Careers

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. 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 - Collaborate with simulation and robotics experts to translate physical modeling needs into robust, scalable, and maintainable simulation solutions. - Design and implement high-performance simulation modeling and tools for rigid and deformable body simulation. - Identify and optimize performance bottlenecks in simulation pipelines to support real-time and batch simulation workflows. - Help build validation and unit testing pipelines to ensure correctness and physical fidelity of simulation results. - Identify potential sources of sim-to-real gaps and propose modeling and numerical approximations to reduce them. - Stay current with the latest advances in numerical methods, parallel computing, and GPU architectures, and incorporate them into our tools.

The 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. We are looking to hire a Senior Design Automation Engineer to join our growing software team. You will work closely with our superconducting chip design teams to enable their working designing, simulating, and improving the performance of our quantum devices. The ideal candidate should be able to translate high-level science requirements into software implementations (e.g. Python APIs/frameworks, automation routines, database schemas, infrastructure-as-code setups) that are performant, scalable, and intuitive. This requires someone who (1) has a strong desire to work within a team of scientists and engineers, and (2) demonstrates ownership in initiating and driving projects to completion. This role has a particular emphasis on working directly with chip designers to develop scientific software for automating, scaling, and optimizing the quantum device design process. 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 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. Key job responsibilities - Work with designers to build a quantum processor design automation flow. This will involve a combination of writing new software and influencing the working model of our scientist collaborators on the design team. - Develop a shared Python library for analysis and optimization routines that can be re-used across designs. - Profile and improve the performance of design, simulation, & analysis tools to enable scaling to larger devices. - Leverage infrastructure-as-code to define and orchestrate high-performance computing (HPC) workloads. - Make changes to the database and UI as necessary to capture and visualize design progress and performance. - Look for opportunities to accelerate design workflows by taking advantage of the latest advancements in scientific computing, machine learning, and open-source chip layout and design software. - Empower scientists to actively contribute to the codebase through mentorship and documentation. We are looking for candidates with strong engineering principles, a bias for action, superior problem-solving, and excellent communication skills. Working effectively within a team environment is essential. As a research software engineer embedded in a broader research science organization, you will have the opportunity to work on new ideas and stay abreast of the field of experimental quantum computation. A day in the life The majority of your time will be spent on projects that extend the functional capabilities or performance of our internal research software stack. This requires working backwards from the needs of our science staff in the context of our larger experimental roadmap. You will translate science and software requirements into design proposals balancing implementation complexity against time-to-delivery. Once a design proposal has been reviewed and accepted, you’ll drive implementation and coordinate with internal stakeholders to ensure a smooth roll out. Because many high-level experimental goals have cross-cutting requirements, you’ll often work closely with other engineers or scientists or on the team. About the team You will be joining the software group within the Center of Quantum Computing. Our team is comprised of scientists and software engineers who are building scalable software that enables quantum computing technologies.

Amazon Devices is an inventive research and development company that designs and engineer high-profile devices like the Kindle family of products, Fire Tablets, Fire TV, Health Wellness, Amazon Echo & Astro products. This is an exciting opportunity to join Amazon in developing state-of-the-art techniques that bring Gen AI on edge for our consumer products. We are looking for exceptional scientists to join our Applied Science team and help develop the next generation of edge models, and optimize them while doing co-designed with custom ML HW based on a revolutionary architecture. Work hard. Have Fun. Make History. Key job responsibilities Quantize, prune, distill, finetune Gen AI models to optimize for edge platforms Fundamentally understand Amazon’s underlying Neural Edge Engine to invent optimization techniques Analyze deep learning workloads and provide guidance to map them to Amazon’s Neural Edge Engine Use first principles of Information Theory, Scientific Computing, Deep Learning Theory, Non Equilibrium Thermodynamics Train custom Gen AI models that beat SOTA and paves path for developing production models Collaborate closely with compiler engineers, fellow Applied Scientists, Hardware Architects and product teams to build the best ML-centric solutions for our devices Publish in open source and present on Amazon's behalf at key ML conferences - NeurIPS, ICLR, MLSys.

You will be working with a unique and gifted team developing exciting products for consumers. The team is a multidisciplinary group of engineers and scientists engaged in a fast paced mission to deliver new products. The team faces a challenging task of balancing cost, schedule, and performance requirements. You should be comfortable collaborating in a fast-paced and often uncertain environment, and contributing to innovative solutions, while demonstrating leadership, technical competence, and meticulousness. Your deliverables will include development of thermal solutions, concept design, feature development, product architecture and system validation through to manufacturing release. You will support creative developments through application of analysis and testing of complex electronic assemblies using advanced simulation and experimentation tools and techniques. Key job responsibilities In this role, you will: - Lead end-to-end thermal design for SoC and consumer electronics, spanning package, board, system architecture, and product integration - Perform advanced CFD simulations using tools such as Star-CCM+ or FloEFD to assess feasibility, risks, and mitigation strategies - Plan and execute thermal validation for devices and SoC packages, ensuring compliance with safety, reliability, and qualification requirements - Partner with cross-functional and cross-site teams to influence product decisions, define thermal limits, and establish temperature thresholds - Develop data processing, statistical analysis, and test automation frameworks to improve insight quality, scalability, and engineering efficiency - Communicate thermal risks, trade-offs, and mitigation strategies clearly to engineering leadership to support schedule, performance, and product decisions About the team Amazon Lab126 is an inventive research and development company that designs and engineers high-profile consumer electronics. Lab126 began in 2004 as a subsidiary of Amazon.com, Inc., originally creating the best-selling Kindle family of products. Since then, we have produced innovative devices like Fire tablets, Fire TV and Amazon Echo. What will you help us create?

Success in any organization begins with its people and having a comprehensive understanding of our workforce and how we best utilize their unique skills and experience is paramount to our future success. WISE (Workforce Intelligence powered by Scientific Engineering) delivers the scientific and engineering foundation that powers Amazon's enterprise-wide workforce planning ecosystem. Addressing the critical need for precise workforce planning, WISE enables a closed-loop mechanism essential for ensuring Amazon has the right workforce composition, organizational structure, and geographical footprint to support long-term business needs with a sustainable cost structure. We are looking for a Sr. Applied Scientist to join our ML/AI team to work on Advanced Optimization and LLM solutions. You will partner with Software Engineers, Machine Learning Engineers, Data Engineers and other Scientists, TPMs, Product Managers and Senior Management to help create world-class solutions. We're looking for people who are passionate about innovating on behalf of customers, demonstrate a high degree of product ownership, and want to have fun while they make history. You will leverage your knowledge in machine learning, advanced analytics, metrics, reporting, and analytic tooling/languages to analyze and translate the data into meaningful insights. You will have end-to-end ownership of operational and technical aspects of the insights you are building for the business, and will play an integral role in strategic decision-making. Further, you will build solutions leveraging advanced analytics that enable stakeholders to manage the business and make effective decisions, partner with internal teams to identify process and system improvement opportunities. As a tech expert, you will be an advocate for compelling user experiences and will demonstrate the value of automation and data-driven planning tools in the People Experience and Technology space. Key job responsibilities * Engineering execution - drive crisp and timely execution of milestones, consider and advise on key design and technology trade-offs with engineering teams * Priority management - manage diverse requests and dependencies from teams * Process improvements – define, implement and continuously improve delivery and operational efficiency * Stakeholder management – interface with and influence your stakeholders, balancing business needs vs. technical constraints and driving clarity in ambiguous situations * Operational Excellence – monitor metrics and program health, anticipate and clear blockers, manage escalations To be successful on this journey, you love having high standards for yourself and everyone you work with, and always look for opportunities to make our services better.

Amazon's Compliance and Safety Services (CoSS) Team is looking for a smart and creative Applied Scientist to apply and extend state-of-the-art research in NLP, multi-modal modeling, domain adaptation, continuous learning and large language model to join the Applied Science team. At Amazon, we are working to be the most customer-centric company on earth. Millions of customers trust us to ensure a safe shopping experience. This is an exciting and challenging position to drive research that will shape new ML solutions for product compliance and safety around the globe in order to achieve best-in-class, company-wide standards around product assurance. You will research on large amounts of tabular, textual, and product image data from product detail pages, selling partner details and customer feedback, evaluate state-of-the-art algorithms and frameworks, and develop new algorithms to improve safety and compliance mechanisms. You will partner with engineers, technical program managers and product managers to design new ML solutions implemented across the entire Amazon product catalog. Key job responsibilities As an Applied Scientist on our team, you will: - Research and Evaluate state-of-the-art algorithms in NLP, multi-modal modeling, domain adaptation, continuous learning and large language model. - Design new algorithms that improve on the state-of-the-art to drive business impact, such as synthetic data generation, active learning, grounding LLMs for business use cases - Design and plan collection of new labels and audit mechanisms to develop better approaches that will further improve product assurance and customer trust. - Analyze and convey results to stakeholders and contribute to the research and product roadmap. - Collaborate with other scientists, engineers, product managers, and business teams to creatively solve problems, measure and estimate risks, and constructively critique peer research - Consult with engineering teams to design data and modeling pipelines which successfully interface with new and existing software - Publish research publications at internal and external venues. About the team The science team delivers custom state-of-the-art algorithms for image and document understanding. The team specializes in developing machine learning solutions to advance compliance capabilities. Their research contributions span multiple domains including multi-modal modeling, unstructured data matching, text extraction from visual documents, and anomaly detection, with findings regularly published in academic venues.

Have you ever wondered how Amazon predicts delivery times and ensures your orders arrive exactly when promised? Have you wondered where all those Amazon semi-trucks on the road are headed? Are you passionate about increasing efficiency and reducing carbon footprint? Does the idea of having worldwide impact on Amazon's multimodal logistics network that includes planes, trucks, and vans sound exciting to you? Are you interested in developing Generative AI solutions using state-of-the-art LLM techniques to revolutionize how Amazon optimizes the fulfillment of millions of customer orders globally with unprecedented scale and precision? If so, then we want to talk with you! Join our team to apply the latest advancements in Generative AI to enhance our capability and speed of decision making. Fulfillment Planning & Execution (FPX) Science team within SCOT- Fulfillment Optimization owns and operates optimization, machine learning, and simulation systems that continually optimize the fulfillment of millions of products across Amazon’s network in the most cost-effective manner, utilizing large scale optimization, advanced machine learning techniques, big data technologies, and scalable distributed software on the cloud that automates and optimizes inventory and shipments to customers under the uncertainty of demand, pricing, and supply. The team has embarked on its Generative AI to build the next-generation AI agents and LLM frameworks to promote efficiency and improve productivity. We’re looking for a passionate, results-oriented, and inventive machine learning scientist who can design, build, and improve models for our outbound transportation planning systems. You will work closely with our product managers and software engineers to disambiguate complex supply chain problems and create ML / AI solutions to solve those problems at scale. You will work independently in an ambiguous environment while collaborating with cross-functional teams to drive forward innovation in the Generative AI space. Key job responsibilities * Design, develop, and evaluate tailored ML/AI, models for solving complex business problems. * Research and apply the latest ML / AI techniques and best practices from both academia and industry. * Identify and implement novel Generative AI use cases to deliver value. * Design and implement Generative AI and LLM solutions to accelerate development and provide intuitive explainability of complex science models. * Develop and implement frameworks for evaluation, validation, and benchmarking AI agents and LLM frameworks. * Think about customers and how to improve the customer delivery experience. * Use analytical techniques to create scalable solutions for business problems. * Work closely with software engineering teams to build model implementations and integrate successful models and algorithms in production systems at large scale. * Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation. A day in the life You will have the opportunity to learn how Amazon plans for and executes within its logistics ne twork including Fulfillment Centers, Sort Centers, and Delivery Stations. In this role, you will design and develop Machine Learning / AI models with significant scope, impact, and high visibility. You will focus on designing, developing, and deploying Generative AI solutions at scale that will improve efficiency, increase productivity, accelerate development, automate manual tasks, and deliver value to our internal customers. Your solutions will impact business segments worth many-billions-of-dollars and geographies spanning multiple countries and markets. From day one, you will be working with bar raising scientists, engineers, and designers. You will also collaborate with the broader science community in Amazon to broaden the horizon of your work. Successful candidates must thrive in fast-paced environments, which encourage collaborative and creative problem solving, be able to measure and estimate risks, constructively critique peer research, and align research focuses with the Amazon's strategic needs. We look for individuals who know how to deliver results and show a desire to develop themselves, their colleagues, and their career. About the team FPX Science tackles some of the most mathematically complex challenges in transportation planning and execution space to improve Amazon's operational efficiency worldwide at a scale that is unique to Amazon. We own the long-term and intermediate-term planning of Amazon’s global fulfillment centers and transportation network as well as the short-term network planning and execution that determines the optimal flow of customer orders through Amazon fulfillment network. FPX science team is a group of scientists with different technical backgrounds including Machine Learning and Operations Research, who will collaborate closely with you on your projects. Our team directly supports multiple functional areas across SCOT - Fulfillment Optimization and the research needs of the corresponding product and engineering teams. We disambiguate complex supply chain problems and create innovative data-driven solutions to solve those problems at scale with a mix of science-based techniques including Operations Research, Simulation, Machine Learning, and AI to tackle some of our biggest technical challenges. In addition, we are incorporating the latest advances in Generative AI and LLM techniques in how we design, develop, enhance, and interpret the results of these science models.

Amazon LEO is Amazon’s low Earth orbit satellite network. Our mission is to deliver fast, reliable internet connectivity to customers beyond the reach of existing networks. From individual households to schools, hospitals, businesses, and government agencies, Amazon Leo will serve people and organizations operating in locations without reliable connectivity. The Amazon LEO Infrastructure Data Engineering, Analytics, and Science team owns designing, implementing, and operating systems/models that support the optimal demand/capacity planning function. We are looking for a talented scientist to implement LEO's long-term vision and strategy for capacity simulations and network bandwidth optimization. This effort will be instrumental in helping LEO execute on its business plans globally. As one of our valued team members, you will be obsessed with matching our standards for operational excellence with a relentless focus on delivering results. Key job responsibilities In this role, you will: Work cross-functionally with product, business development, and various technical teams (engineering, science, R&D, simulations, etc.) to implement the long-term vision, strategy, and architecture for capacity simulations and inventory optimization. Design and deliver modern, flexible, scalable solutions to complex optimization problems for operating and planning satellite resources. Contribute to short and long terms technical roadmap definition efforts to predict future inventory availability and key operational and financial metrics across the network. Design and deliver systems that can keep up with the rapid pace of optimization improvements and simulating how they interact with each other. Analyze large amounts of satellite and business data to identify simulation and optimization opportunities. Synthesize and communicate insights and recommendations to audiences of varying levels of technical sophistication to drive change across LEO. Export Control Requirement: Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum.

As part of the AWS Applied AI Solutions organization, we have a vision to provide business applications, leveraging Amazon's unique experience and expertise, that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers' businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. We blend vision with curiosity and Amazon's real-world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are no-brainers to buy and easy to use. The Applied Scientist II will contribute to the development of AI systems. The role requires extending existing scientific techniques and inventing new ones to address specific customer needs at a project level. You should be comfortable working semi-autonomously on difficult problems with visible risks or roadblocks. You'll work closely with technical leaders within the team. We're looking for scientists who can maintain high standards while moving quickly, prioritizing both rapid experimentation and responsible AI development to deliver measurable customer impact. Key job responsibilities * Design and implement solutions that extend or adapt scientific approaches for customer needs at the project level * Deliver components into production that meet high quality standards (efficient, reproducible, testable code) * Produce research reports demonstrating correctness, scholarship, and scientific rigor * Work with product and science teams to deliver impactful AI features * Contribute to operational excellence in the team's deliverables About the team Amazon Connect is a highly disruptive cloud-based contact center that enables businesses to deliver engaging, dynamic, and personal customer service experiences. Amazon Connect is the result of the ten years of development that went into building the tools Amazon uses to provide its award winning customer service at massive scale and launching it as a publicly available AWS service. With Amazon Connect, you can create your own cloud-based contact center and be taking calls in minutes. Amazon Connect leverages the power of Artificial Intelligence and the large ecosystem of AWS services such as Amazon Lex, Amazon Polly, AWS Lambda, Amazon S3 and Amazon Kinesis to provide a truly frustration free, easy-to-use, extensible, and natural customer experience. With this technology, we are transforming an industry and the way customers interact with businesses and how agents service them.

As part of the AWS Applied AI Solutions organization, we have a vision to provide business applications, leveraging Amazon's unique experience and expertise, that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers' businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. We blend vision with curiosity and Amazon's real-world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are no-brainers to buy and easy to use. The Senior Applied Scientist will lead the scientific agenda for AI systems at the product level. The role requires identifying and solving ill-defined problems where no textbook solutions exist, balancing rapid innovation with reliability and compliance. You should be comfortable making decisions with incomplete information and driving solutions in ambiguous problem spaces. You'll work closely with senior technical leaders within the team and across AWS, influencing across multiple teams. We're looking for scientists who can maintain high standards while moving quickly, prioritizing both rapid experimentation and responsible AI development to deliver measurable customer impact. Key job responsibilities * Lead the design, implementation, and delivery of scientifically-complex production solutions that address medium-to-large business problems * Drive your team's scientific agenda and propose new initiatives aligned with customer needs and business problems * Invent new methodologies or paradigms when existing approaches are insufficient * Influence across multiple teams to build consensus on technical direction and scientific approaches * Deliver significant portions of critical-path code that meets high quality standards (efficient, reproducible, testable, maintainable) * Actively mentor and develop other scientists, fostering a culture of scientific excellence About the team Amazon Connect is a highly disruptive cloud-based contact center that enables businesses to deliver engaging, dynamic, and personal customer service experiences. Amazon Connect is the result of the ten years of development that went into building the tools Amazon uses to provide its award winning customer service at massive scale and launching it as a publicly available AWS service. With Amazon Connect, you can create your own cloud-based contact center and be taking calls in minutes. Amazon Connect leverages the power of Artificial Intelligence and the large ecosystem of AWS services such as Amazon Lex, Amazon Polly, AWS Lambda, Amazon S3 and Amazon Kinesis to provide a truly frustration free, easy-to-use, extensible, and natural customer experience. With this technology, we are transforming an industry and the way customers interact with businesses and how agents service them.