3 questions with Antia Lamas-Linares about the Nobel Prize in physics

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

Last week, the Swedish Academy announced that John Clauser, Alain Aspect, and Anton Zeilinger had won the Nobel Prize in physics “for experiments with entangled photons, establishing the violation of Bell inequalities, and pioneering quantum information science”.

Antia Lamas-Linares, quantum networking lead at Amazon Web Services and an expert in quantum optics, is seen looking into the camera
Antia Lamas-Linares, a principal research scientist with Amazon Web Services (AWS) and head of the AWS Center for Quantum Networking.

When two quantum subsystems — particles, atoms, or molecules — are “entangled”, then measurements performed on one are correlated with measurements performed on the other. The experimental setup that Clauser, Aspect, and Zeilinger investigated — in which entangled quantum subsystems have been widely separated — is closely related to those used in modern quantum networks.

The first application of quantum networking is likely to be quantum key distribution, in which two parties exchange private cryptographic keys and use quantum entanglement to ensure that their communication channel hasn’t been compromised.

On the occasion of the Swedish Academy’s announcement, Amazon Science asked Antia Lamas-Linares, who leads Amazon Web Services’ Center for Quantum Networking, three questions about Clauser, Aspect, and Zeilinger’s work and its implications for her own field.

  1. Q. 

    One of the things that Clauser and Aspect did to win the Nobel Prize was a set of experiments that challenged the “hidden-variable hypothesis”. What is the hidden-variable hypothesis, and what were their experiments?

    A. 

    At the beginnings of quantum mechanics, when people started looking at this theory that was really successful at doing things like predicting the spectra coming out of atoms, and they started looking at the implications for how we understand physical theories, there was this epic battle that went on for years between Einstein and Bohr, two giants of early 20th-century physics.

    The problem was that as you look deeply into the theory, you realize that there is, for example, inherent randomness. You can prepare a couple of systems in identical ways, and you measure something about the system, and the outcomes are different. And they are different for very fundamental reasons. It's not just, oh, we just didn't have enough information. No, even with perfect information, the outcomes of identical measurement can be different. This was not compatible with how physical theories were supposed to work.

    Entanglement has made this progression from being an uncomfortable property of quantum systems — and a philosophical question — to something that constitutes the basis of quantum technologies.
    Antia Lamas-Linares

    It became a sort of hobby of Einstein’s to come up with little paradoxes based on these things that challenged the way we understand physical theories, from a very foundational point of view. In quantum mechanics, you can formally write something that we call an entangled state, and this is a state that involves more than one particle or more than one subsystem. It describes correlations between parts of that system.

    Einstein’s point was, if I take the two subsystems and separate them very far away, then I can measure something on one and know the outcome in the other one instantaneously, or faster than light communication, which is not compatible with relativity. His conclusion was that there must be an underlying theory that “explained” the quantum-mechanical correlations and the apparent randomness of measurement outcomes.

    Essentially, the results look random because there are these hidden variables that we don't know about. But if we knew their values, the results would be predictable. These theories became known as “hidden variable” theories.

    It wasn't until the ’60s that John Bell wrote a beautiful, very simple theorem where he said, let's assume that there is some underlying information, some underlying physical theory that works in this general way. Can I have a set of measurements that have different outcomes from the quantum-mechanical model?

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

    This is called the Bell inequality. It says, if you measure a particular sequence of correlations and you get a value below a certain threshold, then there could be an underlying hidden-variable theory of quantum mechanics. But if the value is above this threshold, then quantum mechanics cannot be explained by hidden variables. At this point, no matter how uncomfortable we are with the implications of quantum mechanics, we don’t get to pretend there is an underlying theory that will explain it all away.

    It really changes our perception of the nature of reality. The randomness in measurement results is fundamental to nature. It's not just an accident from the lack of information about the hidden variables.

    Eventually, people said, Well, okay, let's test these things. For that, you need to make entangled particles, and you need to measure them in the way prescribed by Bell’s theorem. That's essentially what John Clauser and Alain Aspect did during the late ’70s and early ’80s, with increasing levels of sophistication. Anton Zeilinger wasn't part of those Bell inequality measurements, but he used entanglement in a multitude of ground-breaking experiments, such as quantum teleportation, entanglement swapping, and the generation of tripartite entangled states.

    Clauser experiment
    In his original experiment, John Clauser used irradiated calcium atoms to emit pairs of entangled photons and polarizing filters to measure correlations between their polarizations.
    Adapted from a figure by Johan Jarnestad for the Royal Swedish Academy of Sciences

  2. Q. 

    So what does this all have to do with quantum networking?

    A. 

    With quantum networking, the two sides start by sharing entangled particles. The idea is that the outcomes on both sides are perfectly correlated, but if a malicious party tries to measure in-between, the correlations are broken, and this is detectable by the legitimate parties. It's related to the fact that quantum mechanics has properties like the no-cloning theorem that ensure that unknown quantum states cannot be perfectly copied. So you cannot just take any particle that is coming by and make a copy, because this inevitably alters the original state.

    Related content
    Collaboration will seek to advance the development of a quantum internet.

    So the two sides take a subset of the results, and using classical communication, they say, Hey, let's check that nobody has interfered with our measurements. What did you get for the first one? How about number 3,047? And they can check that the correlations are as expected from quantum theory. They sacrifice maybe 10% of their data to check this, and if the correlations hold, they can be sure that nobody has otherwise tampered with the entangled particles.

    Now to be clear, they're not sharing a message. They're sharing correlated random numbers, obtained from measurements on the entangled pair of particles. Correlated random numbers are exactly what you need for a symmetric cryptographic key. When you use a key as part of a cryptographic system, you need two parties to share a secret. It doesn't matter what the secret is, as long as it is not predictable. In this way quantum mechanics gives us the two requirements for a cryptographic key: randomness and privacy.

  3. Q. 

    It’s been 50 years since Clauser’s original experiment. How has our thinking about these questions changed in the interim?

    A. 

    What’s exciting about this is that entanglement has made this progression from being an uncomfortable property of quantum systems — and a philosophical question — to something that constitutes the basis of quantum technologies. We no longer consider entanglement an uncomfortable consequence of quantum mechanics. It is now a resource.

    Related content
    Among the ‘first wave’ of scientists to gain a PhD in quantum technology, the senior manager of research science discusses her two-decade-long career journey.

    Alain Aspect has said that when he was doing his PhD, he was repeatedly discouraged from pursuing these experiments because working on the foundations of physics was a career killer. This is not what you do if you want to be successful.

    My own PhD centered on building entanglement sources, which is a very engineering-focused task. I needed to engineer a system — in my case, a nonlinear crystal — to give me higher-quality entangled photon pairs. I wasn’t trying to prove philosophical questions regarding entanglement.

    You could consider large parts of what Oskar [Painter, head of quantum hardware at Amazon Web Services] does and what I do as “entanglement engineering”. Our groups in AWS do quantum engineering, and entanglement is a vital resource that we produce, channel, and measure. That is a pretty radical evolution from where things stood when John, Alain, and Anton did their groundbreaking work.

Research areas

Related content

US, WA, Seattle
Amazon's Worldwide Pricing & Promotions organization is seeking a talented, hands-on Research Scientist to join the Pricing and Promotion Optimization Science (P2OS) team — the optimization "application layer" within Amazon's Pricing Sciences organization. Amazon adjusts prices on hundreds of millions of products daily across a global marketplace; P2OS is the team that makes those prices optimal. P2OS is a small, specialized unit with an outsized charter: develop and maintain the models that determine optimal prices and promotions across Amazon's catalog and merchant programs. We own the full optimization stack — from price prediction to promotion targeting to competitiveness guardrails — and we measure success in terms of accretive Gross Contribution and Customer Pricing Perception (GCCP). Our work spans Retail Core, Amazon Business, Fresh, Grocery, and international marketplaces, and we are continually investing in more extensible, generalizable science foundations to keep pace with a growing and evolving business. We are looking for an innovative, organized, and customer-focused scientist with exceptional machine learning and predictive modeling skills, causal and experimental evaluation experience, and the entrepreneurial spirit to apply state-of-the-art methods to some of the most impactful pricing problems in e-commerce. You should be comfortable with ambiguity, motivated by measurable business impact, and excited by the opportunity to work at Amazon-scale. Key job responsibilities * Innovate and build. Design, develop, and deploy machine learning models that set optimal prices and promotions across Amazon's global catalog. Own models end-to-end — from problem formulation and data analysis through offline evaluation, A/B testing, and production launch. * Build a generalizable science foundation. Develop models and evaluation frameworks designed to scale across merchant programs, product categories, and marketplaces — enabling cross-learning and reducing the time and cost of applying science to new business contexts. * Build and evolve optimization systems. Design and improve optimization systems — including reinforcement learning and multi-objective optimization approaches — that automate price and promotion decisions at scale across millions of products. * Apply generative AI and foundation models. Identify and pursue opportunities to leverage large language models, embeddings, and generative AI techniques in pricing science — from enriching product representations and extracting competitive signals from unstructured data, to building more capable and explainable pricing systems. * Experiment rigorously. Design and execute A/B tests and causal inference studies to measure the business and customer impact of pricing model changes. Translate findings into production-ready science improvements. * Stay at the frontier. Establish mechanisms to track the latest advances in reinforcement learning, causal ML, multi-objective optimization, generative AI, and demand modeling — and identify opportunities to apply them to Pricing & Promotions business problems. * See the big picture. Contribute to the long-term scientific vision for how Amazon sets competitive, perception-preserving prices — balancing profitability, customer trust, and marketplace health.
US, CA, San Francisco
Amazon is on a mission to redefine the future of automation — and we're looking for exceptional talent to help lead the way. We are building the next generation of advanced robotic systems that seamlessly blend cutting-edge AI, sophisticated control systems, and novel mechanical design to create adaptable, intelligent automation solutions capable of operating safely alongside humans in dynamic, real-world environments. At Amazon, we leverage the power of machine learning, artificial intelligence, and advanced robotics to solve some of the most complex operational challenges at a scale unlike anywhere else in the world. Our fleet of robots spans hundreds of facilities globally, working in sophisticated coordination to deliver on our promise of customer excellence — and we're just getting started. As a Sr. Scientist in Robot Navigation, you will be at the forefront of this transformation — architecting and delivering navigation systems that are intelligent, safe, and scalable. You will bring deep expertise in learning-based planning and control, a strong understanding of foundation models and their application to embodied agents, and as well as have in-depth understanding of control-theoretic approaches such as model predictive control (MPC)-based trajectory planning. You will develop navigation solutions that seamlessly blend data-driven intelligence with principled control-theoretic guarantees. Our vision is bold: to build navigation systems that allow robots to move fluidly and safely through dynamic environments — understanding context, anticipating change, and adapting in real time. You will lead research that bridges the gap between cutting-edge academic advances and production grade deployment, collaborating with world-class teams pushing the boundaries of robotic autonomy, manipulation, and human-robot interaction. Join us in building the next generation of intelligent navigation systems that will define the future of autonomous robotics at scale. Key job responsibilities - Design, develop, and deploy perception algorithms for robotics systems, including object detection, segmentation, tracking, depth estimation, and scene understanding - Lead research initiatives in computer vision, sensor fusion and 3D perception - Collaborate with cross-functional teams including robotics engineers, software engineers, and product managers to define and deliver perception capabilities - Drive end-to-end ownership of ML models — from data collection and labeling strategy to training, evaluation, and deployment - Mentor junior scientists and engineers; contribute to a culture of technical excellence - Define and track key metrics to measure perception system performance in real-world environments - Publish research findings in top-tier venues (CVPR, ICCV, ECCV, ICRA, NeurIPS, etc.) and contribute to patents A day in the life - Train ML models for deployment in simulation and real-world robots, identify and document their limitations post-deployment - Drive technical discussions within your team and with key stakeholders to develop innovative solutions to address identified limitations - Actively contribute to brainstorming sessions on adjacent topics, bringing fresh perspectives that help peers grow and succeed — and in doing so, build lasting trust across the team - Mentor team members while maintaining significant hands-on contribution to technical solutions About the team Our team is a group is a diverse group of scientists and engineers passionate about building intelligent machines. We value curiosity, rigor, and a bias for action. We believe in learning from failure and iterating quickly toward solutions that matter.
US, WA, Seattle
Applied Scientists in AWS Automated Reasoning are dedicated to making AWS the best computing service in the world for customers who require advanced and rigorous solutions for automated reasoning, privacy, and sovereignty. Key job responsibilities The successful candidate will: - Solve large or significantly complex problems that require deep knowledge and understanding of your domain and scientific innovation. - Own strategic problem solving, and take the lead on the design, implementation, and delivery for solutions that have a long-term quantifiable impact. - Provide cross-organizational technical influence, increasing productivity and effectiveness by sharing your deep knowledge and experience. - Develop strategic plans to identify fundamentally new solutions for business problems. - Assist in the career development of others, actively mentoring individuals and the community on advanced technical issues. A day in the life This is a unique and rare opportunity to get in early on a fast-growing segment of AWS and help shape the technology, product and the business. You will have a chance to utilize your deep technical experience within a fast moving, start-up environment and make a large business and customer impact. About the team Diverse Experiences Amazon Automated Reasoning 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 Amazon Automated Reasoning? At Amazon, automated reasoning is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for automated reasoning across all of Amazon's products and services. We offer talented automated reasoning professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores. Inclusive Team Culture In Amazon Automated Reasoning, it's in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest automated reasoning challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices. Training & 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, training, 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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there's nothing we can't achieve.
US, WA, Seattle
Applied Scientists in AWS Automated Reasoning are dedicated to making AWS the best computing service in the world for customers who require advanced and rigorous solutions for automated reasoning, privacy, and sovereignty. Key job responsibilities The successful candidate will: - Solve large or significantly complex problems that require deep knowledge and understanding of your domain and scientific innovation. - Own strategic problem solving, and take the lead on the design, implementation, and delivery for solutions that have a long-term quantifiable impact. - Provide cross-organizational technical influence, increasing productivity and effectiveness by sharing your deep knowledge and experience. - Develop strategic plans to identify fundamentally new solutions for business problems. - Assist in the career development of others, actively mentoring individuals and the community on advanced technical issues. A day in the life This is a unique and rare opportunity to get in early on a fast-growing segment of AWS and help shape the technology, product and the business. You will have a chance to utilize your deep technical experience within a fast moving, start-up environment and make a large business and customer impact. About the team Diverse Experiences Amazon Automated Reasoning 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 Amazon Automated Reasoning? At Amazon, automated reasoning is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for automated reasoning across all of Amazon's products and services. We offer talented automated reasoning professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores. Inclusive Team Culture In Amazon Automated Reasoning, it's in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest automated reasoning challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices. Training & 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, training, 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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there's nothing we can't achieve.
GB, London
Are you excited about using econometrics, experimentation, and machine learning to impact real-world business decisions? We are looking for an Economist II to work on challenging problems at the intersection of causal inference and machine learning for Prime Video Ads. You will design experiments, build econometric and ML models, and translate findings into decisions that shape how millions of customers experience advertising on Prime Video. If you have a deeply quantitative approach to problem-solving, enjoy building and implementing models end-to-end, and want to work on problems where rigorous economics meets production-scale ML, we want to talk to you. Key job responsibilities - Design, execute, and analyze experiments to measure the impact of ad policies on customer behavior and business outcomes - Develop causal inference models (experimental and observational) to estimate short- and long-term effects of strategic initiatives - Collaborate with scientists, engineers, and product teams to deliver measurable business impact - Influence business leaders based on empirical findings
US, MA, Boston
Applied Scientists in AWS Automated Reasoning are dedicated to making AWS the best computing service in the world for customers who require advanced and rigorous solutions for automated reasoning, privacy, and sovereignty. Key job responsibilities The successful candidate will: - Solve large or significantly complex problems that require deep knowledge and understanding of your domain and scientific innovation. - Own strategic problem solving, and take the lead on the design, implementation, and delivery for solutions that have a long-term quantifiable impact. - Provide cross-organizational technical influence, increasing productivity and effectiveness by sharing your deep knowledge and experience. - Develop strategic plans to identify fundamentally new solutions for business problems. - Assist in the career development of others, actively mentoring individuals and the community on advanced technical issues. A day in the life This is a unique and rare opportunity to get in early on a fast-growing segment of AWS and help shape the technology, product and the business. You will have a chance to utilize your deep technical experience within a fast moving, start-up environment and make a large business and customer impact. About the team Diverse Experiences Amazon Automated Reasoning 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 Amazon Automated Reasoning? At Amazon, automated reasoning is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for automated reasoning across all of Amazon's products and services. We offer talented automated reasoning professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores. Inclusive Team Culture In Amazon Automated Reasoning, it's in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest automated reasoning challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices. Training & 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, training, 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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there's nothing we can't achieve.
US, MA, Boston
Applied Scientists in AWS Automated Reasoning are dedicated to making AWS the best computing service in the world for customers who require advanced and rigorous solutions for automated reasoning, privacy, and sovereignty. Key job responsibilities The successful candidate will: - Solve large or significantly complex problems that require deep knowledge and understanding of your domain and scientific innovation. - Own strategic problem solving, and take the lead on the design, implementation, and delivery for solutions that have a long-term quantifiable impact. - Provide cross-organizational technical influence, increasing productivity and effectiveness by sharing your deep knowledge and experience. - Develop strategic plans to identify fundamentally new solutions for business problems. - Assist in the career development of others, actively mentoring individuals and the community on advanced technical issues. A day in the life This is a unique and rare opportunity to get in early on a fast-growing segment of AWS and help shape the technology, product and the business. You will have a chance to utilize your deep technical experience within a fast moving, start-up environment and make a large business and customer impact. About the team Diverse Experiences Amazon Automated Reasoning 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 Amazon Automated Reasoning? At Amazon, automated reasoning is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for automated reasoning across all of Amazon's products and services. We offer talented automated reasoning professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores. Inclusive Team Culture In Amazon Automated Reasoning, it's in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest automated reasoning challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices. Training & 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, training, 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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there's nothing we can't achieve.
US, TX, Austin
Applied Scientists in AWS Automated Reasoning are dedicated to making AWS the best computing service in the world for customers who require advanced and rigorous solutions for automated reasoning, privacy, and sovereignty. Key job responsibilities The successful candidate will: - Solve large or significantly complex problems that require deep knowledge and understanding of your domain and scientific innovation. - Own strategic problem solving, and take the lead on the design, implementation, and delivery for solutions that have a long-term quantifiable impact. - Provide cross-organizational technical influence, increasing productivity and effectiveness by sharing your deep knowledge and experience. - Develop strategic plans to identify fundamentally new solutions for business problems. - Assist in the career development of others, actively mentoring individuals and the community on advanced technical issues. A day in the life This is a unique and rare opportunity to get in early on a fast-growing segment of AWS and help shape the technology, product and the business. You will have a chance to utilize your deep technical experience within a fast moving, start-up environment and make a large business and customer impact. About the team Diverse Experiences Amazon Automated Reasoning 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 Amazon Automated Reasoning? At Amazon, automated reasoning is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for automated reasoning across all of Amazon's products and services. We offer talented automated reasoning professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores. Inclusive Team Culture In Amazon Automated Reasoning, it's in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest automated reasoning challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices. Training & 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, training, 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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there's nothing we can't achieve.
US, TX, Austin
Applied Scientists in AWS Automated Reasoning are dedicated to making AWS the best computing service in the world for customers who require advanced and rigorous solutions for automated reasoning, privacy, and sovereignty. Key job responsibilities The successful candidate will: - Solve large or significantly complex problems that require deep knowledge and understanding of your domain and scientific innovation. - Own strategic problem solving, and take the lead on the design, implementation, and delivery for solutions that have a long-term quantifiable impact. - Provide cross-organizational technical influence, increasing productivity and effectiveness by sharing your deep knowledge and experience. - Develop strategic plans to identify fundamentally new solutions for business problems. - Assist in the career development of others, actively mentoring individuals and the community on advanced technical issues. A day in the life This is a unique and rare opportunity to get in early on a fast-growing segment of AWS and help shape the technology, product and the business. You will have a chance to utilize your deep technical experience within a fast moving, start-up environment and make a large business and customer impact. About the team Diverse Experiences Amazon Automated Reasoning 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 Amazon Automated Reasoning? At Amazon, automated reasoning is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for automated reasoning across all of Amazon's products and services. We offer talented automated reasoning professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores. Inclusive Team Culture In Amazon Automated Reasoning, it's in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest automated reasoning challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices. Training & 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, training, 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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there's nothing we can't achieve.
US, MA, Boston
Sr. Applied Scientists in AWS Automated Reasoning are dedicated to making AWS the best computing service in the world for customers who require advanced and rigorous solutions for automated reasoning, privacy, and sovereignty. Key job responsibilities The successful candidate will: - Solve large or significantly complex problems that require deep knowledge and understanding of your domain and scientific innovation. - Own strategic problem solving, and take the lead on the design, implementation, and delivery for solutions that have a long-term quantifiable impact. - Provide cross-organizational technical influence, increasing productivity and effectiveness by sharing your deep knowledge and experience. - Develop strategic plans to identify fundamentally new solutions for business problems. - Assist in the career development of others, actively mentoring individuals and the community on advanced technical issues. A day in the life This is a unique and rare opportunity to get in early on a fast-growing segment of AWS and help shape the technology, product and the business. You will have a chance to utilize your deep technical experience within a fast moving, start-up environment and make a large business and customer impact. About the team Diverse Experiences Amazon Automated Reasoning 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 Amazon Automated Reasoning? At Amazon, automated reasoning is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for automated reasoning across all of Amazon's products and services. We offer talented automated reasoning professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores. Inclusive Team Culture In Amazon Automated Reasoning, it's in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest automated reasoning challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices. Training & 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, training, 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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there's nothing we can't achieve.