Recent honors and awards for Amazon scientists

Researchers honored for their contributions to the scientific community.

Kostas Bimpikis honored with the Revenue Management and Pricing Section Prize

Kostas Bimpikis, an Amazon Scholar working with Amazon Flex, won the 2022 INFORMS Revenue Management and Pricing Section Prize for the 2019 paper, “Spatial Pricing in Ride-Sharing Networks”.

Kostas Bimpikis profile pic
Kostas Bimpikis

The paper, coauthored by Ozan Candogan, professor of operations management at the University of Chicago, and Daniela Saban, associate professor of Operations, Information, and Technology at Stanford, was awarded for being “the best contribution to the science of pricing and revenue management published in English.”

The paper, published in Operations Research in 2019, explores “spatial price discrimination in the context of a ride-sharing platform that serves a network of locations.” The paper addressed the issue of location-based pricing and found that, by setting different prices across their networks, ride-sharing companies and drivers would benefit from more balanced demand patterns.

The award was presented at INFORMS 2022, the world’s largest operations research and analytics conference.

Bimpikis is an associate professor of Operations, Information, and Technology and a Winnick Family Faculty Scholar at the Stanford Graduate School of Business.

Bimpikis, who joined Amazon as a Scholar in July 2020, also currently serves as an associate editor for Management Science, Operations Research, and Manufacturing and Service Operations Management.

Anton van den Hengel earns Pattern Recognition Journal’s Best Paper Award

Anton van den Hengel, Amazon director of applied science, has won Pattern Recognition Journal’s Best Paper Award for a 2019 paper on deep-learning architectures.

Anton van den Hengel is seen smiling into the camera, with some office buildings in the background
Anton van den Hengel

The paper, “Wider or Deeper: Revisiting the ResNet Model for Visual Recognition”, undermined conventional wisdom by demonstrating that increasing depth may not be the best way to improve the performance of a deep neural network. Van den Hengel, who was also a professor of computer science at the University of Adelaide, coauthored the paper with fellow university researchers Zifeng Wu and Chunhua Shen.

Since its publication, the paper has received more than 1,000 citations. The model published with the paper has been included in many primary deep learning packages and in MATLAB.

Van den Hengel joined Amazon as director of applied science in March of 2020. At Amazon, he leads a research team working in machine learning and computer vision, with specific focus on vision and language, as well as on natural language processing.

Van den Hengel was the founding director of the Australian Institute for Machine Learning (AIML), Australia’s first institute dedicated to machine learning research. He continues to work part-time as director of AIML’s new Centre for Augmented Reasoning, whose mission is to build core artificial intelligence (AI) capability in Australia.

Established more than 50 years ago, Pattern Recognition accepts papers that make original contributions to the theory, methodology, and application of pattern recognition.

Sergei Kalinin named an Asia-Pacific Artificial Intelligence Association fellow and winner of Foresight Institute Feynman Prize in Experiment

Sergei Kalinin, an Amazon principal research scientist, has been named a fellow of the Asia-Pacific Artificial Intelligence Association (AAIA).

Sergei Kalinin
Sergei Kalinin

The AAIA selected Kalinin for his “outstanding achievements in the area of application of machine learning and artificial intelligence in atomically resolved and mesoscopic imaging.”

Traditionally, mesoscopic imaging allows scientists to explore objects ranging from materials microstructure to organization of biological tissues. Kalinin applied mesoscopic imaging to guide the development of advanced materials for energy and information technologies.

Kalinin earned his master’s degree in materials science from Moscow State University in 1998. He went on to earn his PhD in materials science from the University of Pennsylvania in 2002. He spent nearly 20 years at Oak Ridge National Laboratory (ORNL), where his initial research centered around scanning-probe microscopy methods for probing ferroelectric and energy materials, including batteries and fuel cells. In 2016, Kalinin began working on machine learning methods in electron microscopy for applications such as real-time image analytics, automated and autonomous microscopy, and direct atomic fabrication.

Kalinin left ORNL in March of 2022 to become a research professor at the University of Tennessee, Knoxville. At that time, he also joined Amazon as a principal research scientist working on special projects. In addition to AI, his areas of interest include photovoltaics, physics, and electrochemistry.

Kalinin also has served on the board of directors of the Materials Research Society and in 2019 was a founding member of the American Physical Society Topical Group on Data Science. He is a fellow of the American Physical Society, Materials Research Society, the Institute of Physics, the Institute of Electrical and Electronics Engineers (IEEE), and AVS: Science and Technology of Materials, Interfaces, and Processing (formerly the American Vacuum Society).

The AAIA is a nonprofit, nongovernmental interdisciplinary organization of industries that use AI in their applications, such as computing, communication, medical, transportation, agriculture, and many others. Incorporated in Hong Kong in 2021, the organization’s primary mission is to help scientists enhance the development and application of AI through academic research, exchanges, conferences, publications, and other activities.

Additionally, Kalinin recently won the 2022 Foresight Institute Feynman Prize in Experiment for his work in nanotechnology.

Nanotechnology studies materials and systems by focusing on the manipulation of individual atoms and molecules at nanoscale, or less than 100 millionth of a millimeter.

Awarded annually since 1993, the Feynman Prize is named in honor of the pioneer American theoretical physicist Richard Feynman, who won the Nobel Prize in physics in 1965 for his contributions to the development of quantum electrodynamics. Many nanotechnology advocates recognize Feynman’s 1959 lecture, “There’s Plenty of Room at the Bottom: An Invitation to Enter a New Field of Physics”, as a seminal inspiration for the burgeoning field of nanotechnology.

The Foresight Institute Feynman Prize for Experiment is awarded for excellence in experimentation to the researchers whose recent work has most advanced the achievement of Feynman’s goal for nanotechnology. This goal centers around molecular manufacturing, which is the construction of atomically precise products through the use of molecular machine systems.

Vinícius Loti de Lima wins Brazil’s Best PhD Thesis Award

The Brazilian Computer Society has awarded first place in the XXXV Theses and Dissertations Contest (CTD 2022) to the doctoral thesis of Vinícius Loti de Lima, an Amazon applied scientist. His thesis was also awarded best thesis by the Brazilian Society of Operational Research and received honorable mention from the Brazilian Society of Computational and Applied Mathematics.

Vinícius Loti de Lima
Vinícius Loti de Lima

The thesis, “Integer Programming Based Methods Applied to Cutting, Packing, and Scheduling”, studied solution methods for combinatorial optimization. The thesis proposed several general methods for deriving algorithms that are fundamental to computer science and operations research.

In the paper, de Lima applied his methods to many well-studied cutting, packing, and scheduling problems. He also proposed solutions to facilitate future research on two-dimensional cutting and packing.

Established in 1978, the Brazilian Computer Society (or SBC, for Sociedade Brasileira de Computação in Portuguese), is an educational organization dedicated to the advancement of computer science in Brazil. SBC is the largest computer society in South America and serves as a forum for researchers, students, and professionals in computer science and information technology.

On average, there are about 300 PhD defenses in computer science each year in Brazil. The Brazilian Computer Society chose 43 candidates for evaluation for the award.

In December 2021, de Lima earned his PhD in computer science from Universidade Estadual de Campinas in São Paulo. His primary research interests included the development of mathematical programming methods, combinatorial algorithms, and decomposition schemes to solve large-scale optimization problems of general relevance.

In April 2022, de Lima joined Amazon as an applied scientist on the capacity planning team. At Amazon, de Lima works on solving real-world optimization problems at scale, applying in practice the theories he developed during his doctoral research.

Gérard Medioni elected as NAI fellow

The National Academy of Inventors (NAI) has named Gérard Medioni, vice president, and distinguished scientist, AWS Applications, as an NAI fellow. Election as an academic fellow is the highest professional distinction awarded to academic inventors.

Gérard Medioni
Gérard Medioni

Medioni has spent more than 40 years researching computer vision and has received more than 52 patents for his work.

He joined Amazon in 2014 to lead the development of the “just walk out” technology for Amazon Go grocery stores. More recently, he has been working on Amazon One, a service that lets people use their palms as a contactless method to pay at a store, present a loyalty card, badge into work, or enter a stadium. He also led the development of the recommendation system for Amazon Style, Amazon’s first-ever physical store with clothing, shoes, and accessories for men, women, and kids.

Medioni, who earned his PhD in computer science from the University of Southern California (USC) in 1983, is also professor emeritus of computer science in the USC Viterbi School of Engineering. Medioni served as chair of the USC Viterbi Department of Computer Science from 2001 to 2007.

NAI aims to benefit society through recognizing and encouraging inventors with US patents, enhancing the visibility of academic technology and innovation, encouraging the disclosure of intellectual property, and educating and mentoring students.

The 2022 class of NAI fellows spans 110 organizations, with research and entrepreneurship that cover a broad range of scientific disciplines.

IFIP confers distinction of fellow to Rustan Leino

The International Federation for Information Processing (IFIP) has named Amazon senior principal applied scientist Rustan Leino as an IFIP fellow, its most prestigious technical distinction. Leino earned the honor in recognition of “outstanding contributions in the field of information processing.”

Rustan Leino
Rustan Leino

IFIP fellowship recognizes members who contribute significantly to driving innovation, conducting research, and developing industry in the information communications technology sector.

Leino works for Amazon Web Services (AWS) as a senior principal engineer in the Automated Reasoning Group (ARG).

At AWS, Leino’s work focuses on formal verification, programming languages, and software-correctness tools for software engineers.

Leino, who earned his master’s degree and PhD in computer science the California Institute of Technology, began his professional career in 1989 on the Microsoft Windows LAN Manager team, and worked at Microsoft for nearly three decades before joining Amazon in 2017. He was named a fellow by the Association for Computing Machinery (ACM) in 2016.

Established in 1960 under the auspices of the United Nations Educational, Scientific and Cultural Organization, the IFIP is a global organization for researchers and professionals working in information and communication technologies.

Leino is currently the chairperson of IFIP Working Group (WG) 2.3, “Programming Methodology.” He has been an active member of WG 2.3 for more than 20 years, serving as secretary for nine years and vice chair for six years. Other IFIP WG 2.3 members at AWS are Ernie Cohen, Rajeev Joshi, Serdar Tasiran, and Emina Torlak, as well as emeritus members John Harrison and Ken McMillan.

Association for Computing Machinery honors Matthew Lease as distinguished member

The Association for Computing Machinery (ACM) has named Amazon Scholar Matthew Lease as a distinguished member for Outstanding Scientific Contributions to Computing. Distinguished members are longstanding ACM members selected by their peers for specific, impactful work that has “spurred innovation, enhanced computer science education, and moved the field forward.”

Matthew Lease
Matthew Lease

Lease is one of 67 distinguished members named in 2022. Honorees are selected for their contributions in three separate categories: educational, engineering, and scientific. They must have at least 15 years of experience in computing, five years of professional ACM membership, and significant accomplishments in the field of computing. Distinguished members also have served as mentors or role models through guiding technical career development.

Lease is the head of the Laboratory for Artificial Intelligence and Human-Centered Computing at University of Texas (UT) Austin, where his research integrates AI with human-computer interaction techniques.

In addition, Lease is a faculty founder and leader of UT Austin’s Good Systems, an eight-year, university-wide initiative to design responsible AI technologies that include agency, equity, trust, transparency, democracy, and justice.

Lease, who earned PhD in computer science from Brown in 2009, has been at UT Austin since August 2009. As a professor in the School of Information, Lease has two principal research areas: information retrieval (IR) and crowdsourcing and human computation (HCOMP).

His IR research works to improve search engines through the development of new models and algorithms. His HCOMP works focuses on using machine learning to build hybrid systems that integrate AI and HCOMP.

Prem Natarajan and Sherief Reda named IEEE fellows

Prem Natarajan, vice president of Alexa AI, was elected to be a fellow of the IEEE Computer Society for his contributions to conversational AI systems, spoken language translation, and home voice-assistant systems.

Prem Natarajan.jpeg

The holder of ten patents, Natarajan leads the development of technical vision and operations strategy for Alexa.

Natarajan earned a master’s degree and PhD in electrical engineering from Tufts University, and completed the executive program in business administration and management from the Massachusetts Institute of Technology Sloan School of Management.

He spent 17 years at Raytheon BBN Technologies, a subsidiary of defense and civilian contractor Raytheon Company. While at Raytheon BBN, Natarajan launched the company’s computer vision, human social-cultural behavior modeling, and document image-processing business lines.

Natarajan is on leave from his position as senior vice dean of engineering at the USC Viterbi School of Engineering. He also is the founding executive director of the USC Computing Forum.

The IEEE also elevated Amazon principal research scientist Sherief Reda to IEEE fellow for “contributions to energy-efficient and approximate computing.”

Sherief Reda
Sherief Reda

Reda’s research interests center around computer design optimizations, with focus on energy-efficient computing, electronic design automation of integrated circuits, embedded systems, and computer architecture.

He joined Amazon as a principal research scientist in July of 2021, working on optimization methods for supply chain systems. Amazon’s Supply Chain Optimization Technology (SCOT) team works on complex supply chain issues at the scale that Amazon requires.

After earning his PhD in computer science and engineering from the University of California, San Diego in 2006, Reda joined the faculty at Brown University. There he is a full professor of Engineering and of Computer Science. In addition, he leads Brown’s SCALable Energy-Efficient Computing Systems (SCALE) Laboratory. He has more than 135 publications, holds five US patents and has been a principal investigator (PI) or co-PI on more than $21 million worth of funded projects from federal agencies and industry.

John Preskill named to White House National Quantum Initiative Advisory Committee

John Preskill, the Richard P. Feynman Professor of Theoretical Physics at the California Institute of Technology and an Amazon Scholar, was named as a member of the National Quantum Initiative Advisory Committee (NQIAC). He will be providing assessments and recommendations for the National Quantum Initiative (NQI) Act.

John Preskill
John Preskill

The NQIAC, which is comprised of leaders in the field from industry, academia, and federal laboratories, is tasked with providing an independent assessment of the NQI Program and to make recommendations for the president, Congress, the National Science and Technology Council (NSTC) Subcommittee on Quantum Information Science, and the NSTC Subcommittee on Economic and Security Implications of Quantum Science when they’re reviewing and revising the NQI Program.

In the announcement, Preskill was cited for research contributions that include “proving security of quantum protocols, proposing and analyzing methods for reliable storage and processing of quantum information, identifying universal properties of quantum entanglement in quantum many-body systems, and applying quantum information theory to quantum gravity and black holes.”

In 2000, he founded Caltech’s Institute for Quantum Information, which is now the Institute for Quantum Information and Matter.

Preskill is a member of the National Academy of Sciences and an American Physical Society fellow.

Preskill joined Amazon Web Service’s quantum computing research effort in June 2020 as an Amazon Scholar.

Related content

IN, KA, Bengaluru
Do you want to join an innovative team of scientists who use machine learning and statistical techniques to create state-of-the-art solutions for providing better value to Amazon’s customers? Do you want to build and deploy advanced ML systems that help optimize millions of transactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data to solve real-world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Machine Learning team for India Consumer Businesses. Machine Learning, Big Data and related quantitative sciences have been strategic to Amazon from the early years. Amazon has been a pioneer in areas such as recommendation engines, ecommerce fraud detection and large-scale optimization of fulfillment center operations. As Amazon has rapidly grown and diversified, the opportunity for applying machine learning has exploded. We have a very broad collection of practical problems where machine learning systems can dramatically improve the customer experience, reduce cost, and drive speed and automation. These include product bundle recommendations for millions of products, safeguarding financial transactions across by building the risk models, improving catalog quality via extracting product attribute values from structured/unstructured data for millions of products, enhancing address quality by powering customer suggestions We are developing state-of-the-art machine learning solutions to accelerate the Amazon India growth story. Amazon India is an exciting place to be at for a machine learning practitioner. We have the eagerness of a fresh startup to absorb machine learning solutions, and the scale of a mature firm to help support their development at the same time. As part of the India Machine Learning team, you will get to work alongside brilliant minds motivated to solve real-world machine learning problems that make a difference to millions of our customers. We encourage thought leadership and blue ocean thinking in ML. Key job responsibilities Use machine learning and analytical techniques to create scalable solutions for business problems Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes Design, develop, evaluate and deploy, innovative and highly scalable ML models Work closely with software engineering teams to drive real-time model implementations Work closely with business partners to identify problems and propose machine learning solutions Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model maintenance Work proactively with engineering teams and product managers to evangelize new algorithms and drive the implementation of large-scale complex ML models in production Leading projects and mentoring other scientists, engineers in the use of ML techniques About the team International Machine Learning Team is responsible for building novel ML solutions that attack India first (and other Emerging Markets across MENA and LatAm) problems and impact the bottom-line and top-line of India business. Learn more about our team from https://www.amazon.science/working-at-amazon/how-rajeev-rastogis-machine-learning-team-in-india-develops-innovations-for-customers-worldwide
US, WA, Seattle
Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video technologist, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! We are forming a new organization within Prime Video to redefine our operational landscape through the power of artificial intelligence. As a Applied Scientist within this initiative, you will be a technical leader helping to design and build the intelligent systems that power our vision. You will tackle complex and ambiguous problems, designing and delivering scalable and resilient agentic AI and ML solutions from the ground up. You will not only write high-quality, maintainable software and models, but also mentor other scientists, influence our technical strategy, and drive engineering best practices across the team. Your work will directly contribute to making Prime Video's operations more efficient and will set the technical foundation for years to come. We're seeking candidates with strong experience in computer vision and generative AI technologies. In this role, you'll apply cutting-edge techniques in image and video understanding, visual content generation, and multimodal AI systems to transform how Prime Video operates at scale. Key job responsibilities • Lead the design and architecture of highly scalable, available, and resilient services for our AI automation platform. • Write high-quality, maintainable, and robust code to solve complex business problems, building flexible systems without over-engineering. • Act as a technical leader and mentor for other engineers on the team, assisting with career growth and encouraging excellence. • Work through ambiguous requirements, cut through complexity, and translate business needs into scalable technical solutions. • Take ownership of the full software development lifecycle, including design, testing, deployment, and operations. • Work closely with product managers, scientists, and other engineers to build and launch new features and systems. About the team This role offers a unique opportunity to shape the future of one of Amazon's most exciting businesses through the application of AI technologies. If you're passionate about leveraging AI to drive real-world impact at massive scale, we want to hear from you.
ES, B, Barcelona
Are you a scientist passionate about advancing the frontiers of computer vision, machine learning, or large language models? Do you want to work on innovative research projects that lead to innovative products and scientific publications? Would you value access to extensive datasets? If you answer yes to any of these questions, you'll find a great fit at Amazon. We're seeking a hands-on researcher eager to derive, implement, and test the next generation of Generative AI, computer vision, ML, and NLP algorithms. Our research is innovative, multidisciplinary, and far-reaching. We aim to define, deploy, and publish pioneering research that pushes the boundaries of what's possible. To achieve our vision, we think big and tackle complex technological challenges at the forefront of our field. Where technology doesn't exist, we create it. Where it does, we adapt it to function at Amazon's scale. We need team members who are passionate, curious, and willing to learn continuously. Key job responsibilities * Derive novel computer vision and ML models or LLMs/VLMs. * Design and develop scalable ML models. * Create and work with large datasets * Work with large GPU clusters. * Work closely with software engineering teams to deploy your innovations. * Publish your work at major conferences/journals. * Mentor team members in the use of your AI models. A day in the life As a Senior Applied Scientist at Amazon, your typical day might look like this: * Dive into coding, deriving new ML models for computer vision or NLP * Experiment with massive datasets on our GPU clusters * Brainstorm with your team to solve complex AI challenges * Collaborate with engineers to turn your research into real products * Write up your findings for publication in top journals or conferences * Mentor junior team members on AI concepts and implementation About the team DiscoVision, a science unit within Amazon's UPMT, focuses on advancing visual content capabilities through state-of-the-art AI technology. Our team specializes in developing state-of-the-art technologies in text-to-image/video Generative AI, 3D modeling, and multimodal Large Language Models (LLMs).
US, WA, Seattle
Are you excited to help customers discover the hottest and best reviewed products? The Discovery Tech team helps customers discover and engage with new, popular and relevant products across Amazon worldwide. We do this by combining technology, science, and innovation to build new customer-facing features and experiences alongside advanced tools for marketers. You will be responsible for creating and building critical services that automatically generate, target, and optimize Amazon’s cross-category marketing and merchandising. Through the enablement of intelligent marketing campaigns that leverage machine-learning models, you will help to deliver the best possible shopping experience for Amazon’s customers all over the globe. We are looking for analytical problem solvers who enjoy diving into data, excited about data science and statistics, can multi-task, and can credibly interface between engineering teams and business stakeholders. Your analytical abilities, business understanding, and technical savvy will be used to identify specific and actionable opportunities to solve existing business problems and look around corners for future opportunities. Your domain spans the design, development, testing, and deployment of data-driven and highly scalable machine learning solutions in product recommendation. As an Applied Scientist, you bring business and industry context to science and technology decisions. You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems, acquiring expertise as needed. You decompose complex problems into straightforward solutions. To know more about Amazon science, please visit https://www.amazon.science
IN, TS, Hyderabad
Do you want to join an innovative team of scientists who leverage machine learning and statistical techniques to revolutionize how businesses discover and purchase products on Amazon? Are you passionate about building intelligent systems that understand and predict complex B2B customer needs? The Amazon Business team is looking for exceptional Applied Science to help shape the future of B2B commerce. Amazon Business is one of Amazon's fastest-growing initiatives focused on serving business customers, from individual professionals to large institutions, with unique and complex purchasing needs. Our customers require sophisticated solutions that go beyond traditional B2C experiences, including bulk purchasing, approval workflows, and business-grade service support. The AB-MSET Applied Science team focuses on building intelligent systems for delivering personalized, contextual service experiences throughout the customer lifecycle. We apply advanced machine learning techniques to develop sophisticated intent detection models for business customer service needs, create intelligent matching algorithms for optimal service routing based on multiple variables including customer value, maturity, effort, and issue complexity, build predictive models to enable proactive service interventions, design recommendation systems for self-service solutions, and develop ML models for automated service resolution. As an Applied Scientist on the team, you will design and develop state-of-the-art ML models for service intent classification, routing optimization, and customer experience personalization. You will analyze large-scale business customer interaction data to identify patterns and opportunities for automation, create scalable solutions for complex B2B service scenarios using advanced ML techniques, and work closely with engineering teams to implement and deploy models in production. You will collaborate with business stakeholders to identify opportunities for ML applications, establish automated processes for model development, validation, and maintenance, lead research initiatives to advance the state-of-the-art in B2B service science, and mentor other scientists and engineers in applying ML techniques to business problems.
US, WA, Seattle
We are seeking a Principal Applied Scientist to lead research and development in automated reasoning, formal verification, and program analysis. You will drive innovation in making formal methods practical and accessible for real-world systems at cloud scale. Key job responsibilities - Lead research initiatives in automated reasoning, formal verification, SMT solving, model checking, or program analysis - Design and implement novel algorithms and techniques that advance the state of the art - Mentor and guide applied scientists, research scientists, and engineers - Collaborate with product teams to transition research into production systems - Define technical vision and strategy for automated reasoning initiatives - Represent AWS in the academic and research community - Drive cross-organizational impact through technical leadership About the team The Automated Reasoning Group at AWS develops and applies cutting-edge formal methods and automated reasoning techniques to ensure the security, reliability, and correctness of AWS services and customer applications. Our work innovates tools and services to perform verification at scale and apply them to build safe and secure systems at AWS. We are also pioneering the use of formal verification and automated reasoning to develop agentic systems, ensuring AI agents operate within defined safety boundaries.
US, WA, Bellevue
As an Applied Scientist on our Central Learning Solutions Team, you will play a critical role in driving the design, development, and delivery of learning programs and initiatives aimed at enhancing leadership and associate development within the organization. You will leverage your expertise in learning science, data analysis, and statistical model design to create impactful learning journey roadmap that align with organizational goals and priorities. Key job responsibilities Research and Analysis: - Conduct research on learning and development trends, theories, and best practices related to leadership and associate development - Analyze data to identify learning needs, performance gaps, and opportunities for improvement within the organization. - Use data-driven insights to inform the design and implementation of learning interventions. Program Design and Development: - Collaborate with cross-functional teams to develop comprehensive learning programs focused on leadership development and associate growth - Design learning experiences using evidence-based instructional strategies, adult learning principles, and innovative technologies. - Create engaging and interactive learning materials, including e-learning modules, instructor-led workshops, and multimedia resources. Evaluation and Continuous Improvement: - Develop evaluation frameworks to assess the effectiveness and impact of learning programs on leadership development and associate performance - Collect and analyze feedback from participants and stakeholders to identify strengths, areas for improvement, and future learning needs. - Iterate on learning interventions based on evaluation results and feedback to continuously improve program outcomes Thought Leadership and Collaboration: - Serve as a subject matter expert on learning science, instructional design, and leadership development within the organization - Collaborate with stakeholders across the company to align learning initiatives with strategic priorities and business objectives - Share knowledge and best practices with colleagues to foster a culture of continuous learning and development.
US, WA, Bellevue
Amazon Leo is an initiative to increase global broadband access through a constellation of 3,236 satellites in low Earth orbit (LEO). Its mission is to bring fast, affordable broadband to unserved and underserved communities around the world. Amazon Leo will help close the digital divide by delivering fast, affordable broadband to a wide range of customers, including consumers, businesses, government agencies, and other organizations operating in places without reliable connectivity. Do you get excited by aerospace, space exploration, and/or satellites? Do you want to help build solutions at Amazon Leo to transform the space industry? If so, then we would love to talk! Key job responsibilities Work cross-functionally with product, business development, and various technical teams (engineering, science, simulations, etc.) to execute on the long-term vision, strategy, and architecture for the science-based global demand forecast. Design and deliver modern, flexible, scalable solutions to integrate data from a variety of sources and systems (both internal and external) and develop Bandwidth Usage models at granular temporal and geographic grains, deployable to Leo traffic management systems. Work closely with the capacity planning science team to ensure that demand forecasts feed seamlessly into their systems to deliver continuous optimization of resources. Lead short and long terms technical roadmap definition efforts to deliver solutions that meet business needs in pre-launch, early-launch, and mature business phases. Synthesize and communicate insights and recommendations to audiences of varying levels of technical sophistication to drive change across Amazon Leo. Export Control Requirement: Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum. About the team The Amazon Leo Global Demand Planning team's mission is to map customer demand across space and time. We enable Amazon Leo's long-term success by delivering actionable insights and scientific forecasts across geographies and customer segments to empower long range planning, capacity simulations, business strategy, and hardware manufacturing recommendations through scalable tools and durable mechanisms.
US, CA, Pasadena
Do you enjoy solving challenging problems and driving innovations in research? As a Research Science intern with the Quantum Algorithms Team at CQC, you will work alongside global experts to develop novel quantum algorithms, evaluate prospective applications of fault-tolerant quantum computers, and strengthen the long-term value proposition of quantum computing. A strong candidate will have experience applying methods of mathematical and numerical analysis to assess the performance of quantum algorithms and establish their advantage over classical algorithms. Key job responsibilities We are particularly interested in candidates with expertise in any of the following subareas related to quantum algorithms: quantum chemistry, many-body physics, quantum machine learning, cryptography, optimization theory, quantum complexity theory, quantum error correction & fault tolerance, quantum sensing, and scientific computing, among others. A day in the life Throughout your journey, you'll have access to unparalleled resources, including state-of-the-art computing infrastructure, cutting-edge research papers, and mentorship from industry luminaries. This immersive experience will not only sharpen your technical skills but also cultivate your ability to think critically, communicate effectively, and thrive in a fast-paced, innovative environment where bold ideas are celebrated. 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. Hybrid Work We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices. This is not a remote internship opportunity. About the team Amazon Web Services (AWS) Center for Quantum Computing (CQC) is a multi-disciplinary team of theoretical and experimental physicists, materials scientists, and hardware and software engineers on a mission to develop a fault-tolerant quantum computer.
US, CA, Pasadena
We’re on the lookout for the curious, those who think big and want to define the world of tomorrow. At Amazon, you will grow into the high impact, visionary person you know you’re ready to be. Every day will be filled with exciting new challenges, 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. The Amazon Web Services (AWS) Center for Quantum Computing (CQC) in Pasadena, CA, is looking for a Quantum Research Scientist Intern in the Device and Architecture Theory group. You will be joining a multi-disciplinary team of scientists, engineers, and technicians, all working at the forefront of quantum computing to innovate for the benefit of our customers. Key job responsibilities As an intern with the Device and Architecture Theory team, you will conduct pathfinding theoretical research to inform the development of next-generation quantum processors. Potential focus areas include device physics of superconducting circuits, novel qubits and gate schemes, and physical implementations of error-correcting codes. You will work closely with both theorists and experimentalists to explore these directions. We are looking for candidates with excellent problem-solving and communication skills who are eager to work collaboratively in a team environment. Amazon Science gives you insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in quantum computing and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work. A day in the life 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. 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. Within AWS UC, Amazon Dedicated Cloud (ADC) roles engage with AWS customers who require specialized security solutions for their cloud services. 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. 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. 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. Export Control Requirement: Due to applicable export control laws and regulations, candidates must be either a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum, or be able to obtain a US export license. If you are unsure if you meet these requirements, please apply and Amazon will review your application for eligibility.