This year's Day One Amazon Robotics Fellows are, top row, left to right: Omoruyi Atheka, Camille Anne Chungyoun, Asbel Fontanez, Zakar Handricken, Abubakarr Jaye, Christopher LeBlanc, and Janeth Meraz; bottom row, left to right: Jessie Mindel, Naana Obeng-Marnu, Kimberly Llajaruna Peralta, Priscila Rubio, Antonio Sanchez, Augustus ‘ Gus’ Teran, and Walter Williams.
This year's Day One Amazon Robotics Fellows are, top row, left to right: Omoruyi Atheka, Camille Anne Chungyoun, Asbel Fontanez, Zakar Handricken, Abubakarr Jaye, Christopher LeBlanc, and Janeth Meraz; bottom row, left to right: Jessie Mindel, Naana Obeng-Marnu, Kimberly Llajaruna Peralta, Priscila Rubio, Antonio Sanchez, Augustus ‘ Gus’ Teran, and Walter Williams.

Amazon Robotics expands Day One Fellowship Program and selects 14 recipients for 2022

Program empowers Black, Latinx, and Native American students to become industry leaders through scholarship, research, and career opportunities.

Amazon Robotics recently announced fourteen new recipients of the Amazon Robotics Day One Fellowship, a program established to support exceptionally talented students from diverse technical and multicultural backgrounds who are pursuing master of science degrees. The program was developed to support emerging leaders in science from backgrounds underrepresented in STEM, awarding scholarships, mentorship, and career opportunities.

Related content
The fellowships are aimed at helping students from underrepresented backgrounds establish careers in robotics, engineering, computer science, and related fields.

The fellowship program was launched last year with an inaugural class of six recipients across three universities. The program has expanded to support fourteen fellows across seven universities, including Brown University, Boston University, Harvard University, Massachusetts Institute of Technology, Northeastern University, Stanford University, and Worcester Polytechnic Institute.

Recipients receive fully funded fellowships in robotics, engineering, computer science, and related fields that will cover tuition, living expenses, and other costs.

Fellowship recipients also have the opportunity to participate in Amazon Robotics’ internship program. During their summer at Amazon Robotics, the Fellows connect with and receive mentorship from industry experts and members of leadership to gain hands-on experience in their chosen field. Fellows seeking full time industry positions also have the opportunity to join Amazon at the conclusion of their graduate studies.

Related content
Three of Amazon’s leading roboticists — Sidd Srinivasa, Tye Brady, and Philipp Michel — discuss the challenges of building robotic systems that interact with human beings in real-world settings.

“We have selected and invested in another outstanding class of future scientists and engineers to pursue some of the hardest problems in our field at some of the best academic institutions on the planet. We are excited to be a part of their journey to greatness,” said Tye Brady, chief technologist, Amazon Robotics.

The fourteen recipients of the 2022 Day One Amazon Robotics Fellowships are:

Omoruyi Atheka, Stanford University: Atheka will pursue his master's in mechanical engineering at Stanford University where he hopes to become an expert in robotics and develop his problem-solving skills and research independence. He will receive his bachelor’s at MIT in mechanical engineering with a concentration in optics, with a minor in design and political science. During his time at MIT, he has gained extensive knowledge relating to mechanical engineering, technology, and design.

Camille Anne Chungyoun, Stanford University: Chungyoun will pursue a master’s in robotics at Stanford University, where she hopes to conduct research in robotic locomotion and bio-inspired robotics, ultimately allowing her to work in an R&D industry position where she can use robotic locomotion to advance human health and well-being. She is currently finishing her bachelor’s in mechanical engineering, with a concentration in mechatronics, at the University of Washington.

Asbel Fontanez, Boston University: Fontanez is pursuing a master’s in robotics and autonomous systems at Boston University where he earned his bachelor’s in electrical engineering with a concentration in machine learning. In addition to spending more than 10 years participating in robotics competitions, he has also worked with engineers from Florida Power & Light, Motorola Solutions, and SpaceX. His experiences have given him a greater foundational understanding in many areas of engineering, including mechanical, electrical, and computer engineering.

Zakar Handricken, Northeastern University: Handricken is pursuing a master's in computer science at Northeastern in the Khoury College of Computer Sciences, Institute for Experiential Robotics, led by Taskin Padir. He earned his bachelor’s in computer science from Bridgewater State University where he participated in undergraduate research and worked as an intern at AcadiaSoft. He later joined Fidelity Investments as a software engineer, where he worked on projects under Fidelity's Center for Applied Technology and Data Warehouse. At Fidelity, he began his independent study of artificial intelligence to understand and research its application in robotics, data systems, and more within multidisciplinary areas.

Abubakarr Jaye, Brown: Jaye is pursuing a master’s of engineering with an emphasis on machine learning (ML) at Brown University. He received his bachelor’s in computer science and economics at the University of Illinois Urbana-Champaign. It was there he learned of ML through a friend who demonstrated an animal image neural net classifier built from scratch. His focus is currently on the application of machine learning in finance and economics.

Christopher LeBlanc, Northeastern University: LeBlanc will pursue a master's in artificial intelligence with a specialization in robotics and agent-based systems. He interned for the Louisiana Material Design Alliance, a group concerned with the innovation of novel manufacturing methods. LeBlanc obtained his bachelor's from Louisiana State University in computer science with a minor in chemistry. He decided to follow a career in artificial intelligence to satisfy his long-held curiosity about how a machine could learn. His research interests include robotics, reinforcement learning, and their applications in the automation of industrial systems.

Janeth Meraz, Brown: Meraz is pursuing a master’s degree in computer science at Brown. She earned dual bachelor's degrees in computer science and mathematics from the University of Texas at El Paso. She worked as a researcher studying the optimization of neural network weight-initialization in Diego Aguirre's Applied Intelligence Research Lab, and is a member of the Association for Computing Machinery. Meraz has also served as a mentor in the Computing Alliance for Hispanic Serving Institutions Allyship Program.

Jessie Mindel, MIT: Mindel will earn her bachelor’s in electrical engineering and computer science with an emphasis on new media at University of California, Berkeley. At the core of her work lies storytelling, placemaking, and community-centered design. She seeks to build embodied, empathetic, and narrative technologies that help people better understand themselves, more meaningfully connect with others, and more creatively explore their worlds.

Naana Obeng-Marnu, MIT: Obeng-Marnu will pursue a master’s in media arts and sciences at the MIT Media Lab under the Center for Constructive Communication. She graduated with honors from Brown University with a degree in English, nonfiction writing. She was a premier partner experience operations associate at Meta where she built frameworks and automated processes to better support creators and publishers. As secretary of the board of directors for Brown Broadcasting Service she works alongside industry leaders in new media to support and mentor Brown University students interested in media, design, and tech careers.

Kimberly Llajaruna Peralta, Harvard: Peralta will pursue a master’s degree in data science at Harvard University. She earned her bachelors from the University of Rochester in mechanical engineering and studio arts, where she also worked at Corning as a mechanical process engineer. She developed an interest in data driven decision making during her time at the Corning lens manufacturing facility while working on projects to determine optimal tolerances for manufacturing tools and to design tools that improve the precision of coaters.

Priscila Rubio, Boston University: Rubio will pursue a master’s of science in robotics and autonomous systems at Boston University. She previously interned at the National Institutes of Health, where she investigated the activation mechanism of A3 adenosine receptors. She later interned at Northrop Grumman where she worked to help design mechanical ground support equipment for the Minotaur rocket. She received her bachelors in mechanical engineering at the University of Maryland. There, she worked at US Medical Innovations and used her mechatronics knowledge to extend the capabilities of surgical instruments.

Antonio Sanchez, Worcester Polytechnic Institute: Sanchez will pursue a master’s in either soft robotics or human/robot interaction in the WPI Soft Robotics lab. He will receive his bachelor’s at Texas A&M in mechatronics, where, throughout his undergraduate career, he held several engineering internships. He is interested in embedded electronic systems, machine learning, and computer science.

Augustus ‘ Gus’ Teran, Worcester Polytechnic Institute: Teran is pursuing a master’s in robotics engineering with a focus on multi-robot systems at WPI, where he earned dual bachelor’s degrees in computer science and engineering. He was one of the authors of “Air-Releasable Soft Robots for Explosive Ordnance Disposal” which explored using soft robotics to assist in the de-mining of land mines. The paper was accepted by the IEEE International Conference on Soft Robotics.

Walter Williams, Harvard: Williams will pursue a master’s of engineering in computational science and engineering at Harvard University. He is currently finishing his bachelor's degree in computer science at University of Memphis. There he worked at the Cybersecurity Lab of the Center for Information Assurance, focusing on machine learning based applications in cybersecurity. He has also competed in machine learning competitions, finishing in the top 11% of Kaggle's 2020 Plant Pathology competition.

Read about the teams that are creating the next robotics innovations at Amazon, see job opportunities, and find out more about Amazon's participation at ICRA.

Research areas

Related content

US, CA, Santa Clara
We are seeking an Applied Scientist II to join Amazon Customer Service's Science team, where you will build AI-based automated customer service solutions using state-of-the-art techniques in retrieval-augmented generation (RAG), agentic AI, and post-training of large language models. You will work at the intersection of research and production, developing intelligent systems that directly impact millions of customers while collaborating with scientists, engineers, and product managers in a fast-paced, innovative environment. Key job responsibilities - Design, develop, and deploy information retrieval systems and RAG pipelines using embedding models, reranking algorithms, and generative models to improve customer service automation - Conduct post-training of large language models using techniques such as Supervised Fine-Tuning (SFT), Direct Preference Optimization (DPO), and Group Relative Policy Optimization (GRPO) to optimize model performance for customer service tasks - Build and curate high-quality datasets for model training and evaluation, ensuring data quality and relevance for customer service applications - Design and implement comprehensive evaluation frameworks, including data curation, metrics development, and methods such as LLM-as-a-judge to assess model performance - Develop AI agents for automated customer service, understanding their advantages and common pitfalls, and implementing solutions that balance automation with customer satisfaction - Independently perform research and development with minimal guidance, staying current with the latest advances in machine learning and AI - Collaborate with cross-functional teams including engineering, product management, and operations to translate research into production systems - Publish findings and contribute to the broader scientific community through papers, patents, and open-source contributions - Monitor and improve deployed models based on real-world performance metrics and customer feedback A day in the life As an Applied Scientist II, you will start your day reviewing metrics from deployed models and identifying opportunities for improvement. You might spend your morning experimenting with new post-training techniques to improve model accuracy, then collaborate with engineers to integrate your latest model into production systems. You will participate in design reviews, share your findings with the team, and mentor junior scientists. You will balance research exploration with practical implementation, always keeping the customer experience at the forefront of your work. You will have the autonomy to drive your own research agenda while contributing to team goals and deliverables. About the team The Amazon Customer Service Science team is dedicated to revolutionizing customer support through advanced AI and machine learning. We are a diverse group of scientists and engineers working on some of the most challenging problems in natural language understanding and AI automation. Our team values innovation, collaboration, and a customer-obsessed mindset. We encourage experimentation, celebrate learning from failures, and are committed to maintaining Amazon's high bar for scientific rigor and operational excellence. You will have access to world-class computing resources, massive datasets, and the opportunity to work alongside some of the brightest minds in AI and machine learning.
US, CA, Sunnyvale
Amazon's AGI Information is seeking an exceptional Applied Scientist to drive science advancements in the Amazon Knowledge Graph team (AKG). AKG is re-inventing knowledge graphs for the LLM era, optimizing for LLM grounding. At the same time, AKG is innovating to utilize LLMs in the knowledge graph construction pipelines to overcome obstacles that traditional technologies could not overcome. As a member of the AKG IR team, you will have the opportunity to work on interesting problems with immediate customer impact. The team is addressing challenges in web-scale knowledge mining, fact verification, multilingual information retrieval, and agent memory operating over Graphs. You will also have the opportunity to work with scientists working on the other challenges, and with the engineering teams that deliver the science advancements to our customers. A successful candidate has a strong machine learning and agent background, is a master of state-of-the-art techniques, has a strong publication record, has a desire to push the envelope in one or more of the above areas, and has a track record of delivering to customers. The ideal candidate enjoys operating in dynamic environments, is self-motivated to take on new challenges, and enjoys working with customers, stakeholders, and engineering teams to deliver big customer impact, shipping solutions via rapid experimentation and then iterating on user feedback and interactions. Key job responsibilities As an Applied Scientist, you will leverage your technical expertise and experience to demonstrate leadership in tackling large complex problems. You will collaborate with applied scientists and engineers to develop novel algorithms and modeling techniques to build the knowledge graph that delivers fresh factual knowledge to our customers, and that automates the knowledge graph construction pipelines to scale to many billions of facts. Your first responsibility will be to solve entity resolution to enable conflating facts from multiple sources into a single graph entity for each real world entity. You will develop generic solutions that work fo all classes of data in AKG (e.g., people, places, movies, etc.), that cope with sparse, noisy data, that scale to hundreds of millions of entities, and that can handle streaming data. You will define a roadmap to make progress incrementally and you will insist on scientific rigor, leading by example.
US, CA, Sunnyvale
Amazon 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 innovative 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 unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic 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. We leverage advanced robotics, machine learning, and artificial intelligence to solve complex operational challenges at 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 foundation models that: - Enable unprecedented generalization across diverse tasks - Integrate multi-modal learning capabilities (visual, tactile, linguistic) - Accelerate skill acquisition through demonstration learning - Enhance robotic perception and environmental understanding - Streamline development processes through reusable capabilities 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. As a Senior Applied Scientist, you will develop and improve machine learning systems that help robots perceive, reason, and act in real-world environments. You will leverage state-of-the-art models (open source and internal research), evaluate them on representative tasks, and adapt/optimize them to meet robustness, safety, and performance needs. You will invent new algorithms where gaps exist. You’ll collaborate closely with research, controls, hardware, and product-facing teams, and your outputs will be used by downstream teams to further customize and deploy on specific robot embodiments. Key job responsibilities As a Senior Applied Scientist in the Foundations Model team, you will: - Leverage state-of-the-art models for targeted tasks, environments, and robot embodiments through fine-tuning and optimization. - Execute rapid, rigorous experimentation with reproducible results and solid engineering practices, closing the gap between sim and real environments. - Build and run capability evaluations/benchmarks to clearly profile performance, generalization, and failure modes. - Contribute to the data and training workflow: collection/curation, dataset quality/provenance, and repeatable training recipes. - Write clean, maintainable, well commented and documented code, contribute to training infrastructure, create tools for model evaluation and testing, and implement necessary APIs - Stay current with latest developments in foundation models and robotics, assist in literature reviews and research documentation, prepare technical reports and presentations, and contribute to research discussions and brainstorming sessions. - Work closely with senior scientists, engineers, and leaders across multiple teams, participate in knowledge sharing, support integration efforts with robotics hardware teams, and help document best practices and methodologies.
US, WA, Seattle
We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to apply their causal inference / structural econometrics skillsets to solve real world problems. The intern will work in the area of Store Economics and Science (SEAS) and develop models to SEAS. Our PhD Economist Internship Program offers hands-on experience in applied economics, supported by mentorship, structured feedback, and professional development. Interns work on real business and research problems, building skills that prepare them for full-time economist roles at Amazon and beyond. You will learn how to build data sets and perform applied econometric analysis collaborating with economists, scientists, and product managers. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with placement. These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis. About the team The Stores Economics and Science Team (SEAS) is a Stores-wide interdisciplinary team at Amazon with a "peak jumping" mission focused on disruptive innovation. The team applies science, economics, and engineering expertise to tackle the business's most critical problems, working to move from local to global optima across Amazon Stores operations. SEAS builds partnerships with organizations throughout Amazon Stores to pursue this mission, exploring frontier science while learning from the experience and perspective of others. Their approach involves testing solutions first at a small scale, then aligning more broadly to build scalable solutions that can be implemented across the organization. The team works backwards from customers using their unique scientific expertise to add value, takes on long-run and high-risk projects that business teams typically wouldn't pursue, helps teams with kickstart problems by building practical prototypes, raises the scientific bar at Amazon, and builds and shares software that makes Amazon more productive.
US, WA, Seattle
Amazon 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 electromechanical design to create adaptable automation solutions capable of working safely alongside humans in dynamic environments. This is a unique opportunity to shape the future of robotics and automation at an unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic manipulation, locomotion, and human-robot interaction. Amazon is seeking a talented and motivated Principal Applied Scientist to develop tactile sensors and guide the sensing strategy for our gripper design. The ideal candidate will have extensive experience in sensor development, analysis, testing and integration. This candidate must have the ability to work well both independently and in a multidisciplinary team setting. Key job responsibilities - Author functional requirements, design verification plans and test procedures - Develop design concepts which meet the requirements - Work with engineering team members to implement the concepts in a product design - Support product releases to manufacturing and customer deployments - Work efficiently to support aggressive schedules
US, WA, Redmond
Amazon Leo is an initiative to launch a constellation of Low Earth Orbit satellites that will provide low-latency, high-speed broadband connectivity to unserved and underserved communities around the world. As a Communications Engineer in Modeling and Simulation, this role is primarily responsible for the developing and analyzing high level system resource allocation techniques for links to ensure optimal system and network performance from the capacity, coverage, power consumption, and availability point of view. Be part of the team defining the overall communication system and architecture of Amazon Leo’s broadband wireless network. This is a unique opportunity to innovate and define novel wireless technology with few legacy constraints. The team develops and designs the communication system of Leo and analyzes its overall system level performance, such as overall throughput, latency, system availability, packet loss, etc., as well as compatibility for both connectivity and interference mitigation with other space and terrestrial systems. This role in particular will be responsible for 1) evaluating complex multi-disciplinary trades involving RF bandwidth and network resource allocation to customers, 2) understanding and designing around hardware/software capabilities and constraints to support a dynamic network topology, 3) developing heuristic or solver-based algorithms to continuously improve and efficiently use available resources, 4) demonstrating their viability through detailed modeling and simulation, 5) working with operational teams to ensure they are implemented. This role will be part of a team developing the necessary simulation tools, with particular emphasis on coverage, capacity, latency and availability, considering the yearly growth of the satellite constellation and terrestrial network. 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. Key job responsibilities • Work within a project team and take the responsibility for the Leo's overall communication system design and architecture • Extend existing code/tools and create simulation models representative of the target system, primarily in MATLAB • Design interconnection strategies between fronthaul and backhaul nodes. Analyze link availability, investigate link outages, and optimize algorithms to study and maximize network performance • Use RF and optical link budgets with orbital constellation dynamics to model time-varying system capacity • Conduct trade-off analysis to benefit customer experience and optimization of resources (costs, power, spectrum), including optimization of satellite constellation design and link selection • Work closely with implementation teams to simulate expected system level performance and provide quick feedback on potential improvements • Analyze and minimize potential self-interference or interference with other communication systems • Provide visualizations, document results, and communicate them across multi-disciplinary project teams to make key architectural decisions
US, CA, Cupertino
The AWS Neuron Science Team is looking for talented scientists to enhance our software stack, accelerating customer adoption of Trainium and Inferentia accelerators. In this role, you will work directly with external and internal customers to identify key adoption barriers and optimization opportunities. You'll collaborate closely with our engineering teams to implement innovative solutions and engage with academic and research communities to advance state-of-the-art ML systems. As part of a strategic growth area for AWS, you'll work alongside distinguished engineers and scientists in an exciting and impactful environment. We actively work on these areas: - AI for Systems: Developing and applying ML/RL approaches for kernel/code generation and optimization - Machine Learning Compiler: Creating advanced compiler techniques for ML workloads - System Robustness: Building tools for accuracy and reliability validation - Efficient Kernel Development: Designing high-performance kernels optimized for our ML accelerator architectures A day in the life AWS Utility Computing (UC) provides 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, Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services. Additionally, this role may involve exposure to and experience with Amazon's growing suite of generative AI services and other cloud computing offerings across the AWS portfolio. About the team AWS Neuron is the software of Trainium and Inferentia, the AWS Machine Learning chips. Inferentia delivers best-in-class ML inference performance at the lowest cost in the cloud to our AWS customers. Trainium is designed to deliver the best-in-class ML training performance at the lowest training cost in the cloud, and it’s all being enabled by AWS Neuron. Neuron is a Software that include ML compiler and native integration into popular ML frameworks. Our products are being used at scale with external customers like Anthropic and Databricks as well as internal customers like Alexa, Amazon Bedrocks, Amazon Robotics, Amazon Ads, Amazon Rekognition and many more.
US, TX, Austin
Amazon Security is seeking an Applied Scientist to work on GenAI acceleration within the Secure Third Party Tools (S3T) organization. The S3T team has bold ambitions to re-imagine security products that serve Amazon's pace of innovation at our global scale. This role will focus on leveraging large language models and agentic AI to transform third-party security risk management, automate complex vendor assessments, streamline controllership processes, and dramatically reduce assessment cycle times. You will drive builder efficiency and deliver bar-raising security engagements across Amazon. Key job responsibilities Own and drive end-to-end technical delivery for scoped science initiatives focused on third-party security risk management, independently defining research agendas, success metrics, and multi-quarter roadmaps with minimal oversight. Understanding approaches to automate third-party security review processes using state-of-the-art large language models, development intelligent systems for vendor assessment document analysis, security questionnaire automation, risk signal extraction, and compliance decision support. Build advanced GenAI and agentic frameworks including multi-agent orchestration, RAG pipelines, and autonomous workflows purpose-built for third-party risk evaluation, security documentation processing, and scalable vendor assessment at enterprise scale. Build ML-powered risk intelligence capabilities that enhance third-party threat detection, vulnerability classification, and continuous monitoring throughout the vendor lifecycle. Coordinate with Software Engineering and Data Engineering to deploy production-grade ML solutions that integrate seamlessly with existing third-party risk management workflows and scale across the organization. About the team Security is central to maintaining customer trust and delivering delightful customer experiences. At Amazon, our Security organization is designed to drive bar-raising security engagements. Our vision is that Builders raise the Amazon security bar when they use our recommended tools and processes, with no overhead to their business. Diverse Experiences Amazon Security values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why Amazon Security? At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon’s products and services. We offer talented security professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores. Inclusive Team Culture In Amazon Security, it’s in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices. Training & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, training, and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.
US, CA, Mountain View
At AWS Healthcare AI, we're revolutionizing healthcare delivery through AI solutions that serve millions globally. As a pioneer in healthcare technology, we're building next-generation services that combine Amazon's world-class AI infrastructure with deep healthcare expertise. Our mission is to accelerate our healthcare businesses by delivering intuitive and differentiated technology solutions that solve enduring business challenges. The AWS Healthcare AI organization includes services such as HealthScribe, Comprehend Medical, HealthLake, and more. We're seeking a Senior Applied Scientist to join our team working on our AI driven clinical solutions that are transforming how clinicians interact with patients and document care. Key job responsibilities To be successful in this mission, we are seeking an Applied Scientist to contribute to the research and development of new, highly influencial AI applications that re-imagine experiences for end-customers (e.g., consumers, patients), frontline workers (e.g., customer service agents, clinicians), and back-office staff (e.g., claims processing, medical coding). As a leading subject matter expert in NLU, deep learning, knowledge representation, foundation models, and reinforcement learning, you will collaborate with a team of scientists to invent novel, generative AI-powered experiences. This role involves defining research directions, developing new ML techniques, conducting rigorous experiments, and ensuring research translates to impactful products. You will be a hands-on technical innovator who is passionate about building scalable scientific solutions. You will set the standard for excellence, invent scalable, scientifically sound solutions across teams, define evaluation methods, and lead complex reviews. This role wields significant influence across AWS, Amazon, and the global research community.
US, CA, San Francisco
The Amazon Center for Quantum Computing (CQC) is a multi-disciplinary team of scientists, engineers, and technicians, all working to innovate in quantum computing for the benefit of our customers. We are looking to hire an Applied Scientist to design and model novel superconducting quantum devices (including qubits), readout and control schemes, and advanced quantum processors. The ideal candidate will have a track record of original scientific contributions, strong engineering principles, and/or software development experience. Resourcefulness, as well as strong organizational and communication skills, is essential. About the team The Amazon Center for Quantum Computing (CQC) is a multi-disciplinary team of scientists, engineers, and technicians, on a mission to develop a fault-tolerant quantum computer. Inclusive Team Culture Here at Amazon, 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. Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred 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. 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 U.S export license. If you are unsure if you meet these requirements, please apply and Amazon will review your application for eligibility.