Careers

Amazon is looking for a talented Postdoctoral Scientist to join its AI Research on foundation models, large-scale representation learning, and distributed learning methods and systems for a one-year, full-time research position. At Amazon, you will invent, implement, and deploy state of the art machine learning algorithms and systems. You will build prototypes and innovate on new representation learning solutions. You will interact closely with our customers and with the academic and research communities. You will be at the heart of a growing and exciting focus area and work with other acclaimed engineers and world famous scientists. Large-scale foundation models have been the powerhouse in many of the recent advancements in computer vision, natural language processing, automatic speech recognition, recommendation systems, and time series modeling. Developing such models requires not only skillful modeling in individual modalities, but also understanding of how to synergistically combine them, and how to scale the modeling methods to learn with huge models and on large datasets. Join us to work as an integral part of a team that has diverse experiences in this space. We actively work on these areas: * Hardware-informed efficient model architecture, training objective and curriculum design * Distributed training, accelerated optimization methods * Continual learning, multi-task/meta learning * Reasoning, interactive learning, reinforcement learning * Robustness, privacy, model watermarking * Model compression, distillation, pruning, sparsification, quantization In this role, you will have the opportunity to: - Leverage machine learning models and advanced statistical techniques to extract valuable insights from historical data and comparable item information. - Tackle data scarcity challenges by developing innovative approaches to maximize the utility of available data sources. - Collaborate with cross-functional teams to develop and deploy production-ready solutions. - Participate in research activities, including publishing papers, attending conferences, and collaborating with academic institutions to advance the state-of-the-art in relevant fields. Key job responsibilities In this role you will: • Work closely with a senior science advisor, collaborate with other scientists and engineers, and be part of Amazon’s vibrant and diverse global science community. • Publish your innovation in top-tier academic venues and hone your presentation skills. • Be inspired by challenges and opportunities to invent cutting-edge techniques in your area(s) of expertise.

Transform analytics at global scale with cutting-edge AI/ML and GenAI - Join the founding team of the Science Center of Excellence at ShipTech Analytics! Revolutionize transportation analytics worldwide by leveraging the latest AI/ML research and technologies at Amazon ShipTech Analytics (STA). As a Sr. Applied Scientist, you'll spearhead initiatives to tackle critical business challenges, optimizing operations and driving innovation across Amazon's massive transportation network. - Pioneer the flagship AI-programs, employing traditional ML and GenAI to derive insights and recommendations for crucial metrics like Delivery Estimate Accuracy (DEA) - Optimize business review processes at scale, directly impacting operations for 100K+ Amazonians worldwide - Collaborate with top minds in AI/ML, working on complex, high-impact problems in the transportation domain - Drive innovation and thought leadership in supply chain analytics, shaping the future of Amazon's logistics operations. We're seeking motivated, multi-talented individuals passionate about pushing the boundaries of AI/ML and GenAI in transportation analytics. Join the founding team of STA's Science Center of Excellence and leave your mark on Amazon's global logistics operations. Apply now for this unique opportunity to transform analytics at an unprecedented scale! Key job responsibilities You will work closely with business/operations leaders, product managers, business intelligent engineers, software engineering leadership & senior engineers to build capabilities that transform our transportation analytics. This includes analyzing big data, building end-to-end analytics pipelines, prototype optimization/ML/simulation models, and launch production capabilities. You will have exposure to senior leadership as you communicate results and provide scientific guidance to the business. Your insights will be a key influencer of our product strategy and roadmap and your experimental research will inform our future investment areas.

AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new 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, Internet of Things (Iot), Platform, and Productivity Apps services in AWS. Within AWS UC, Amazon Dedicated Cloud (ADC) roles engage with AWS customers who require specialized security solutions for their cloud services. The AWS Center for Quantum Computing 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 a Senior Research Scientist to develop and test novel calibration and optimization tools for the operation of large scale quantum processors. You will be a technical leader on a team of engineers and scientists at the frontier of quantum processor control and error correction. You are expected to develop & lead high-impact research projects that intersect with our engineering roadmap. We are looking for candidates with strong engineering principles and resourcefulness. Organization and communication skills are essential. A day in the life 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. AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new 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, Internet of Things (Iot), Platform, and Productivity Apps services in AWS. Within AWS UC, Amazon Dedicated Cloud (ADC) roles engage with AWS customers who require specialized security solutions for their cloud services. 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 (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Diverse Experiences AWS 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.

At AWS, we build and operate AI services responsibly, driving measurable success along multiple Responsible AI dimensions, including safety, fairness, privacy, security, robustness, explainability, and transparency. As a Principal Applied Scientist on this team, you will contribute to: • Understanding in depth the technical and scientific issues related to safety, fairness, privacy, security, robustness, explainability, transparency, and other issues, in both "classical" and generative AI. • Developing new solutions and science best practices in Responsible AI. • Developing our research and innovation agenda. • Defining the strategies, priorities and metrics for technical progress in Responsible AI. • Building and developing the AWS team. • Driving adoption of new science and best practices among service teams

The Fulfillment by Amazon (FBA) and Supply Chain by Amazon (SCA) enable third-party sellers to use Amazon’s world-class science and logistics infrastructure to supply and fulfill customers world-wide with unprecedented fast delivery promise to customer. In doing so, sellers spend more time building great products, delight customers and grow their business. The FBA team is looking for a passionate, curious, and creative Principal Research Scientist with expertise in operations research, machine learning or statistics, along with a proven record of solving business problems through scalable modeling and analytical skills. As a lead research scientist in the team, you will be responsible for designing and implementing cutting edge optimization and ML models, building automated inventory, logistics and revenue management systems while collaborating with business and software teams to solve key challenges facing the worldwide FBA business. Such challenges include 1) designing end-to-end supply and demand management systems, ranging from capacity, inventory, and workforce management systems, 2) developing and improving optimization and ML models to help FBA sellers grow their business, 3) ensuring that worldwide Amazon customers have access to the largest selection of products through FBA sellers, and 4) driving out costs across end-to-end FBA supply chain. Unlike many companies who buy existing off-the-shelf planning systems, we design and build systems to suit Amazon’s particular needs. Our team members are on the forefront of supply chain thought leadership by working on some of the most difficult problems in the industry with some of the best product managers, research scientists, statisticians, economists and software developers in the business. We value individuals who exhibit deep technical proficiency, a desire for learning new areas, and a track record of delivering tangible results while fostering personal growth, team development, and career advancement. A day in the life In this pivotal role, you will be a technical leader in operations research or machine learning, with significant scope, impact, and visibility. Your solutions have the potential to drive billions of dollars in impact for Amazon's third-party seller business. As a senior scientist on the team, you will engage in every facet of the process—from idea generation, business analysis and scientific research to development and deployment of advanced models—granting you a profound sense of ownership. From day one, you will collaborate with experienced scientists, engineers, and product managers who are passionate about their work. Moreover, you will collaborate with Amazon's broader decision and research science community, enriching your perspective and mentoring fellow engineers and scientists. The successful candidate will have the strong expertise in applying operations research methodologies to address a wide variety of supply chain problems with millions of unique products involving hundreds of thousands of Selling Partners and tens of millions of customers worldwide. You will strive for simplicity, demonstrate judgment backed by mathematical rigor, as you continually seek opportunities to innovate, build, and deliver. Entrepreneurial spirit, adaptability to diverse roles, and agility in a fast-paced, high-energy, highly collaborative environment are essential. About the team Sellers play a vital role in Amazon’s ecosystem, integral to our mission of offering the Earth’s largest selection and lowest prices. FBA is a service that enables third-party sellers to outsource order fulfillment to Amazon, and leverage Amazon’s world-class facilities to provide customers Prime delivery promise. By partnering with Amazon, sellers benefit from powerful, cost-effective solutions that leverage our scale and technology, gain access to Prime members worldwide, increase their sales, and have more time to continue inventing amazing products for customers. With commitment to taking on even more of the supply chain and operational complexities on behalf of our selling partners, Amazon introduced Supply Chain by Amazon (SCA), an end-to-end, fully automated suite of supply chain services. This comprehensive solution empowers sellers to quickly and reliably transport products from manufacturing sites to customers worldwide. Amazon Warehousing and Distribution is a pivotal service in SCA, that provides best-in-class bulk storage and distribution services to sellers, ensuring they remain well-stocked across all their sale and fulfillment channels while reducing the total supply chain costs. The FBA team is the core group in charge of fulfillment, inventory management, pricing, and a diverse range of operational recommendation services for sellers, as well as building the internal resource management systems. We work to learn seller behavior, understand seller experience, build automated assistants to sellers, recommend right actions to sellers, design seller policies and incentives, and develop science products and services that empower third-party sellers to grow their businesses. To do so, we build and innovate science solutions at the intersection of machine learning, statistics, economics, operations research, and data analytics. We work full-stack, from foundational backend systems to future-forward user interfaces. Our culture is centered on rapid prototyping, rigorous experimentation, and data-driven decision-making.

Amazon Robotics is seeking a Principal Applied Scientist to develop state-of-the-art algorithms to control the fleet of 750,000 mobile robots in Amazon’s order fulfillment network. You will have the chance to solve complex planning and coordination problems and see your solutions come to life in Amazon’s warehouses! In this position, you will own the science of planning and scheduling fleet activities to achieve system-level objectives across a broad range of building types and workflows. You will improve the algorithms that control today’s global robotic fleet to unlock new opportunities for Amazon’s evolving network, as well as develop new capabilities from the ground up. You will explore how to leverage the power of our robotic mobility foundation model to predict the motion of the fleet to enable new ways of making decisions at scale. You will influence the design of future warehouses and the integration of new robotic technologies. This role offers the chance to have broad impact on the next wave of robotics You will collaborate with brilliant colleagues in a culture that values ingenuity, teamwork and delivering impact. Come join our mission to pioneer the future of automation! About the team Our multi-disciplinary science team includes scientists with backgrounds in simulation, planning and scheduling, grasping and manipulation, machine learning, and operations research. We develop novel planning algorithms and machine learning methods and apply them to real-word robotic warehouses, including: * Planning and coordinating the paths of thousands of robots * Dynamic allocation and scheduling of tasks to thousands of robots * Learning how to adapt system behavior to varying operating conditions * Co-design of robotic logistics processes and the algorithms to optimize them Our team also serves as a hub to foster innovation and support scientists across Amazon Robotics. We also coordinate research engagements with academia, such as the Robotics section of the Amazon Research Awards.

Join us in the evolution of Amazon’s Seller business! The Selling Partner Recruitment and Success organization is the growth and development engine for our Store. Partnering with business, product, and engineering, we catalyze SP growth with comprehensive and accurate data, unique insights, and actionable recommendations and collaborate with WW SP facing teams to drive adoption and create feedback loops. We strongly believe that any motivated SP should be able to grow their businesses and reach their full potential supported by Amazon tools and resources. We are looking for an Applied Scientist II to lead us to identify data-driven insight and opportunities to improve our SP recruitment strategy and drive new seller success. As a successful applied scientist on our talented team of scientists and engineers, you will solve complex problems to identify actionable opportunities, and collaborate with engineering, research, and business teams for future innovation. You need to be a sophisticated user and builder of statistical models and put them in production to answer specific business questions. You are an expert at synthesizing and communicating insights and recommendations to audiences of varying levels of technical sophistication. You will continue to contribute to the research community, by working with scientists across Amazon, as well as collaborating with academic researchers and publishing papers (www.aboutamazon.com/research). Key job responsibilities As an Applied Scientist on the team, you will: - Identify opportunities to improve SP recruitment and development process and translate those opportunities into science problems via principled statistical solutions (e.g. ML, causal, RL). - Mentor and guide the applied scientists in our organization and hold us to a high standard of technical rigor and excellence in MLOps. - Lead and execute roadmaps for complex science projects to help SP have a delightful selling experience while creating long term value for our shoppers. - Work with our engineering partners and draw upon your experience to meet latency and other system constraints. - Identify untapped, high-risk technical and scientific directions, and simulate new research directions that you will drive to completion and deliver. - Be responsible for communicating our science innovations to the broader internal & external scientific community.

Join us in the evolution of Amazon’s Seller business! The Selling Partner Recruitment and Success organization is the growth and development engine for our Store. Partnering with business, product, and engineering, we catalyze SP growth with comprehensive and accurate data, unique insights, and actionable recommendations and collaborate with WW SP facing teams to drive adoption and create feedback loops. We strongly believe that any motivated SP should be able to grow their businesses and reach their full potential supported by Amazon tools and resources. We are looking for a Senior Applied Scientist to lead us to identify data-driven insight and opportunities to improve our SP recruitment strategy and drive new seller success. As a successful applied scientist on our talented team of scientists and engineers, you will solve complex problems to identify actionable opportunities, and collaborate with engineering, research, and business teams for future innovation. You need to be a sophisticated user and builder of statistical models and put them in production to answer specific business questions. We prefer candidates with strong causal ML knowledge. You are an expert at synthesizing and communicating insights and recommendations to audiences of varying levels of technical sophistication. You will continue to contribute to the research community, by working with scientists across Amazon, as well as collaborating with academic researchers and publishing papers (www.aboutamazon.com/research). Key job responsibilities As a Sr. Applied Scientist in the team, you will: - Identify opportunities to improve SP growth and translate those opportunities into science problems via principled statistical solutions (e.g. ML, causal, RL). - Mentor and guide the applied scientists in our organization and hold us to a high standard of technical rigor and excellence in MLOps. - Design and lead roadmaps for complex science projects to help SP have a delightful selling experience while creating long term value for our shoppers. - Work with our engineering partners and draw upon your experience to meet latency and other system constraints. - Identify untapped, high-risk technical and scientific directions, and simulate new research directions that you will drive to completion and deliver. - Be responsible for communicating our science innovations to the broader internal & external scientific community.

Where will Amazon's growth come from in the next year? What about over the next five? Which product lines are poised to quintuple in size? Are we investing enough in our infrastructure, or too much? How do our customers react to changes in prices, product selection, or delivery times? These are among the most important questions at Amazon today. The Topline Forecasting team in the Supply Chain Optimization Technologies (SCOT) group is looking for innovative, passionate and results-oriented Principal Economist to provide thought-leadership to help answer these questions. You will have an opportunity to own the long-run outlook for Amazon’s global consumer business and shape strategic decisions at the highest level. The successful candidate will be able to formalize problem definitions from ambiguous requirements, build econometric models using Amazon’s world-class data systems, and develop cutting-edge solutions for non-standard problems. Key job responsibilities • You understand the state-of-the-art in time series and econometric modeling. • You apply econometric tools and theory to solve business problems in a fast moving environment. • You excel at extracting insights and correct interpretations from data using advanced modeling techniques. • You communicate insights in a digestible manner to senior leaders in Finance and Operations within the company. • You are able to anticipate future business challenges and key questions, and have the ability to design modeling solutions to tackle them. • You have broad influence over the Topline team’s scientific research agenda and deliverables. • You contribute to the broader Econ research community in Amazon. • You advise other economists on scientific best-practices and raise the bar of research. • You will actively mentor other scientists and contribute to their career development.

Amazon is looking for talented Postdoctoral Scientists to join our Stores Foundational AI team for a one-year, full-time research position. The Stores Foundational AI team builds foundation models for multiple Amazon entities, such as ASIN, customer, seller and brand. These foundation models are used in downstream applications by various partner teams in Stores. Our team also invests in building foundational large language models, which can power conversational applications as well as machine learning tasks with scarce data (zero/few-shot learning). The postdoc is expected to develop machine learning techniques for Large Language Model (LLM) Alignment. Currently, Alignment techniques for LLMs rely primarily on the annotation of preference between alternative responses followed by policy (LLM) optimization either directly (DPO-style) or after learning one or multiple reward functions (PPO-style). However, the data from such annotation is often noisy and confounded by ambiguity, subjectivity, and multi-dimensionality of preference. The goal of the project is to develop 1) high-quality data annotation procedures with clear instructions, 2) preference models which account for noisiness, ambiguity, subjectivity, and multi-dimensionality of preference annotation, and 3) appropriate algorithms for directly optimizing the policy (LLM) or appropriate loss functions for learning rewards using such preference models. Key job responsibilities • Work closely with a senior science advisor, collaborate with other scientists and engineers, and be part of Amazon’s vibrant and diverse global science community. • Publish your innovation in top-tier academic venues and hone your presentation skills. • Be inspired by challenges and opportunities to invent cutting-edge techniques in your area(s) of expertise.