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.

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Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the next-level. We focus on creating entirely new products and services with a goal of positively impacting the lives of our customers. No industries or subject areas are out of bounds. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have thirteen employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We are constantly learning through programs that are local, regional, and global. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. Key job responsibilities * Partner with laboratory science teams on design and analysis of experiments * Originate and lead the development of new data collection workflows with cross-functional partners * Develop and deploy scalable bioinformatics analysis and QC workflows * Evaluate and incorporate novel bioinformatic approaches to solve critical business problems About the team Our team highly values work-life balance, mentorship and career growth. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We care about your career growth and strive to assign projects and offer training that will challenge you to become your best.
US, WA, Seattle
Join the Worldwide Sustainability (WWS) organization where we capitalize on our size, scale, and inventive culture to build a more resilient and sustainable company. WWS manages our social and environmental impacts globally, driving solutions that enable our customers, businesses, and the world around us to become more sustainable. Sustainability Science and Innovation is a multi-disciplinary team within the WW Sustainability organization that combines science, analytics, economics, statistics, machine learning, product development, and engineering expertise to identify, evaluate and/or develop new science, technologies, and innovations that aim to address long-term sustainability challenges. We are looking for a Sr. Research Scientist to help us develop and drive innovative scientific solutions that will improve the sustainability of materials in our products, packaging, operations, and infrastructure. You will be at the forefront of exploring and resolving complex sustainability issues, bringing innovative ideas to the table, and making meaningful contributions to projects across SSI’s portfolio. This role not only demands technical expertise but also a strategic mindset and the agility to adapt to evolving sustainability challenges through self-driven learning and exploration. In this role, you will leverage your breadth of expertise in AI models and methodologies and industrial research experience to build scientific tools that inform sustainability strategies related to materials and energy. The successful applicant will lead by example, pioneering science-vetted data-driven approaches, and working collaboratively to implement strategies that align with Amazon’s long-term sustainability vision. Key job responsibilities - Develop scientific models that help solve complex and ambiguous sustainability problems, and extract strategic learnings from large datasets. - Work closely with applied scientists and software engineers to implement your scientific models. - Support early-stage strategic sustainability initiatives and effectively learn from, collaborate with, and influence stakeholders to scale-up high-value initiatives. - Support research and development of cross-cutting technologies for industrial decarbonization, including building the data foundation and analytics for new AI models. - Drive innovation in key focus areas including packaging materials, building materials, and alternative fuels. About the team Diverse Experiences: World Wide Sustainability (WWS) 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. Inclusive Team Culture: 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 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 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
We are a passionate team applying the latest advances in technology to solve real-world challenges. As a Data Scientist working at the intersection of machine learning and advanced analytics, you will help develop innovative products that enhance customer experiences. Our team values intellectual curiosity while maintaining sharp focus on bringing products to market. Successful candidates demonstrate responsiveness, adaptability, and thrive in our open, collaborative, entrepreneurial environment. Working at the forefront of both academic and applied research, you will join a diverse team of scientists, engineers, and product managers to solve complex business and technology problems using scientific approaches. You will collaborate closely with other teams to implement innovative solutions and drive improvements. At Amazon, we cultivate an inclusive culture through our Leadership Principles, which emphasize seeking diverse perspectives, continuous learning, and building trust. Our global community includes thirteen employee-led affinity groups with 40,000 members across 190 chapters, showcasing our commitment to embracing differences and fostering continuous learning through local, regional, and global programs. We prioritize work-life balance, recognizing it as fundamental to long-term happiness and fulfillment. Our team is committed to supporting your career development through challenging projects, mentorship opportunities, and targeted training programs that help you reach your full potential. Key job responsibilities Key job responsibilities * Deliver data analyses that optimize overall team process and guide decision-making * Deep dive to understand source of anomalies across a variety of datasets including low-level sequencing read data * Identify key metrics that are drivers to achieve team goals; work with senior stakeholders to refine your results * Use modern statistical methods to highlight insights for predictive & generative ML models and assay process * Perform correlation analysis, significance testing, and simulation on high- and low-fidelity datasets for various types of readouts * Generate reports with tables and visualization that support operational cycle analysis and one-off POC experiments * Collaborate with multi-disciplinary domain experts to support your findings and their experiments * Write well-tested scripts that can be promoted by our software teams to production pipelines * Learn about new statistical methods for our domain and adopt them in your work * Work fluently in SQL and Python. Be skilled in generating compelling visualizations. A day in the life New data has just landed and promoted to our datalake. You load the data and verify it's overall integrity by visualizing variation across target subsets. You realize we may have made progress toward our goals and begin to test the validity of your nominal results. At midday you grab lunch with new coworkers and learn about their fields or weird interests (there are many). You generate visualizations for the entire dataset and perform significance tests that reinforce specific findings. You meet with peers in the afternoon to discuss your findings and breakdown the remaining tasks to finalize your group report! About the team Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the limits. We focus on creating entirely new products and services with a goal of positively impacting the lives of our customers. No industries or subject areas are out of bounds. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you.
GB, MLN, Edinburgh
Do you want a role with deep meaning and the ability to make a major impact? As part of Intelligent Talent Acquisition (ITA), you'll have the opportunity to reinvent the hiring process and deliver unprecedented scale, sophistication, and accuracy for Amazon Talent Acquisition operations. ITA is an industry-leading people science and technology organization made up of scientists, engineers, analysts, product professionals and more, all with the shared goal of connecting the right people to the right jobs in a way that is fair and precise. Last year we delivered over 6 million online candidate assessments, and helped Amazon deliver billions of packages around the world by making it possible to hire hundreds of thousands of workers in the right quantity, at the right location and at exactly the right time. You’ll work on state-of-the-art research, advanced software tools, new AI systems, and machine learning algorithms, leveraging Amazon's in-house tech stack to bring innovative solutions to life. Join ITA in using technologies to transform the hiring landscape and make a meaningful difference in people's lives. Together, we can solve the world's toughest hiring problems. A day in the life As a Research Scientist, you will partner on design and development of AI-powered systems to scale job analyses enterprise-wide, match potential candidates to the jobs they’ll be most successful in, and conduct validation research for top-of-funnel AI-based evaluation tools. You’ll have the opportunity to develop and implement novel research strategies using the latest technology and to build solutions while experiencing Amazon’s customer-focused culture. The ideal scientist must have the ability to work with diverse groups of people and inter-disciplinary cross-functional teams to solve complex business problems. About the team The Lead Generation & Detection Services (LEGENDS) organization is a specialized organization focused on developing AI-driven solutions to enable fair and efficient talent acquisition processes across Amazon. Our work encompasses capabilities across the entire talent acquisition lifecycle, including role creation, recruitment strategy, sourcing, candidate evaluation, and talent deployment. The focus is on utilizing state-of-the-art solutions using Deep Learning, Generative AI, and Large Language Models (LLMs) for recruitment at scale that can support immediate hiring needs as well as longer-term workforce planning for corporate roles. We maintain a portfolio of capabilities such as job-person matching, person screening, duplicate profile detection, and automated applicant evaluation, as well as a foundational competency capability used throughout Amazon to help standardize the assessment of talent interested in Amazon.
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 robotics dexterous hands that: - Enable unprecedented generalization across diverse tasks - Are compliant but at the same time impact resistant - Can enable power grasps with the same reliability as fine dexterity and nonprehensile manipulation - Can naturally cope with the uncertainty of the environment - 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 novel sensing and actuation technologies for dexterous manipulation - Develop parallel paths for rapid finger design and prototyping combining different actuation and sensing technologies as well as different finger morphologies - Develop new testing and validation strategies to support fast continuous integration and modularity - Build and test full hand prototypes to validate the performance of the solution - Create hybrid approaches combining different actuation technologies, under-actuation, active and passive compliance - Hand integration into rest of the embodiment - Partner with cross-functional teams to rapidly create new concepts and prototypes - Work with Amazon's robotics engineering and operations teams to grasp their requirements and develop tailored solutions - Document the designs, performance, and validation of the final system