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

US, CA, San Francisco
Amazon’s Frontier AI & Robotics (FAR) team is seeking a Member of Technical Staff to drive foundational research and build intelligent robotic systems from the ground up. In this role, you will operate at the intersection of innovative AI research and real-world robotics - conducting original research, publishing, and deploying your innovations into production systems at Amazon scale. We’re looking for researchers who think from first principles, push the boundaries of what’s possible, and take full ownership of turning breakthrough ideas into working systems. You will join the next revolution in robotics, where you'll work alongside world-renowned AI pioneers to push the boundaries of what's possible in robotic intelligence. As a Member of Technical Staff, you'll develop breakthrough foundation models that enable robots to perceive, understand, and interact with the physical world in unprecedented ways—with a strong emphasis on the hardware systems that bring these models to life. You'll drive independent research initiatives in areas such as locomotion, manipulation, motor control, actuator design, sim2real transfer, and multi-modal robot learning, designing novel frameworks that bridge state-of-the-art research with real-world hardware deployment at Amazon scale. In this role, you'll balance innovative technical exploration with hands-on hardware implementation, collaborating with mechanical, electrical, and controls engineering teams to ensure your models and algorithms perform robustly on physical robotic platforms in dynamic real-world environments. You'll have access to Amazon's computational resources and advanced robotics infrastructure—including high degree-of-freedom prototype platforms, custom actuators, and precision sensing systems—enabling you to tackle ambitious problems in areas like multi-modal robotic foundation models, motor-level control optimization, and efficient model architectures that scale across diverse robotic hardware. Key job responsibilities · Drive independent research initiatives across the full robotics stack, including robot co-design, manipulation mechanisms, innovative actuation and motor control strategies, state estimation, low-level control, system identification, reinforcement learning, and sim-to-real transfer, as well as foundation models for perception and manipulation · Lead full-stack robotics projects from conceptualization through hardware deployment, taking a system-level approach that integrates actuator dynamics, sensor feedback (force/torque, IMUs, encoders), and electromechanical constraints with algorithmic development · Develop and optimize control algorithms and sensing pipelines for physical robotic hardware, including motor characterization, actuator performance tuning, and robust sensor integration in production environments · Collaborate with hardware, mechanical, and electrical engineering teams to ensure seamless integration of learned models across the robotics stack—from embedded compute and communication buses to actuator-level control · Contribute to the team's technical strategy and help shape our approach to next-generation hardware-aware robotics challenges, including hardware-in-the-loop validation and prototype-to-deployment transitions A day in the life · Design and implement innovative systems and algorithms, leveraging our extensive computational and robotics hardware infrastructure to prototype and evaluate at scale · Collaborate with hardware and software engineers to solve complex technical challenges spanning motors, actuators, sensors, and learned control · Lead technical initiatives from conception to hardware deployment, working closely with robotics engineers and lab teams to integrate your solutions into physical robotic platforms · Participate in technical discussions and design reviews with team leaders, hardware engineers, and fellow scientists · Leverage our compute cluster and advanced robotics lab—including high-DoF prototype platforms and custom actuation systems—to rapidly prototype and validate new ideas · Transform theoretical insights into practical solutions that perform reliably on real-world robotic hardware About the team At Frontier AI & Robotics, we're not just advancing robotics – we're reimagining it from the ground up. Our team is building the future of intelligent robotics through ground breaking foundation models and end-to-end learned systems. We tackle some of the most challenging problems in AI and robotics, from developing sophisticated perception systems to creating adaptive manipulation strategies that work in complex, real-world scenarios. What sets us apart is our unique combination of ambitious research vision and practical impact. We leverage Amazon's massive computational infrastructure and rich real-world datasets to train and deploy state-of-the-art foundation models. Our work spans the full spectrum of robotics intelligence – from multimodal perception using images, videos, and sensor data, to sophisticated manipulation strategies that can handle diverse real-world scenarios. We're building systems that don't just work in the lab, but scale to meet the demands of Amazon's global operations. Join us if you're excited about pushing the boundaries of what's possible in robotics, working with world-class researchers, and seeing your innovations deployed at unprecedented scale.
GB, Virtual Location - Uk
Amazon Integrated Security is seeking a Principal Applied Scientist to lead research at the intersection of cognitive psychology, measurement science, and AI security. This role will pioneer new approaches to understanding and leveraging behavioral characteristics of autonomous AI systems in security contexts, turning threat actor use of AI into a structural advantage for defenders. Key job responsibilities Establish and lead a novel research program exploring cognitive patterns and biases in agentic AI systems used for offensive security purposes. Design and conduct experiments to understand black-box AI system behavior, develop measurement frameworks for previously unmeasurable security concepts, and translate research findings into actionable defensive strategies and tooling. Create feedback loops between offensive and defensive security teams, collaborate with threat intelligence experts and red team operations, and publish findings that advance both academic understanding and practical security outcomes. Apply measurement science expertise to quantify complex security concepts including risk, business impact, and trust. A day in the life Work closely with a Principal Technologist with AI and security expertise, senior security engineers with threat intelligence backgrounds, offensive AI security teams, and detection/response operations. Mentor junior scientists and engineers while maintaining strong connections with academic research communities.
US, NY, New York
We are seeking a Sr. Applied Scientist to develop cutting-edge machine learning algorithms for motor control systems in robots. In this role, you will focus on creating and optimizing intelligent motor control strategies to enable robots to perform complex, whole-body tasks. Your contributions will be essential in advancing robotics by enabling fluid, reliable, and safe interactions between robots and their environments. Key job responsibilities - Develop controllers that leverage reinforcement learning, imitation learning, or other advanced AI techniques to achieve natural, robust, and adaptive motor behaviors - Collaborate with multi-disciplinary teams to integrate motor control systems with robotic hardware, ensuring alignment with real-world constraints such as actuator dynamics and energy efficiency - Use simulation and real-world testing to refine and validate control algorithms - Stay updated on advancements in robotics, AI, and control systems to apply advanced techniques to robotic motion challenges - Lead technical projects from conception through production deployment - Mentor junior scientists and engineers - Bridge research initiatives with practical engineering implementation About the team Fauna Robotics, an Amazon company, is building capable, safe, and genuinely delightful robots for everyday life. Our goal is simple: make robots people actually want to live and interact with in everyday human spaces. We believe that future won’t arrive until building for robotics becomes far more accessible. Today, too much effort is spent reinventing the fundamentals. We’re changing that by developing tightly integrated hardware and software systems that make it faster, safer, and more intuitive to create real-world robotic products. Our work spans the full stack: mechanical design, control systems, dynamic modeling, and intelligent software. The focus is not just functionality, but experience. We’re building robots that feel responsive, expressive, and genuinely useful. At Fauna, you’ll work at the frontier of this space, helping define how robots move, manipulate, and interact with people in natural environments. It’s an opportunity to solve hard problems across hardware and software with a team focused on making robotics accessible and joyful to build. If you care about making robotics real for everyone and building systems that are as delightful as they are capable, we’re interested in hearing from you. an opportunity to solve hard problems across hardware and software with a team focused on making robotics accessible and joyful to build. If you care about making robotics real for everyone and building systems that are as delightful as they are capable, we’re interested in hearing from you.
US, NY, New York
We are seeking an Applied Scientist to lead the development of evaluation frameworks and data collection protocols for robotic capabilities. In this role, you will focus on designing how we measure, stress-test, and improve robot behavior across a wide range of real-world tasks. Your work will play a critical role in shaping how policies are validated and how high-quality datasets are generated to accelerate system performance. You will operate at the intersection of robotics, machine learning, and human-in-the-loop systems, building the infrastructure and methodologies that connect teleoperation, evaluation, and learning. This includes developing evaluation policies, defining task structures, and contributing to operator-facing interfaces that enable scalable and reliable data collection. The ideal candidate is highly experimental, systems-oriented, and comfortable working across software, robotics, and data pipelines, with a strong focus on turning ambiguous capability goals into measurable and actionable evaluation systems. Key job responsibilities - Design and implement evaluation frameworks to measure robot capabilities across structured tasks, edge cases, and real-world scenarios - Develop task definitions, success criteria, and benchmarking methodologies that enable consistent and reproducible evaluation of policies - Create and refine data collection protocols that generate high-quality, task-relevant datasets aligned with model development needs - Build and iterate on teleoperation workflows and operator interfaces to support efficient, reliable, and scalable data collection - Analyze evaluation results and collected data to identify performance gaps, failure modes, and opportunities for targeted data collection - Collaborate with engineering teams to integrate evaluation tooling, logging systems, and data pipelines into the broader robotics stack - Stay current with advances in robotics, evaluation methodologies, and human-in-the-loop learning to continuously improve internal approaches - Lead technical projects from conception through production deployment - Mentor junior scientists and engineers About the team Fauna Robotics, an Amazon company, is building capable, safe, and genuinely delightful robots for everyday life. Our goal is simple: make robots people actually want to live and interact with in everyday human spaces. We believe that future won’t arrive until building for robotics becomes far more accessible. Today, too much effort is spent reinventing the fundamentals. We’re changing that by developing tightly integrated hardware and software systems that make it faster, safer, and more intuitive to create real-world robotic products. Our work spans the full stack: mechanical design, control systems, dynamic modeling, and intelligent software. The focus is not just functionality, but experience. We’re building robots that feel responsive, expressive, and genuinely useful. At Fauna, you’ll work at the frontier of this space, helping define how robots move, manipulate, and interact with people in natural environments. It’s an opportunity to solve hard problems across hardware and software with a team focused on making robotics accessible and joyful to build. If you care about making robotics real for everyone and building systems that are as delightful as they are capable, we’re interested in hearing from you.
US, NY, New York
We are seeking a Robotics/AI Motor Control Scientist to develop cutting-edge machine learning algorithms for motor control systems in robots. In this role, you will focus on creating and optimizing intelligent motor control strategies to enable robots to perform complex, whole-body tasks. Your contributions will be essential in advancing robotics by enabling fluid, reliable, and safe interactions between robots and their environments. Key job responsibilities - Develop controllers that leverage reinforcement learning, imitation learning, or other advanced AI techniques to achieve natural, robust, and adaptive motor behaviors - Collaborate with multi-disciplinary teams to integrate motor control systems with robotic hardware, ensuring alignment with real-world constraints such as actuator dynamics and energy efficiency - Use simulation and real-world testing to refine and validate control algorithms - Stay updated on advancements in robotics, AI, and control systems to apply advanced techniques to robotic motion challenges - Lead technical projects from conception through production deployment - Mentor junior scientists and engineers - Bridge research initiatives with practical engineering implementation About the team Fauna Robotics, an Amazon company, is building capable, safe, and genuinely delightful robots for everyday life. Our goal is simple: make robots people actually want to live and interact with in everyday human spaces. We believe that future won’t arrive until building for robotics becomes far more accessible. Today, too much effort is spent reinventing the fundamentals. We’re changing that by developing tightly integrated hardware and software systems that make it faster, safer, and more intuitive to create real-world robotic products. Our work spans the full stack: mechanical design, control systems, dynamic modeling, and intelligent software. The focus is not just functionality, but experience. We’re building robots that feel responsive, expressive, and genuinely useful. At Fauna, you’ll work at the frontier of this space, helping define how robots move, manipulate, and interact with people in natural environments. It’s an opportunity to solve hard problems across hardware and software with a team focused on making robotics accessible and joyful to build. If you care about making robotics real for everyone and building systems that are as delightful as they are capable, we’re interested in hearing from you. an opportunity to solve hard problems across hardware and software with a team focused on making robotics accessible and joyful to build. If you care about making robotics real for everyone and building systems that are as delightful as they are capable, we’re interested in hearing from you.
AU, VIC, Melbourne
Are you excited about leveraging state-of-the-art Computer Vision algorithms and large datasets to solve real-world problems? Join Amazon as an Applied Scientist Intern and be at the forefront of AI innovation! As an Applied Scientist Intern, you'll work in a fast-paced, cross-disciplinary team of pioneering researchers. You'll tackle complex problems, developing solutions that either build on existing academic and industrial research or stem from your own innovative thinking. Your work may even find its way into customer-facing products, making a real-world impact. Key job responsibilities - Develop novel solutions and build prototypes - Work on complex problems in Computer Vision and Machine Learning - Contribute to research that could significantly impact Amazon's operations - Collaborate with a diverse team of experts in a fast-paced environment - Collaborate with scientists on writing and submitting papers to Tier-1 conferences (e.g., CVPR, ICCV, NeurIPS, ICML) - Present your research findings to both technical and non-technical audiences Key Opportunities: - Collaborate with leading machine learning researchers - Access innovative tools and hardware (large GPU clusters) - Address challenges at an unparalleled scale - Become a disruptor, innovator, and problem solver in the field of computer vision - Potentially deliver solutions to production in customer-facing applications - Opportunities to become an FTE after the internship Join us in shaping the future of AI at Amazon. Apply now and turn your research into real-world solutions!
US, WA, Seattle
The Alexa for Shopping team is seeking a customer-obsessed senior economist to own and drive analytics strategy for GenAI-powered Shopping experiences. This role will partner closely with senior leaders to deliver high-quality insights that inform executive decision-making for the AI shopping assistant, Rufus. The successful candidate will demonstrate strong attention to detail, excellent written and verbal communication, and the ability to influence across organizations. In this role, you will mentor and set the bar for data science, economics, and engineering partners by establishing best practices for understanding customer behavior in AI-driven shopping experiences. You will invent and scale metrics that measure customer adoption and habituation, and build agentic, automated analytical workflows that enable fast, repeatable deep dives. This position will play a critical role in shaping product roadmap and investment decisions in a rapidly evolving GenAI space. The ideal candidate will operate effectively in ambiguous environments, exercise strong business judgment on high-impact, one-way door decisions, and continuously raise the bar for analytical rigor and operational excellence. You will work cross-functionally with product, engineering, and economics partners to deliver results for customers Key job responsibilities - Own the development of customer and shopping-mission cohorts to understand behavior with and without Rufus engagement across the end-to-end shopping journey. - Identify which Rufus query types and interaction patterns drive the most customer value for specific customer cohorts and shopping missions. - Build predictive models to estimate customer re-engagement and long-term adoption of Rufus based on interaction quality and downstream shopping outcomes. - Invent, operationalize, and publish scalable metrics and dashboards that surface actionable insights, enabling data-driven product growth and executive decision-making. - Partner closely with Product, Engineering, and Economics teams to translate analytical insights into roadmap priorities and customer-focused improvements. About the team The Alexa for Shopping economics team focuses on understanding how GenAI-powered shopping tools are transforming customer behavior across the shopping lifecycle - from inspiration and problem-solving, to product research, selection, purchase, and post-purchase support. We build the foundational measurement frameworks that enable teams to evaluate performance, identify what Rufus experiences resonate most with customers, and uncover opportunities for improvement. Our work directly influences customer-centric product roadmap decisions and helps scale impactful, high-quality AI shopping experiences
US, CA, San Francisco
Amazon’s Frontier AI & Robotics (FAR) team is seeking a Member of Technical Staff to drive foundational research and build intelligent robotic systems from the ground up. In this role, you will operate at the intersection of cutting-edge AI research and real-world robotics - conducting original research, publishing, and deploying your innovations into production systems at Amazon scale. We’re looking for researchers who think from first principles, push the boundaries of what’s possible, and take full ownership of turning breakthrough ideas into working systems.  You will join the next revolution in robotics, where you'll work alongside world-renowned AI pioneers to push the boundaries of what's possible in robotic intelligence. As a Member of Technical Staff, you'll be at the forefront of developing breakthrough foundation models and full-stack robotics systems that enable robots to perceive, understand, and interact with the world in unprecedented ways. You'll drive technical excellence and independent research initiatives in areas such as locomotion, manipulation, perception, sim2real transfer, multi-modal, multi-task robot learning, designing novel frameworks that bridge the gap between state-of-the-art research and real-world deployment at Amazon scale. In this role, you'll balance innovative technical exploration with practical implementation, collaborating with platform teams to ensure your models and algorithms perform robustly in dynamic real-world environments. You’ll have the freedom to pursue ambitious research directions while leveraging Amazon’s vast computational resources to tackle ambiguous problems in areas like very large multi-modal robotic foundation models and efficient, promptable model architectures that can scale across diverse robotic applications. Key job responsibilities - Drive independent research initiatives across the robotics stack, driving breakthrough approaches through hands-on research and development in areas including robot co-design, dexterous manipulation mechanisms, innovative actuation strategies, state estimation, low-level control, system identification, reinforcement learning, sim-to-real transfer, as well as foundation models focusing on breakthrough approaches in perception, and manipulation. - Lead and Guide technical direction for full-stack robotics projects from conceptualization through deployment, taking a system-level approach that integrates hardware considerations with algorithmic development - Develop and optimize control algorithms and sensing pipelines that enable robust performance in production environments - Collaborate with platform and hardware teams to ensure seamless integration across the entire robotics stack, optimizing and scaling models for real-world applications - Contribute to team's technical decisions and influence implementation strategies to help shape our approach to next-generation robotics challenges - Mentor fellow researchers while maintaining solid individual technical contributions A day in the life - Design and implement novel foundation model architectures and innovative systems and algorithms, leveraging our extensive infrastructure to prototype and evaluate at scale - Collaborate with our world-class research team to solve complex technical challenges across the full robotics stack - Lead focused technical initiatives from conception through deployment, ensuring successful integration with production systems - Drive technical discussions and brainstorming sessions with team leaders, fellow researchers and key stakeholders - Conduct experiments and prototype new ideas using our massive compute cluster and extensive robotics infrastructure - Transform theoretical insights into practical solutions that can handle the complexities of real-world robotics applications About the team At Frontier AI & Robotics, we're not just advancing robotics – we're reimagining it from the ground up. Our team is building the future of intelligent robotics through innovative foundation models and end-to-end learned systems. We tackle some of the most challenging problems in AI and robotics, from developing sophisticated perception systems to creating adaptive manipulation strategies that work in complex, real-world scenarios. What sets us apart is our unique combination of ambitious research vision and practical impact. We leverage Amazon's massive computational infrastructure and rich real-world datasets to train and deploy state-of-the-art foundation models. Our work spans the full spectrum of robotics intelligence – from multimodal perception using images, videos, and sensor data, to sophisticated manipulation strategies that can handle diverse real-world scenarios. We're building systems that don't just work in the lab, but scale to meet the demands of Amazon's global operations. Join us if you're excited about pushing the boundaries of what's possible in robotics, working with world-class researchers, and seeing your innovations deployed at unprecedented scale.
US, CA, San Francisco
Amazon’s Frontier AI & Robotics (FAR) team is seeking a Member of Technical Staff to drive foundational research and build intelligent robotic systems from the ground up. In this role, you will operate at the intersection of cutting-edge AI research and real-world robotics - conducting original research, publishing, and deploying your innovations into production systems at Amazon scale. We’re looking for researchers who think from first principles, push the boundaries of what’s possible, and take full ownership of turning breakthrough ideas into working systems.  You will join the next revolution in robotics, where you'll work alongside world-renowned AI pioneers to push the boundaries of what's possible in robotic intelligence. As a Member of Technical Staff, you'll be at the forefront of developing breakthrough foundation models and full-stack robotics systems that enable robots to perceive, understand, and interact with the world in unprecedented ways. You'll drive technical excellence and independent research initiatives in areas such as locomotion, manipulation, perception, sim2real transfer, multi-modal, multi-task robot learning, designing novel frameworks that bridge the gap between state-of-the-art research and real-world deployment at Amazon scale. In this role, you'll balance innovative technical exploration with practical implementation, collaborating with platform teams to ensure your models and algorithms perform robustly in dynamic real-world environments. You’ll have the freedom to pursue ambitious research directions while leveraging Amazon’s vast computational resources to tackle ambiguous problems in areas like very large multi-modal robotic foundation models and efficient, promptable model architectures that can scale across diverse robotic applications. Key job responsibilities - Drive independent research initiatives across the robotics stack, including robot co-design, dexterous manipulation mechanisms, innovative actuation strategies, state estimation, low-level control, system identification, reinforcement learning, sim-to-real transfer, as well as foundation models focusing on breakthrough approaches in perception, and manipulation, for example open-vocabulary panoptic scene understanding, scaling up multi-modal LLMs, sim2real/real2sim techniques, end-to-end vision-language-action models, efficient model inference, video tokenization - Design and implement novel deep learning architectures that push the boundaries of what robots can understand and accomplish - Guide technical direction for full-stack robotics projects from conceptualization through deployment, taking a system-level approach that integrates hardware considerations with algorithmic development, ensuring robust performance in production environments - Collaborate with platform and hardware teams to ensure seamless integration across the entire robotics stack, optimizing and scaling models for real-world applications - Contribute to team's technical decisions and influence implementation strategies to help shape our approach to next-generation robotics challenges - Mentor fellow researchers while maintaining solid individual technical contributions A day in the life - Design and implement novel foundation model architectures and innovative systems and algorithms, leveraging our extensive infrastructure to prototype and evaluate at scale - Collaborate with our world-class research team to solve complex technical challenges across the full robotics stack - Lead focused technical initiatives from conception through deployment, ensuring successful integration with production systems - Drive technical discussions and brainstorming sessions with team leaders, fellow researchers and key stakeholders - Conduct experiments and prototype new ideas using our massive compute cluster and extensive robotics infrastructure - Transform theoretical insights into practical solutions that can handle the complexities of real-world robotics applications About the team At Frontier AI & Robotics, we're not just advancing robotics – we're reimagining it from the ground up. Our team is building the future of intelligent robotics through innovative foundation models and end-to-end learned systems. We tackle some of the most challenging problems in AI and robotics, from developing sophisticated perception systems to creating adaptive manipulation strategies that work in complex, real-world scenarios. What sets us apart is our unique combination of ambitious research vision and practical impact. We leverage Amazon's massive computational infrastructure and rich real-world datasets to train and deploy state-of-the-art foundation models. Our work spans the full spectrum of robotics intelligence – from multimodal perception using images, videos, and sensor data, to sophisticated manipulation strategies that can handle diverse real-world scenarios. We're building systems that don't just work in the lab, but scale to meet the demands of Amazon's global operations. Join us if you're excited about pushing the boundaries of what's possible in robotics, working with world-class researchers, and seeing your innovations deployed at unprecedented scale.
IN, KA, Bengaluru
Amazon is looking for a passionate, talented, and inventive Applied Scientists with machine learning background to help build industry-leading Speech and Language technology. Our mission is to provide a delightful experience to Amazon’s customers by pushing the envelope in Automatic Speech Recognition (ASR), Natural Language Understanding (NLU), Machine Learning (ML) and Computer Vision (CV). Key job responsibilities Amazon is looking for a passionate, talented, and inventive Applied Scientists with machine learning background to help build industry-leading Speech and Language technology. Our mission is to provide a delightful experience to Amazon’s customers by pushing the envelope in Automatic Speech Recognition (ASR), Natural Language Understanding (NLU), Machine Learning (ML) and Computer Vision (CV). As part of our AI team in Amazon AWS, you will work alongside internationally recognized experts to develop novel algorithms and modeling techniques to advance the state-of-the-art in human language technology. Your work will directly impact millions of our customers in the form of products and services that make use of speech and language technology. You will gain hands on experience with Amazon’s heterogeneous speech, text, and structured data sources, and large-scale computing resources to accelerate advances in spoken language understanding. We are hiring in all areas of human language technology: ASR, MT, NLU, text-to-speech (TTS), and Dialog Management, in addition to Computer Vision. We are also looking for talents with experiences/expertise in building large-scale, high-performing systems. A day in the life 0