Careers

The Amazon Center for Quantum Computing (CQC) team is looking for a passionate, talented, and inventive Research Engineer specializing in hardware design for cryogenic environments. The ideal candidate should have expertise in 3D CAD (SolidWorks), thermal and structural FEA (Ansys/COMSOL), hardware design for cryogenic applications, design for manufacturing, and mechanical engineering principles. The candidate must have demonstrated experience driving designs through full product development cycles (requirements, conceptual design, detailed design, manufacturing, integration, and testing). Candidates must also have a strong background in both cryogenic mechanical engineering theory and implementation. Working effectively within a cross-functional team environment is critical. Key job responsibilities The CQC collaborates across teams and projects to offer state-of-the-art, cost-effective solutions for scaling the signal delivery to quantum processor systems at cryogenic temperatures. Equally important is the ability to scale the thermal performance and improve EMI mitigation of the cryogenic environment. You will work on the following: - High density novel packaging solutions for quantum processor units - Cryogenic mechanical design for novel cryogenic signal conditioning sub-assemblies - Cryogenic mechanical design for signal delivery systems - Simulation-driven designs (shielding, filtering, etc.) to reduce sources of EMI within the qubit environment. - Own end-to-end product development through requirements, design reports, design reviews, assembly/testing documentation, and final delivery A day in the life As you design and implement cryogenic hardware solutions, from requirements definition to deployment, you will also: - Participate in requirements, design, and test reviews and communicate with internal stakeholders - Work cross-functionally to help drive decisions using your unique technical background and skill set - Refine and define standards and processes for operational excellence - Work in a high-paced, startup-like environment where you are provided the resources to innovate quickly 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.

As an Applied Scientist in the Alexa AI team, you will spearhead the advancement and deployment of state-of-the-art LLM systems that revolutionize how millions of customers interact with Alexa across many languages and locales. You'll leverage your expertise in machine learning, natural language processing, and large language models to create reliable, scalable, high-performance products that set new standards in operational excellence. Working at the intersection of research and production, you'll translate the latest AI innovations into customer-facing features that delight users daily. Your work will span the full ML lifecycle: from analyzing customer behavior patterns and building novel metrics for personal digital assistants, to adapting and post-training large language models (SFT, RL, DPO) and conducting rigorous A/B testing across diverse devices, endpoints, and languages. Collaborating closely with business, engineering, and science teams across Amazon, you'll lead high-visibility programs that automate workflows and deliver measurable customer impact, helping bring a consistent experience to customers in every language they speak. This role offers the unique opportunity to publish at top-tier conferences while seeing your innovations scale to one of the world's most popular voice assistants, serving millions of customers globally. Key job responsibilities As an Applied Scientist in the Alexa AI team: - You'll analyze and model customer behavior at scale, building novel metrics for personal digital assistants across diverse devices, endpoints, and languages. Your work will involve creating deep learning, policy-based learning, and machine learning algorithms that directly impact customer experiences, translating complex data patterns into actionable insights that drive product innovation. - Your technical leadership will extend to adapting large language models through supervised fine-tuning, reinforcement learning, and preference optimization (SFT, RL, DPO), building and deploying automated training and evaluation pipelines, and conducting rigorous model and data analysis through online A/B testing. You'll research and implement novel approaches that push the boundaries of conversational AI, including how it generalizes across multiple languages and scripts. - Beyond model development, you'll ensure operational excellence by taking ownership of production systems, including on-call responsibilities during peak and non-peak hours. Working alongside Software Development Engineers, you'll deploy fixes and handle high-severity issues, ensuring our ML systems maintain the reliability and performance that millions of Alexa customers depend on daily. A day in the life As an Applied Scientist in the Alexa AI team, your day will involve collaborating with talented engineers and scientists to build scalable solutions for our conversational assistant. You'll dive into data analysis, experiment with novel algorithms, fine-tune and align LLMs, and iterate on models based on real-time user feedback. Working in a fast-paced, ambiguous environment, you'll tackle complex technical challenges, from debugging production issues to presenting research findings to stakeholders. Your self-motivated approach will drive you to swiftly deliver impactful solutions while maintaining the high standards that define our mission to revolutionize user experiences for millions of customers. About the team The Alexa AI team develops the intelligence behind one of the world's most popular voice assistants, serving millions of customers globally. We're a diverse group of scientists, engineers, and researchers united by our mission to make Alexa more natural, helpful, and delightful. Our culture thrives on innovation, collaboration, and customer obsession. We tackle some of the most challenging problems in conversational AI, from multilingual natural language understanding to personalization at scale. Here, you'll work alongside world-class talent, publish at top-tier conferences, and see your innovations impact customers daily. We move fast, think big, and celebrate both successes and learnings.

Are you passionate about programming languages, applying formal verification, program analysis, constraint-solving, and/or theorem proving to real world problems? Do you want to create products that help customers? If so, then we have an exciting opportunity for you. In this role, you will interact with internal teams and external customers to understand their requirements. You will apply your knowledge to propose innovative solutions, create software prototypes, and productize prototypes into production systems using software development tools and methodologies. In addition, you will support and scale your solutions to meet the ever growing demand of customer use. Technical Responsibilities: - Interact with various teams to develop an understanding of their security and safety requirements. - Apply the acquired knowledge to build tools find problems, or show the absence of security/safety problems. - Implement these tools through the use of SAT, SMT, and various concepts from programming languages, theorem proving, formal verification and constraint solving. - Perform analysis of the customer systems using tools developed in-house or externally provided - Create software prototypes to verify and validate the devised solutions methodologies; integrate the prototypes into production systems using standard software development tools and methodologies. Leadership Responsibilities: - Can present and defend company-wide technical decisions to the internal technical community and represent the company effectively at technical conferences. - Functional thought leader, sought after for key tech decisions. Can successfully sell ideas to an executive level decision maker. - Mentors and trains the research scientist community on complex technical issues. AWS has the most services and more features within those services, than any other cloud provider–from infrastructure technologies like compute, storage, and databases–to emerging technologies, such as machine learning and artificial intelligence, data lakes and analytics, and Internet of Things. Whether its Identity features such as access management and sign on, cryptography, console, builder & developer tools, and even projects like automating all of our contractual billing systems, AWS Platform is always innovating with the customer in mind. The AWS Platform team sustains over 750 million transactions per second. We have a formal mentor search application that lets you find a mentor that works best for you based on location, job family, job level etc. Your manager can also help you find a mentor or two, because two is better than one. In addition to formal mentors, we work and train together so that we are always learning from one another, and we celebrate and support the career progression of our team members. Key job responsibilities Technical Responsibilities: - Interact with various teams to develop an understanding of their security and safety requirements. - Apply the acquired knowledge to build tools find problems, or show the absence of security/safety problems. - Implement these tools through the use of SAT, SMT, BDDs, and various concepts from programming languages, theorem proving, formal verification and constraint solving. - Perform analysis of the customer systems using tools developed in-house or externally provided - Create software prototypes to verify and validate the devised solutions methodologies; integrate the prototypes into production systems using standard software development tools and methodologies. Leadership Responsibilities: - Can present and defend company-wide technical decisions to the internal technical community and represent the company effectively at technical conferences. - Functional thought leader, sought after for key tech decisions. Can successfully sell ideas to an executive level decision maker. - Mentors and trains the research scientist community on complex technical issues. A day in the life You will be working on technology related to formal methods, automated reasoning, automated testing, and adjacent areas. You will work with fellow applied scientists to solve challenging problems that provide value to customers by improving the quality of software. You will have an opportunity to publish your work. Why AWS Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. About the team The Automated Reasoning in Identity (ARI) team is growing fast. It works on applying automated reasoning techniques to services within AWS's Identity organization, building on initial successes of the Zelkova and Access Analyzer projects. The reach of AR within Identity is growing, with more scientists joining all the time.

Do you want to make a real difference to real people's lives? Want to design and build fair and explainable systems which automate recruitment processes across Amazon? Come and be part of a team that develops new machine learning (ML) technologies, which help Amazon scale for its customers by recruiting diverse teams. Join our Recommendations team within Intelligent Talent Acquisition (ITA) where you’ll build machine learning products that transform how job seekers find opportunities and recruiters discover talent. You’ll develop sophisticated recommendation systems powering both Amazon Jobs and internal hiring platforms, operating at global scale to match the right people with the right positions. Using techniques including representation learning, reinforcement learning, and probabilistic modeling, your work will directly improve efficiency for recruiters and help candidates find their ideal roles. This position offers the chance to solve complex problems with significant impact by creating systems that make Amazon’s entire hiring ecosystem more effective while collaborating with scientists across the organization. Key job responsibilities - Design and implement machine learning models that power recommendation systems for job seekers and recruiters, ensuring high performance, scalability, and reliability at global scale. Our ideal candidate has a strong scientific foundation and experience of statistical analysis and model building and has a passion for fairness and explainability in ML systems. - Collaborate with engineers, scientists, and product managers to define requirements, create solutions, and deliver products that improve the hiring experience. - Participate in the full software development lifecycle including scoping, design, coding, testing, documentation, deployment, and maintenance of recommendation systems and ML models. - Solve complex ML problems using optimal data structures and algorithms, making thoughtful trade-offs between efficiency and maintainability. - Stay current with scientific literature and develop novel approaches that address business challenges in talent acquisition. You will have the opportunity to provide feedback on scientific work across the organization helping the entire Intelligent Talent Acquisition organization improve. A day in the life You might spend the morning reviewing a colleague’s code for a new recommendation algorithm feature, then collaborate with product managers to refine requirements for an upcoming enhancement. After lunch, you’ll dive into model development, analyzing performance metrics from recent A/B tests and implementing improvements to the job-seeker recommendation pipeline. Throughout the day, you’ll participate in scientific discussions with peers across the organization, providing valuable feedback while continuing to refine your expertise. About the team The Recommendations team is a hybrid group of software engineers and applied scientists located in Edinburgh. We build tools that match people to jobs and jobs to people, optimizing experiences for both recruiters and candidates. Our work directly impacts Amazon’s ability to find and hire exceptional talent globally. The team maintains a collaborative environment with regular knowledge sharing and mentorship opportunities. We work closely with our product teams to understand business needs and develop innovative scientific solutions that improve hiring outcomes across both industry and student requisitions worldwide.

Do you want to lead the development of advanced machine learning systems that protect millions of customers and power a trusted global eCommerce experience? Are you passionate about modeling terabytes of data, solving highly ambiguous fraud and risk challenges, and driving step-change improvements through scientific innovation? If so, the Amazon Buyer Risk Prevention (BRP) Machine Learning team may be the right place for you. We are seeking a Senior Applied Scientist to define and drive the scientific direction of large-scale risk management systems that safeguard millions of transactions every day. In this role, you will lead the design and deployment of advanced machine learning solutions, influence cross-team technical strategy, and leverage emerging technologies—including Generative AI and LLMs—to build next-generation risk prevention platforms. Key job responsibilities Lead the end-to-end scientific strategy for large-scale fraud and risk modeling initiatives Define problem statements, success metrics, and long-term modeling roadmaps in partnership with business and engineering leaders Design, develop, and deploy highly scalable machine learning systems in real-time production environments Drive innovation using advanced ML, deep learning, and GenAI/LLM technologies to automate and transform risk evaluation Influence system architecture and partner with engineering teams to ensure robust, scalable implementations Establish best practices for experimentation, model validation, monitoring, and lifecycle management Mentor and raise the technical bar for junior scientists through reviews, technical guidance, and thought leadership Communicate complex scientific insights clearly to senior leadership and cross-functional stakeholders Identify emerging scientific trends and translate them into impactful production solutions

Do you want to join an innovative team of scientists applying machine learning and advanced statistical techniques to protect Amazon customers and enable a trusted eCommerce experience? Are you excited about modeling terabytes of data and building state-of-the-art algorithms to solve complex, real-world fraud and risk challenges? Do you enjoy owning end-to-end machine learning problems, directly influencing customer experience and company profitability, while collaborating in a diverse, high-performing team? If so, the Amazon Buyer Risk Prevention (BRP) Machine Learning team may be the right fit for you. We are seeking an Applied Scientist to design, develop, and deploy advanced algorithmic systems that safeguard millions of transactions every day. In this role, you will independently drive model development from problem formulation to production deployment, build scalable ML solutions, and leverage emerging technologies—including Generative AI and LLMs—to enhance fraud detection and next-generation risk prevention systems. Key job responsibilities Own end-to-end development of machine learning models for large-scale risk management systems Analyze large volumes of historical and real-time data to identify fraud patterns and emerging risk trends Design, develop, validate, and deploy innovative models to production environments Apply GenAI/LLM technologies to automate risk evaluation and improve operational efficiency Collaborate closely with software engineering teams to implement scalable, real-time model solutions Partner with operations and business stakeholders to translate risk insights into measurable impact Establish scalable and automated processes for data analysis, model experimentation, validation, and monitoring Track model performance and business metrics; communicate insights clearly to technical and non-technical stakeholders Research and implement novel machine learning and statistical methodologies

Do you want to join an innovative team of scientists applying machine learning and advanced statistical techniques to protect Amazon customers and enable a trusted eCommerce experience? Are you excited about modeling terabytes of data and building state-of-the-art algorithms to solve complex, real-world fraud and risk challenges? Do you enjoy owning end-to-end machine learning problems, directly influencing customer experience and company profitability, while collaborating in a diverse, high-performing team? If so, the Amazon Buyer Risk Prevention (BRP) Machine Learning team may be the right fit for you. We are seeking an Applied Scientist to design, develop, and deploy advanced algorithmic systems that safeguard millions of transactions every day. In this role, you will independently drive model development from problem formulation to production deployment, build scalable ML solutions, and leverage emerging technologies—including Generative AI and LLMs—to enhance fraud detection and next-generation risk prevention systems. Key job responsibilities Own end-to-end development of machine learning models for large-scale risk management systems Analyze large volumes of historical and real-time data to identify fraud patterns and emerging risk trends Design, develop, validate, and deploy innovative models to production environments Apply GenAI/LLM technologies to automate risk evaluation and improve operational efficiency Collaborate closely with software engineering teams to implement scalable, real-time model solutions Partner with operations and business stakeholders to translate risk insights into measurable impact Establish scalable and automated processes for data analysis, model experimentation, validation, and monitoring Track model performance and business metrics; communicate insights clearly to technical and non-technical stakeholders Research and implement novel machine learning and statistical methodologies

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 ABOUT AWS: 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. Why AWS Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. 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 in the cloud. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity and AmazeCon conferences, inspire us to never stop embracing our uniqueness. Mentorship and 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.

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 ABOUT AWS: 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. Why AWS Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. 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 in the cloud. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity and AmazeCon conferences, inspire us to never stop embracing our uniqueness. Mentorship and 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.

Are you a scientist interested in pushing the state of the art in machine learning and recommendation systems? Are you interested in working on novel ideas that can positively impact millions of customers? Do you wish you had access to large datasets and tremendous computational resources? Answer yes to any of these questions and you will be a great fit for our team at Amazon. As an Senior Applied Scientist in our team, you will be responsible for the research, design, and development of new AI technologies for Personalization. You will adopt or invent new machine learning and analytical techniques in the realm of recommendations and large language models. You will collaborate with scientists, engineers, and product partners locally and abroad. Your work will include inventing, experimenting with, and launching new features, products and systems. Key job responsibilities - Using Amazon’s large-scale computing resources, you will ask research questions about customer behavior, build state-of-the-art models to optimize the shopping experience, and run these models directly on the retail website. - Develop AI solutions for Recommendation systems using Deep learning, LLMs, Reinforcement Learning, distillation, and Optimization methods; - Work closely with engineers and product managers to design, implement and launch AI solutions end-to-end; - Design and conduct offline and online (A/B) experiments to evaluate proposed solutions based on in-depth data analyses; - Effectively communicate technical and non-technical ideas with teammates and stakeholders; - Stay up-to-date with advancements and the latest modeling techniques in the field; - Publish your research findings in top conferences and journals. About the team Our team is part of Amazon’s Personalization organization, a high-performing group that leverages Amazon’s expertise in machine learning, big data, distributed systems, and user experience design to deliver the best shopping experiences for our customers. We run global experiments and our work has revolutionized e-commerce with features such as "Keep shopping for ...", “Customers who bought this item also bought”, and “Frequently bought together”.