer, in which a single bit might consist of a billion electrons sloshing back and forth, with their location representing a 0 or a 1.

“If some electrons get lost, that’s OK. And redundancy is built in. But in the case of a qubit, there’s just one photon and no redundancy,” says Schuster. “And beside the possibility of losing the photon altogether, the slightest noise from the environment can disturb the quantum superposition, creating errors.” This risk of noise is one of the reasons quantum computing typically requires superconducting materials and temperatures very near absolute zero to operate at all.

And the fact that quantum states can only be maintained for a very brief time compounds the error problem.

Related content
The head of Amazon Web Services’ quantum communication program on the Nobel winners’ influence on her field.

“I like to joke that my goal is to make qubits last for the blink of an eye,” says Schuster. Right now, state-of-the-art devices with multiple qubits might boast decoherence times of around 100 microseconds (0.0001 seconds), he says.

Decoherence means the loss of the fragile quantum state. This loss of information results in small computation errors that can quickly multiply, potentially making any output useless. And the more qubits in play, the more quickly errors can accumulate. With leading quantum processors currently containing up to a few hundred qubits (of a variety of natures), we are in what Caltech theoretical physicist and Amazon Scholar John Preskill termed the “noisy intermediate-scale quantum” (NISQ) era.

“By the time we get about 100 qubits interacting with each other, the errors become so great you can't really do much, so there's no point making a 1000-qubit system yet,” says Schuster.

Decoherence is a tractable problem, though, and it is being relentlessly addressed by researchers including Schuster and members of his lab. Fortunately, however, decoherence does not need to be totally overcome before quantum computers can successfully scale up.

Already, the accuracy of the qubits in Schuster’s quantum systems is well over 99%. In fact, as a scientific field the accuracy is getting so high that a threshold is approaching, says Schuster, beyond which sophisticated error-correcting algorithms will be able to counteract the remaining problems caused by the fragility of the qubits.

Related content
How an Amazon quantum computing scientist won the first-ever quantum chess tournament.

“Once we get our error rate low enough, scaling up will actually result in even fewer errors,” he says. “Amazon's effort is focused on getting to this goal of error correction, because then we can truly make a large-scale quantum computer.”

Schuster is two decades into his quantum journey. Is it getting any easier?

“When I started it all felt impossible, but we just tried it anyway,” he says. “Now, the problems no longer necessarily seem impossible, but they are still extremely difficult.”

So why join Amazon now?

Amazon’s efforts are experimental and bold — they are trying different approaches. I think Amazon understands the true magnitude of the challenge and the ultimate value of quantum computing.
David Schuster

“The quality of the team was very appealing,” he says, “and Amazon’s efforts are experimental and bold — they are trying different approaches. I think Amazon understands the true magnitude of the challenge and the ultimate value of quantum computing to their customers through Amazon Web Services, so they are patient.”

It is well known that the arrival of quantum computing will have enormous implications for online security and encryption, because the highest levels of protection currently being employed to protect online data will not stand up to the sheer power of quantum computers. Quantum computing will bring with it uncrackable encryption.

Security implications aside, what other useful applications might we expect? There are entire classes of scientific problems that are intractable to classical computers that should succumb to quantum efforts, says Schuster. He is personally excited about the potential to better understand materials in which quantum mechanics plays an important role.

“Many special materials involve complex quantum interactions that we don't understand and, right now, about 30% of supercomputer capacity goes to solving quantum mechanical problems,” he says.

It is inefficient to solve quantum mechanical problems on a classical computer, he adds. “Very small quantum systems that involve 20 particles or states, you could maybe solve on a laptop. But if it involves 50, even the world's biggest supercomputer can't really do very much with it.”

Such research carried out on quantum computers could have big impacts on the discovery of new materials for renewable energy, computing, chemistry, medicines, and more.

There are also some surprising possibilities for Schuster’s quantum circuits.

“I never would have expected this, but I ended up getting involved in searching for dark matter,” he says. There is a type of proposed dark matter — low mass bosons — that would occasionally interact with ordinary matter, resulting in the production of a single microwave photon. And as luck would have it, Schuster’s qubit circuits are able to trap and measure these photons.

“We can use our qubits to detect these newly created photons,” he explains, “making the search for this type of dark matter about 1000 times faster!”

Research areas

Related content

US, MA, N.reading
Amazon Industrial Robotics is seeking exceptional talent to help develop the next generation of advanced robotics systems that will transform automation at Amazon's scale. We're building revolutionary robotic systems that combine cutting-edge AI, sophisticated control systems, and advanced mechanical design to create adaptable automation solutions capable of working safely alongside humans in dynamic environments. This is a unique opportunity to shape the future of robotics and automation at an unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic manipulation, locomotion, and human-robot interaction. As an Applied Scientist in Sensing, you will develop innovative and complex sensing systems for our emerging robotic solutions and improve existing on-robot sensing to optimize performance and enhance customer experience. The ideal candidate has demonstrated experience designing and troubleshooting custom sensor systems from the ground up. They enjoy analytical problem solving and possess practical knowledge of robotic design, fabrication, assembly, and rapid prototyping. They thrive in an interdisciplinary environment and have led the development of complex sensing systems. Key job responsibilities - Design and adapt holistic on-robot sensing solutions for ambiguous problems with fluid requirements - Mentor and develop junior scientists and engineers - Work with an interdisciplinary team to execute product designs from concept to production including specification, design, prototyping, validation and testing - Have responsibility for the designs and performance of a sensing system design - Work with the Operations, Manufacturing, Supply Chain and Quality organizations as well as vendors to ensure a fast development and delivery of the sensing concepts to the team - Develop overall safety concept of the sensing platform - Exhibit role model behaviors of applied science best practices, thorough and predictive analysis and cradle to grave ownership
IN, KA, Bengaluru
You will be working with a unique and gifted team developing exciting products for consumers. The team is a multidisciplinary group of engineers and scientists engaged in a fast paced mission to deliver new products. The team faces a challenging task of balancing cost, schedule, and performance requirements. You should be comfortable collaborating in a fast-paced and often uncertain environment, and contributing to innovative solutions, while demonstrating leadership, technical competence, and meticulousness. Your deliverables will include development of thermal solutions, concept design, feature development, product architecture and system validation through to manufacturing release. You will support creative developments through application of analysis and testing of complex electronic assemblies using advanced simulation and experimentation tools and techniques. Key job responsibilities In this role, you will: - Own thermal design for consumer electronics products at the system level, proposing thermal architecture and aligning with functional leads - Perform CFD simulations using tools such as Star-CCM+ or FloEFD to assess thermal feasibility, identify risks, and propose mitigation options - Generate data processing, statistical analysis, and test automation scripts to improve data consistency, insight quality, and team efficiency - Plan and execute thermal validation activities for devices and SoC packages, including test setup definition, data review, and issue tracking - Work closely with cross-functional and cross-geo teams to support product decisions, generate thermal specifications, and align on thermal requirements - Prepare clear summaries and reports on thermal results, risks, and observations for review by cross-functional leads About the team Amazon Lab126 is an inventive research and development company that designs and engineers high-profile consumer electronics. Lab126 began in 2004 as a subsidiary of Amazon.com, Inc., originally creating the best-selling Kindle family of products. Since then, we have produced innovative devices like Fire tablets, Fire TV and Amazon Echo. What will you help us create?
US, MA, North Reading
At Amazon Robotics, we design advanced robotic systems capable of intelligent perception, learning, and action alongside humans, all on a large scale. Our goal is to develop robots that increase productivity and efficiency at the Amazon fulfillment centers while ensuring the safety of workers. We are seeking an Applied Scientist to develop innovative, scalable solutions in feedback control and state estimation for robotic systems, with a focus on contact-rich manipulation tasks. In this role, you will formulate physics-based models of robotic systems, perform analytical and numerical studies, and design control and estimation algorithms that integrate fundamental principles with data-driven techniques. You will collaborate with a world-class team of experts in perception, machine learning, motion planning, and feedback controls to innovate and develop solutions for complex real-world problems. As part of your work, you will investigate applicable academic and industry research to develop, implement, and test solutions that support product features. You will also design and validate production designs. To succeed in this role, you should demonstrate a strong working knowledge of physical systems, a desire to learn from new challenges, and the problem-solving and communication skills to work within a highly interactive and experienced team. Candidates must show a hands-on passion for their work and the ability to communicate their ideas and concepts both verbally and visually. Key job responsibilities - Research, design, implement, and evaluate feedback control, estimation, and motion-planning algorithms, ensuring effective integration with perception, manipulation, and system-level components. - Develop experiments, simulations, and hardware prototypes to validate control algorithms, and optimization techniques in contact-rich manipulation and other challenging scenarios. - Collaborate with software engineering teams to enable scalable, real-time, and maintainable implementations of algorithms in production systems. - Partner with cross-functional teams across hardware, systems engineering, science, and operations to transition algorithms from early prototyping to robust, production-ready solutions. - Engage with stakeholders at all levels to iterate on system design, define requirements, and drive integration of control and estimation capabilities into Amazon Robotics platforms. A day in the life Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!
IN, HR, Gurugram
Lead ML teams building large-scale forecasting and optimization systems that power Amazon’s global transportation network and directly impact customer experience and cost. As an Applied Science Manager, you will set scientific direction, mentor applied scientists, and partner with engineering and product leaders to deliver production-grade ML solutions at massive scale. Key job responsibilities 1. Lead and grow a high-performing team of Applied Scientists, providing technical guidance, mentorship, and career development. 2. Define and own the scientific vision and roadmap for ML solutions powering large-scale transportation planning and execution. 3. Guide model and system design across a range of techniques, including tree-based models, deep learning (LSTMs, transformers), LLMs, and reinforcement learning. 4. Ensure models are production-ready, scalable, and robust through close partnership with stakeholders. Partner with Product, Operations, and Engineering leaders to enable proactive decision-making and corrective actions. 5. Own end-to-end business metrics, directly influencing customer experience, cost optimization, and network reliability. 6. Help contribute to the broader ML community through publications, conference submissions, and internal knowledge sharing. A day in the life Your day includes reviewing model performance and business metrics, guiding technical design and experimentation, mentoring scientists, and driving roadmap execution. You’ll balance near-term delivery with long-term innovation while ensuring solutions are robust, interpretable, and scalable. Ultimately, your work helps improve delivery reliability, reduce costs, and enhance the customer experience at massive scale.
IL, Haifa
Come join the AWS Agentic AI science team in building the next generation models for intelligent automation. AWS, the world-leading provider of cloud services, has fostered the creation and growth of countless new businesses, and is a positive force for good. Our customers bring problems that will give Applied Scientists like you endless opportunities to see your research have a positive and immediate impact in the world. You will have the opportunity to partner with technology and business teams to solve real-world problems, have access to virtually endless data and computational resources, and to world-class engineers and developers that can help bring your ideas into the world. As part of the team, we expect that you will develop innovative solutions to hard problems, and publish your findings at peer reviewed conferences and workshops. We are looking for world class researchers with experience in one or more of the following areas - autonomous agents, API orchestration, Planning, large multimodal models (especially vision-language models), reinforcement learning (RL) and sequential decision making.
AT, Graz
Are you a MS or PhD student interested in a 2026 internship in the field of machine learning, deep learning, generative AI, large language models and speech technology, robotics, computer vision, optimization, operations research, quantum computing, automated reasoning, or formal methods? If so, we want to hear from you! We are looking for students interested in using a variety of domain expertise to invent, design and implement state-of-the-art solutions for never-before-solved problems. You can find more information about the Amazon Science community as well as our interview process via the links below; https://www.amazon.science/ https://amazon.jobs/content/en/career-programs/university/science https://amazon.jobs/content/en/how-we-hire/university-roles/applied-science Key job responsibilities As an Applied Science Intern, you will own the design and development of end-to-end systems. You’ll have the opportunity to write technical white papers, create roadmaps and drive production level projects that will support Amazon Science. You will work closely with Amazon scientists and other science interns to develop solutions and deploy them into production. You will have the opportunity to design new algorithms, models, or other technical solutions whilst experiencing Amazon’s customer focused culture. The ideal intern must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. A day in the life At Amazon, you will grow into the high impact person you know you’re ready to be. Every day will be filled with developing new skills and achieving personal growth. How often can you say that your work changes the world? At Amazon, you’ll say it often. Join us and define tomorrow. Some more benefits of an Amazon Science internship include; • All of our internships offer a competitive stipend/salary • Interns are paired with an experienced manager and mentor(s) • Interns receive invitations to different events such as intern program initiatives or site events • Interns can build their professional and personal network with other Amazon Scientists • Interns can potentially publish work at top tier conferences each year About the team Applicants will be reviewed on a rolling basis and are assigned to teams aligned with their research interests and experience prior to interviews. Start dates are available throughout the year and durations can vary in length from 3-6 months for full time internships. This role may available across multiple locations in the EMEA region (Austria, Estonia, France, Germany, Ireland, Israel, Italy, Jordan, Luxembourg, Netherlands, Poland, Romania, Spain, South Africa, UAE, and UK). Please note these are not remote internships.
US, MA, N.reading
Amazon Industrial Robotics is seeking exceptional talent to help develop the next generation of advanced robotics systems that will transform automation at Amazon's scale. We're building revolutionary robotic systems that combine cutting-edge AI, sophisticated control systems, and advanced mechanical design to create adaptable automation solutions capable of working safely alongside humans in dynamic environments. This is a unique opportunity to shape the future of robotics and automation at an unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic dexterous manipulation, locomotion, and human-robot interaction. This role presents an opportunity to shape the future of robotics through innovative applications of deep learning and large language models. At Amazon Industrial Robotics we leverage advanced robotics, machine learning, and artificial intelligence to solve complex operational challenges at an unprecedented scale. Our fleet of robots operates across hundreds of facilities worldwide, working in sophisticated coordination to fulfill our mission of customer excellence. We are pioneering the development of dexterous manipulation system that: - Enables unprecedented generalization across diverse tasks - Enables contact-rich manipulation in different environments - Seamlessly integrates low-level skills and high-level behaviors - Leverage mechanical intelligence, multi-modal sensor feedback and advanced control techniques. The ideal candidate will contribute to research that bridges the gap between theoretical advancement and practical implementation in robotics. You will be part of a team that's revolutionizing how robots learn, adapt, and interact with their environment. Join us in building the next generation of intelligent robotics systems that will transform the future of automation and human-robot collaboration. Key job responsibilities - Design and implement methods for dexterous manipulation - Design and implement methods for use of dexterous end effectors with force and tactile sensing - Develop a hierarchical system that combines low-level control with high-level planning - Utilize state-of-the-art manipulation models and optimal control techniques
CA, ON, Toronto
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through cutting-edge generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. Key job responsibilities • Collaborate with business, engineering and science leaders to establish science optimization and monetization roadmap for Amazon Retail Ad Service • Drive alignment across organizations for science, engineering and product strategy to achieve business goals • Lead/guide scientists and engineers across teams to develop, test, launch and improve of science models designed to optimize the shopper experience and deliver long term value for Amazon advertisers and third party retailers • Develop state of the art experimental approaches and ML models to keep up with our growing needs and diverse set of customers. • Participate in the Science hiring process as well as mentor other scientists - improving their skills, their knowledge of your solutions, and their ability to get things done. About the team Amazon Retail Ad Service within Sponsored Products and Brands is an ad-tech solution that enables retailers to monetize their online web and app traffic by displaying contextually relevant sponsored products ads. Our mission is to provide retailers with ad-solution for every type of supply to meet their advertising goals. At the same time, enable advertisers to manage their demand across multiple supplies (Amazon, offsite, third-party retailers) leveraging tools they are already familiar with. Our problem space is challenging and exciting in terms of different traffic patterns, varying product catalogs based on retailer industry and their shopper behaviors.
US, WA, Bellevue
Alexa+ is Amazon’s next-generation, AI-powered virtual assistant. Building on the original Alexa, it uses generative AI to deliver a more conversational, personalized, and effective experience. As an Applied Scientist II on the Alexa Sensitive Content Intelligence (ASCI) team, you'll be part of an elite group developing industry-leading technologies in attribute extraction and sensitive content detection that work seamlessly across all languages and countries. In this role, you'll join a team of exceptional scientists pushing the boundaries of Natural Language Processing. Working in our dynamic, fast-paced environment, you'll develop novel algorithms and modeling techniques that advance the state of the art in NLP. Your innovations will directly shape how millions of customers interact with Amazon Echo, Echo Dot, Echo Show, and Fire TV devices every day. What makes this role exciting is the unique blend of scientific innovation and real-world impact. You'll be at the intersection of theoretical research and practical application, working alongside talented engineers and product managers to transform breakthrough ideas into customer-facing experiences. Your work will be crucial in ensuring Alexa remains at the forefront of AI technology while maintaining the highest standards of trust and safety. We're looking for a passionate innovator who combines strong technical expertise with creative problem-solving skills. Your deep understanding of NLP models (including LSTM and transformer-based architectures) will be essential in tackling complex challenges and identifying novel solutions. You'll leverage your exceptional technical knowledge, strong Computer Science fundamentals, and experience with large-scale distributed systems to create reliable, scalable, and high-performance products that delight our customers. Key job responsibilities In this dynamic role, you'll design and implement GenAI solutions that define the future of AI interaction. You'll pioneer novel algorithms, conduct ground breaking experiments, and optimize user experiences through innovative approaches to sensitive content detection and mitigation. Working alongside exceptional engineers and scientists, you'll transform theoretical breakthroughs into practical, scalable solutions that strengthen user trust in Alexa globally. You'll also have the opportunity to mentor rising talent, contributing to Amazon's culture of scientific excellence while helping build high-performing teams that deliver swift, impactful results. A day in the life Imagine starting your day collaborating with brilliant minds on advancing state-of-the-art NLP algorithms, then moving on to analyze experiment results that could reshape how Alexa understands and responds to users. You'll partner with cross-functional teams - from engineers to product managers - to ensure data quality, refine policies, and enhance model performance. Your expertise will guide technical discussions, shape roadmaps, and influence key platform features that require cross-team leadership. About the team The Alexa Sensitive Content Intelligence (ASCI) team owns the Responsible AI and customer feedback charters in Alexa+ and Classic Alexa across all device endpoints, modalities and languages. The mission of our team is to (1) minimize negative surprises to customers caused by sensitive content, (2) detect and prevent potential brand-damaging interactions, (3) build customer trust through generating appropriate interactions on sensitive topics, and (4) analyze customer feedback to gain insight and drive continuous improvement loops. The term “sensitive content” includes within its scope a wide range of categories of content such as offensive content (e.g., hate speech, racist speech), profanity, content that is suitable only for certain age groups, politically polarizing content, and religiously polarizing content. The term “content” refers to any material that is exposed to customers by Alexa (including both 1P and 3P experiences) and includes text, speech, audio, and video.
US, WA, Seattle
Are you passionate to join an innovative team of scientists and engineers who use machine learning and AI techniques to create state-of-the-art solutions to help seller succeed on Amazon? The Selling Partner Growth org is looking for a Senior Applied Scientist to lead us on our mission to understand demand side signals on Amazon, and empower sellers to grow their business and provide a great customer experience. As a Senior Applied Scientist on our team of scientists and engineers, you will have opportunities to create significant impact on our systems, our business and most importantly, our customers as we take on challenges that can revolutionize the e-commerce industry. You will identify specific and actionable opportunities to solve business problems, propose state-of-the-art solutions and collaborate with engineering, and business teams for future innovation. You need to be a great translation between ambiguous business domains and rigorous scientific solutions, an expert at inventing and simplify, and a good communicator to surface insights and recommendations to audiences of varying levels of technical sophistication. Major responsibilities - Use machine learning and AI techniques to create scalable seller-facing solutions - Analyze and extract relevant information from large amounts of Amazon's historical business data to help automate and optimize key processes - Design, development and evaluation of highly innovative models - Work closely with software engineering teams to drive real-time model implementations and new feature creations To know more about Amazon science, Please visit https://www.amazon.science