Careers

Do you enjoy solving challenging problems and driving innovations in research? Do you want to create scalable optimization models and apply machine learning techniques to guide real-world decisions? We are looking for builders, innovators, and entrepreneurs who want to bring their ideas to reality and improve the lives of millions of customers. As a Research Science intern focused on Operations Research and Optimization intern, you will be challenged to apply theory into practice through experimentation and invention, develop new algorithms using modeling software and programming techniques for complex problems, implement prototypes and work with massive datasets. As you navigate through complex algorithms and data structures, you'll find yourself at the forefront of innovation, shaping the future of Amazon's fulfillment, logistics, and supply chain operations. Imagine waking up each morning, fueled by the excitement of solving intricate puzzles that have a direct impact on Amazon's operational excellence. Your day might begin by collaborating with cross-functional teams, exchanging ideas and insights to develop innovative solutions. You'll then immerse yourself in a world of data, leveraging your expertise in optimization, causal inference, time series analysis, and machine learning to uncover hidden patterns and drive operational efficiencies. Throughout your journey, you'll have access to unparalleled resources, including state-of-the-art computing infrastructure, cutting-edge research papers, and mentorship from industry luminaries. This immersive experience will not only sharpen your technical skills but also cultivate your ability to think critically, communicate effectively, and thrive in a fast-paced, innovative environment where bold ideas are celebrated. Amazon has positions available for Operations Research Science Internships in, but not limited to, Bellevue, WA; Boston, MA; Cambridge, MA; New York, NY; Santa Clara, CA; Seattle, WA; Sunnyvale, CA. Key job responsibilities We are particularly interested in candidates with expertise in: Optimization, Causal Inference, Time Series, Algorithms and Data Structures, Statistics, Operations Research, Machine Learning, Programming/Scripting Languages, LLMs In this role, you ain hands-on experience in applying cutting-edge analytical techniques to tackle complex business challenges at scale. If you are passionate about using data-driven insights to drive operational excellence, we encourage you to apply. The ideal candidate should possess the ability to work collaboratively with diverse groups and cross-functional teams to solve complex business problems. A successful candidate will be a self-starter, comfortable with ambiguity, with strong attention to detail and the ability to thrive in a fast-paced, ever-changing environment. A day in the life Develop and apply optimization, causal inference, and time series modeling techniques to drive operational efficiencies and improve decision-making across Amazon's fulfillment, logistics, and supply chain operations Design and implement scalable algorithms and data structures to support complex optimization systems Leverage statistical methods and machine learning to uncover insights and patterns in large-scale operations data Prototype and validate new approaches through rigorous experimentation and analysis Collaborate closely with cross-functional teams of researchers, engineers, and business stakeholders to translate research outputs into tangible business impact

The AWS Partner Intelligence Science team is hiring an Applied Scientist to develop science products that support AWS initiatives to grow AWS Partners. The team is seeking candidates with strong background in machine learning and engineering, creativity, curiosity, and great business judgment. As an applied scientist on the team, you will work on targeting and lead prioritization related AI/ML products, recommendation systems, and deliver them into the production ecosystem. You are comfortable with ambiguity and have a deep understanding of ML algorithms and an analytical mindset. You are capable of summarizing complex data and models through clear visual and written explanations. You thrive in a collaborative environment and are passionate about learning. Key job responsibilities - Work with customers, product managers, scientists, and engineers to deliver high-quality science products - Experiment with large amounts of data to deliver the best possible science solutions - Design, build, and deploy innovative ML solutions to impact AWS Co-Sell initiatives About the team The AWS Partner Intelligence team is the center of Analytics, Insights, and Science supporting the AWS Specialist Partner Organization on its mission to provide customers with an outstanding experience while working with AWS partners. The Partner Intelligence Science team builds science solutions to boost productivity and accelerate AWS and AWS partners' revenue growth.

The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Applied Scientist with a strong deep learning background, to build industry-leading technology with Large Language Models (LLMs) and multi-modal systems. You will support projects that work on cutting edge technologies including multi-modal model alignment, moderation systems and evaluation. Key job responsibilities As an Applied Scientist with the AGI team, you will support the development of novel algorithms and modeling techniques, to advance the state of the art with LLMs. Your work will directly impact our customers in the form of products and services that make use of speech and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in generative artificial intelligence (GenAI). You are also expected to publish in top tier conferences. About the team The AGI team has a mission to push the envelope in LLMs and multimodal systems. Specifically, we focus on model alignment with an aim to maintain safety while not denting utility, in order to provide the best-possible experience for our customers.

Unlock the Future with Amazon Science! Calling all visionary minds passionate about the transformative power of machine learning! Amazon is seeking boundary-pushing graduate student scientists who can turn revolutionary theory into awe-inspiring reality. Join our team of visionary scientists and embark on a journey to revolutionize the field by harnessing the power of cutting-edge techniques in bayesian optimization, time series, multi-armed bandits and more. At Amazon, we don't just talk about innovation – we live and breathe it. You'll conducting research into the theory and application of deep reinforcement learning. You will work on some of the most difficult problems in the industry with some of the best product managers, scientists, and software engineers in the industry. You will propose and deploy solutions that will likely draw from a range of scientific areas such as supervised, semi-supervised and unsupervised learning, reinforcement learning, advanced statistical modeling, and graph models. Throughout your journey, you'll have access to unparalleled resources, including state-of-the-art computing infrastructure, cutting-edge research papers, and mentorship from industry luminaries. This immersive experience will not only sharpen your technical skills but also cultivate your ability to think critically, communicate effectively, and thrive in a fast-paced, innovative environment where bold ideas are celebrated. Join us at the forefront of applied science, where your contributions will shape the future of AI and propel humanity forward. Seize this extraordinary opportunity to learn, grow, and leave an indelible mark on the world of technology. Amazon has positions available for Machine Learning Applied Science Internships in, but not limited to Arlington, VA; Bellevue, WA; Boston, MA; New York, NY; Palo Alto, CA; San Diego, CA; Santa Clara, CA; Seattle, WA. Key job responsibilities We are particularly interested in candidates with expertise in: Optimization, Programming/Scripting Languages, Statistics, Reinforcement Learning, Causal Inference, Large Language Models, Time Series, Graph Modeling, Supervised/Unsupervised Learning, Deep Learning, Predictive Modeling In this role, you will work alongside global experts to develop and implement novel, scalable algorithms and modeling techniques that advance the state-of-the-art in areas at the intersection of Reinforcement Learning and Optimization within Machine Learning. You will tackle challenging, groundbreaking research problems on production-scale data, with a focus on developing novel RL algorithms and applying them to complex, real-world challenges. The ideal candidate should possess the ability to work collaboratively with diverse groups and cross-functional teams to solve complex business problems. A successful candidate will be a self-starter, comfortable with ambiguity, with strong attention to detail and the ability to thrive in a fast-paced, ever-changing environment. A day in the life - Develop scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation. - Design, development and evaluation of highly innovative ML models for solving complex business problems. - Research and apply the latest ML techniques and best practices from both academia and industry. - Think about customers and how to improve the customer delivery experience. - Use and analytical techniques to create scalable solutions for business problems.

Are you a PhD student interested in machine learning, natural language processing, computer vision, automated reasoning, or robotics? We are looking for skilled scientists capable of putting theory into practice through experimentation and invention, leveraging science techniques and implementing systems to work on massive datasets in an effort to tackle never-before-solved problems. A successful candidate will be a self-starter comfortable with ambiguity, strong attention to detail, and the ability to work in a fast-paced, ever-changing environment. As an Applied Science Intern, you will own the design and development of end-to-end systems. You’ll have the opportunity to create technical roadmaps, and drive production level projects that will support Amazon Science. You will work closely with Amazon scientists, and other science interns to develop solutions and deploy them into production. The ideal scientist must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. Amazon Science gives insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists use our working backwards method to enrich the way we live and work. To ensure a great internship experience, please keep these things in mind. This is a full time internship and requires an individual to work 40 hours a week for the duration of the internship. Amazon requires an intern to be located where their assigned team is. Amazon is happy to provide relocation and housing assistance if you are located 50 miles or further from the office location. For more information on the Amazon Science community please visit https://www.amazon.science.

Do you have a passion for data? Are you matriculating in a Master’s or PhD program? Amazon is looking for driven data science students with strong modeling skills who are comfortable owning and executing data. To be successful in this internship, you will need the ability to develop, automate, and run analytical models for our systems. During this internship, you will build tools and support structures needed to analyze and dive deep into data to resolve systems errors and changes. You will have the ability to present your findings to our business partners and help drive improvements. Previous applicants demonstrated the aptitude to manage medium-scale modeling projects, identified requirements, and built methodology/tools that were statistically grounded. For more information on the Amazon Science community please visit https://www.amazon.science

The Automated Reasoning Group is looking for a Senior Applied Scientist with expertise in programming language semantics and deductive verification techniques (e.g. Lean, Dafny) to deliver novel code reasoning capabilities at scale. You will be part of a larger organization that develops a spectrum of formal software analysis tools and applies them to software at all levels of abstraction from assembler through high-level programming languages. You will work with a team of world class automated reasoning experts to deliver code reasoning technology that is powerful yet accessible to all developers. About the team 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, including support for customers who require specialized security solutions for their cloud services. 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. 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. 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. 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. Hybrid Work We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices.

Are you excited about leveraging state-of-the-art Deep Learning, Recommender Systems, Information Retrieval, Natural Language Processing algorithms on large datasets to solve real-world problems? As an Applied Scientist Intern, you will be working in the closest Amazon offices to you (Sydney, Melbourne, Adelaide, Brisbane) in a fast-paced, cross-disciplinary team of experienced R&D scientists. You will take on complex problems, work on solutions that leverage existing academic and industrial research, and utilize your own out-of-the-box pragmatic thinking. In addition to coming up with novel solutions and prototypes, you may even deliver these to production in customer facing products. Key job responsibilities - Develop novel solutions and build prototypes - Work on complex problems in Machine Learning and Information Retrieval - Contribute to research that could significantly impact Amazon operations - Collaborate with a diverse team of experts in a fast-paced environment - Collaborate with scientists on writing and submitting papers to top conferences, e.g. NeurIPS, ICML, KDD, SIGIR - Present your research findings to both technical and non-technical audiences Key Opportunities: - Work in a team of ML scientists to solve recommender systems problems at the scale of Amazon - Access to Amazon services and hardware - Become a disruptor, innovator, and problem solver in the field of information retrieval and recommender systems - Potentially deliver solutions to production in customer-facing applications - Opportunities to be hired full-time after the internship Join us in shaping the future of AI at Amazon. Apply now and turn your research into real-world solutions!

Amazon’s Automated Inventory Management (AIM) team is looking for passionate, hard-working, and talented individuals to join our fast paced, stimulating environment to help invent the future of business ownership with Technology, and to translate big data into actionable insights. The AIM team is part of the Supply Chain Optimization Technology (SCOT) Team within the Operations Organization. As an Applied Scientist on the AIM team, you will design quantitative systems, prediction models and solve real world problems using the latest machine learning techniques. You will also work with a team of Product Managers, Business Intelligence Engineers and Software Engineers to research and build solutions to provide insights to business leaders at the most senior levels throughout the company. Key job responsibilities Implement statistical and machine learning methods to solve complex business problems Research new ways to improve predictive and explanatory models Directly contribute to the design and development of automated prediction systems and ML infrastructure Build models that can detect supply chain defects and explain variance to the optimal state Collaborate with other researchers, software developers, and business leaders to define the scientific roadmap for this team

We are seeking an Applied Scientist to develop innovative perception and machine learning solutions for robot workcells in Amazon Fulfillment centers. In this role, you will leverage advanced sensor technologies to develop and implement state-of-the art ML models to for scene understanding and objection localization. Your solutions will allow Amazon to increase productivity and efficiency while prioritizing employee safety. Key job responsibilities - Design and implement advanced machine learning models for perception tasks such as object detection and scene understanding - Optimize and deploy the ML models on edge devices - Build and test prototype robotic workcell setups to validate the performance of the solution - Work with cross-functional teams to provide inputs and recommendations for the optimal sensor suite to enable a robust solution - Collaborate with Amazon's robotics engineering and operations teams to understand their requirements and develop tailored solutions - Document the architecture, performance, and validation of the final system A day in the life Amazon offers a full range of benefits for you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!