Five ways Amazon is preparing for the energy demands of the future

From investing in new carbon-free energy projects to advocating for grid modernization and collaborating with key stakeholders around the world, Amazon is working toward a cleaner energy future.

As our society relies on technology more than ever, from consumer electronics to large-scale infrastructure in both public and private sectors, global energy demands are continuing to grow. At Amazon, we’re working to meet the future energy demands of our customers and our business while remaining committed to our Climate Pledge to become net-zero carbon by 2040. We know the path forward is changing, and our work to decarbonize our operations won’t be linear, so we’re constantly experimenting, learning, and evolving.

Here are five ways Amazon is innovating to ensure our energy needs are met with sustainability and efficiency in mind:

  1. Matching 100% of the electricity consumed by our operations with renewable energy

    Amazon achieved our goal to match all of the electricity consumed by our operations with 100% renewable energy. We originally pledged to reach this goal in 2030, and achieved it seven years early in 2023. In order to achieve this ambitious goal, we’ve invested in more than 600+ solar and wind projects around the world, representing more than 34 gigawatts (GW) of new energy capacity once operational. Once all of these projects become operational, they’re expected to produce enough energy to power more than 8.3 million average U.S. homes each year. We’ve also been the world’s largest corporate purchaser of renewable energy every year since 2020.

    Looking ahead, increasing energy demands—including those driven by generative AI—will require us to add more sources of carbon-free energy, including nuclear, offshore wind, green hydrogen, and more. In addition, Amazon’s $2 billion Climate Pledge Fund is investing in the next generation of emerging low-carbon energy technologies, including green ammonia, renewable transportation fuels, portable battery storage, and other innovations that can help power the future energy needs of our business and the transition to a lower-carbon economy.

  2. Advocating for grid modernization

    In most cases, when we invest in new carbon-free energy projects like wind and solar farms, that energy goes into the public power grids in those areas—meaning those communities are also benefitting. We want electric grids where we operate to be net-zero carbon for everyone. But right now, grids across the country are limited in how much energy they can accept. While we’re working with utilities and energy companies to fast-forward new solar, wind, and other carbon-free energy projects to meet rising demand, the grid also needs to be modernized so it can handle that demand. More than 70% of the U.S. grid is 25 years old or older, and across the United States, there are currently more than 2.6 million megawatts (MW) of renewable energy and storage projects waiting to come online—nearly double the current amount of U.S. generation capacity, or enough carbon-free energy to power 63.3 million US homes. To help address this, Amazon teams are engaging with energy regulators and other officials at the federal and state levels to help support grid modernization, remove permitting obstacles, and deploy grid-enhancing technologies.

    We’re also working with grid operators and utilities to help ensure grid modernization is funded in the markets where we do business. Like all ratepayers, Amazon pays transmission costs for the energy we use, and those rates are established by utility regulators. Those costs help cover infrastructure upgrades and other grid modernization needs required to support the needs of all energy users.

  3. Deploying renewable energy where it’s needed most

    To have the biggest impact, we focus most of our investments on the grids where our operations are concentrated, as well as regions where the existing grid is most carbon intensive. For example, we have a large AWS presence in Oregon, so we’re working with utility company Umatilla Electric to procure new sources of renewable energy, such as electricity purchased from a local wind farm, to help increase the amount of renewable energy to the local grid.

    We also make a point to invest in renewables projects in places that otherwise rely heavily on fossil fuels like coal, oil, and natural gas to power their grids, such as India, Poland, and the southeastern U.S. To support this effort, Amazon cofounded the Emissions First Partnership, a coalition of companies committed to modernizing the greenhouse gas accounting standards for the power sector, which will encourage companies to invest in renewable and carbon-free energy in more carbon-intensive grids. Both of these approaches help reduce energy-related emissions and match the electricity used by our operations with renewable energy, a win-win for people and the planet.

  4. Taking steps to run our data centers more efficiently

    We’re constantly reevaluating how our data centers operate and determining ways to help them run on less energy and be more efficient. And as the world scales our use of AI, it's important to also minimize its environmental footprint. A new study by Accenture shows that an effective way to do that is by moving IT workloads from on-premises infrastructure to AWS data centers around the globe. The research estimates AWS’s infrastructure is up to 4.1 times more efficient than on-premises, and when workloads are optimized on AWS, the associated carbon footprint can be reduced by up to 99%. This type of impact is possible by AWS optimizing our data center design, investing in purpose-built chips, and innovating with new cooling technologies. For example, we’ve taken steps to design our data centers to use natural air flow to lower server temperatures, which can heat up while in use. This allows us to use less air conditioning when possible. We’ve also designed our AWS machine learning chips, which power millions of workloads daily, to be more energy efficient. For example, AWS’s Graviton processor delivers high performance with high levels of energy efficiency. Graviton4 provides up to 30% better computing performance, 50% more cores, and 75% more memory bandwidth than current-generation Graviton3 processors, delivering the best price performance and energy efficiency for a broad range of workloads running on Amazon EC2. We’re also keeping technologies in use longer by increasing the lifespan of our servers from five to six years.

  5. Incorporating sustainability practices into the design and construction of our buildings

    We’re working to design our corporate buildings in ways that support the transition to net-zero carbon, including by constructing new buildings using low-carbon concrete and electrified HVAC systems. One of our newest Same-Day fulfillment centers in California is set to make history as the world’s first fulfillment facility to achieve Zero Carbon Certification status. The electricity used by our HQ2 headquarters is matched with 100% renewable energy from a local solar farm and has achieved the highest level of LEED green building certification. We’ve also installed energy-efficient lighting, low-flow water fixtures, and implemented recycling and composting in our corporate offices. In Europe and in the U.S., our data centers are transitioning to renewable diesel in our generators, which can result in as much as 90% fewer greenhouse gas emissions over the fuel’s life cycle compared to diesel.

    Amazon is continuing to work toward transitioning our business and our society to a cleaner energy future.

Research areas

Related content

US, WA, Seattle
Revolutionize the Future of AI at the Frontier of Applied Science Are you a brilliant mind seeking to push the boundaries of what's possible with artificial intelligence? Join our elite team of researchers and engineers at the forefront of applied science, where we're harnessing the latest advancements in natural language processing, deep learning, and generative AI to reshape industries and unlock new realms of innovation. As an Applied Science Intern, you'll have the unique opportunity to work alongside world-renowned experts, gaining invaluable hands-on experience with cutting-edge technologies such as large language models, transformers, and neural networks. You'll dive deep into complex challenges, fine-tuning state-of-the-art models, developing novel algorithms for named entity recognition, and exploring the vast potential of generative AI. This internship is not just about executing tasks – it's about being a driving force behind groundbreaking discoveries. You'll collaborate with cross-functional teams, leveraging your expertise in statistics, recommender systems, and question answering to tackle real-world problems and deliver impactful solutions. 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 LLM & GenAI Applied Science Internships in, but not limited to, Bellevue, WA; Boston, MA; Cambridge, MA; New York, NY; Santa Clara, CA; Seattle, WA; Sunnyvale, CA; Pittsburgh, PA. Key job responsibilities We are particularly interested in candidates with expertise in: LLMs, NLP/NLU, Gen AI, Transformers, Fine-Tuning, Recommendation Systems, Deep Learning, NER, Statistics, Neural Networks, Question Answering. 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 LLMs and GenAI. You will tackle challenging, groundbreaking research problems on production-scale data, with a focus on recommendation systems, question answering, deep learning and generative AI. 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 - Collaborate with cross-functional teams to tackle complex challenges in natural language processing, computer vision, and generative AI. - Fine-tune state-of-the-art models and develop novel algorithms to push the boundaries of what's possible. - Explore the vast potential of generative AI and its applications across industries. - Attend cutting-edge research seminars and engage in thought-provoking discussions with industry luminaries. - Leverage state-of-the-art computing infrastructure and access to the latest research papers to fuel your innovation. - Present your groundbreaking work and insights to the team, fostering a culture of knowledge-sharing and continuous learning.
US, WA, Seattle
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.
US, WA, Seattle
Shape the Future of Human-Machine Interaction Are you a master of natural language processing, eager to push the boundaries of conversational AI? Amazon is seeking exceptional graduate students to join our cutting-edge research team, where they will have the opportunity to explore and push the boundaries of natural language processing (NLP), natural language understanding (NLU), and speech recognition technologies. Imagine waking up each morning, fueled by the excitement of tackling complex research problems that have the potential to reshape the world. You'll dive into production-scale data, exploring innovative approaches to natural language understanding, large language models, reinforcement learning with human feedback, conversational AI, and multimodal learning. Your days will be filled with brainstorming sessions, coding sprints, and lively discussions with brilliant minds from diverse backgrounds. 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 Natural Language Processing & Speech Applied 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: NLP/NLU, LLMs, Reinforcement Learning, Human Feedback/HITL, Deep Learning, Speech Recognition, Conversational AI, Natural Language Modeling, Multimodal Learning. 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 Natural Language Processing and Speech Technologies. You will tackle challenging, groundbreaking research problems on production-scale data, with a focus on natural language processing, speech recognition, text-to-speech (TTS), text recognition, question answering, NLP models (e.g., LSTM, transformer-based models), signal processing, information extraction, conversational modeling, audio processing, speaker detection, large language models, multilingual modeling, and more. 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 novel, scalable algorithms and modeling techniques that advance the state-of-the-art in natural language processing, speech recognition, text-to-speech, question answering, and conversational modeling. - Tackle groundbreaking research problems on production-scale data, leveraging techniques such as LSTM, transformer-based models, signal processing, information extraction, audio processing, speaker detection, large language models, and multilingual modeling. - Collaborate with cross-functional teams to solve complex business problems, leveraging your expertise in NLP/NLU, LLMs, reinforcement learning, human feedback/HITL, deep learning, speech recognition, conversational AI, natural language modeling, and multimodal learning. - Thrive in a fast-paced, ever-changing environment, embracing ambiguity and demonstrating strong attention to detail.
US, WA, Seattle
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 will gain 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
US, CA, San Francisco
Are you a brilliant mind seeking to push the boundaries of what's possible with intelligent robotics? Join our elite team of researchers and engineers - led by Pieter Abeel, Rocky Duan, and Peter Chen - at the forefront of applied science, where we're harnessing the latest advancements in large language models (LLMs) and generative AI to reshape the world of robotics and unlock new realms of innovation. As an Applied Science Intern, you'll have the unique opportunity to work alongside world-renowned experts, gaining invaluable hands-on experience with cutting-edge robotics technologies. You'll dive deep into exciting research projects at the intersection of AI and robotics. This internship is not just about executing tasks – it's about being a driving force behind groundbreaking discoveries. You'll collaborate with cross-functional teams, leveraging your expertise in areas such as deep learning, reinforcement learning, computer vision, and motion planning to tackle real-world problems and deliver impactful solutions. 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 robotics and AI, where your contributions will shape the future of intelligent systems and propel humanity forward. Seize this extraordinary opportunity to learn, grow, and leave an indelible mark on the world of technology. Must be eligible and available for a full-time (40h/ week) 12 week internship between May 2026 and September 2026. Amazon has positions available in San Francisco, CA and Seattle, WA. The ideal candidate should possess: - Strong background in machine learning, deep learning, and/or robotics - Publication record at science conferences such as NeurIPS, CVPR, ICRA, RSS, CoRL, and ICLR. - Experience in areas such as multimodal LLMs, world models, image/video tokenization, real2Sim/Sim2real transfer, bimanual manipulation, open-vocabulary panoptic scene understanding, scaling up multi-modal LLMs, and end-to-end vision-language-action models. - Proficiency in Python, Experience with PyTorch or JAX - Excellent problem-solving skills, attention to detail, and the ability to work collaboratively in a team Apply now and embark on an extraordinary journey of discovery and innovation! Key job responsibilities - Develop novel, scalable algorithms and modeling techniques that advance the state-of-the-art in areas at the intersection of LLMs and generative AI for robotics - Tackle challenging, groundbreaking research problems on production-scale data, with a focus on robotic perception, manipulation, and control - Collaborate with cross-functional teams to solve complex business problems, leveraging your expertise in areas such as deep learning, reinforcement learning, computer vision, and motion planning - Demonstrate the ability to work independently, thrive in a fast-paced, ever-changing environment, and communicate effectively with diverse stakeholders
US, WA, Seattle
Unleash Your Potential at the Forefront of AI Innovation At Amazon, we're on a mission to revolutionize the way the world leverages machine learning. Amazon is seeking graduate student scientists who can turn revolutionary theory into awe-inspiring reality. As an Applied Science Intern focused on Information and Knowledge Management in Machine Learning, you will play a critical role in developing the systems and frameworks that power Amazon's machine learning capabilities. You'll be at the epicenter of this transformation, shaping the systems and frameworks that power our cutting-edge AI capabilities. Imagine a role where you develop intuitive tools and workflows that empower machine learning teams to discover, reuse, and build upon existing models and datasets, accelerating innovation across the company. You'll leverage natural language processing and information retrieval techniques to unlock insights from vast repositories of unstructured data, fueling the next generation of AI applications. 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: Knowledge Graphs and Extraction, Neural Networks/GNNs, Data Structures and Algorithms, Time Series, Machine Learning, Natural Language Processing, Deep Learning, Large Language Models, Graph Modeling, Knowledge Graphs and Extraction, Programming/Scripting Languages In this role, you'll collaborate with brilliant minds to develop innovative frameworks and tools that streamline the lifecycle of machine learning assets, from data to deployed models in areas at the intersection of Knowledge Management within Machine Learning. You will conduct groundbreaking research into emerging best practices and innovations in the field of ML operations, knowledge engineering, and information management, proposing novel approaches that could further enhance Amazon's machine learning capabilities. 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.
US, CA, Sunnyvale
As a Principal Scientist within the Artificial General Intelligence (AGI) organization, you are a trusted part of the technical leadership. You bring business and industry context to science and technology decisions, set the standard for scientific excellence, and make decisions that affect the way we build and integrate algorithms. A Principal Applied Scientist will solicit differing views across the organization and are willing to change your mind as you learn more. Your artifacts are exemplary and often used as reference across organization. You are a hands-on scientific leader; develop solutions that are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility; and tackle intrinsically hard problems, acquiring expertise as needed. Principal Applied Scientists are expected to decompose complex problems into straightforward solutions. You amplify your impact by leading scientific reviews within your organization or at your location; and scrutinize and review experimental design, modeling, verification and other research procedures. You also probe assumptions, illuminate pitfalls, and foster shared understanding; align teams toward coherent strategies; and educate keeping the scientific community up to date on advanced techniques, state of the art approaches, the latest technologies, and trends. AGI Principal Applied Scientists help managers guide the career growth of other scientists by mentoring and play a significant role in hiring and developing scientists and leads. You will play a critical role in driving the development of Generative AI (GenAI) technologies that can handle Amazon-scale use cases and have a significant impact on our customers' experiences. Key job responsibilities You will be responsible for defining key research directions, inventing new machine learning techniques, conducting rigorous experiments, and ensuring that research is translated into practice. You will develop long-term strategies, persuade teams to adopt those strategies, propose goals and deliver on them. A Principal Applied Scientist will participate in organizational planning, hiring, mentorship and leadership development. You will also be build scalable science and engineering solutions, and serve as a key scientific resource in full-cycle development (conception, design, implementation, testing to documentation, delivery, and maintenance). A day in the life About the team Amazon’s AGI team is focused on building foundational AI to solve real-world problems at scale, delivering value to all existing businesses in Amazon, and enabling entirely new services and products for people and enterprises around the world.
GB, London
Are you a MS or PhD student interested in a 2026 internship in the field of machine learning, deep learning, generative AI, large language models and speech technology, robotics, computer vision, optimization, operations research, quantum computing, automated reasoning, or formal methods? If so, we want to hear from you! We are looking for students interested in using a variety of domain expertise to invent, design and implement state-of-the-art solutions for never-before-solved problems. You can find more information about the Amazon Science community as well as our interview process via the links below; https://www.amazon.science/ https://amazon.jobs/content/en/career-programs/university/science https://amazon.jobs/content/en/how-we-hire/university-roles/applied-science Key job responsibilities As an Applied Science Intern, you will own the design and development of end-to-end systems. You’ll have the opportunity to write technical white papers, create 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. You will have the opportunity to design new algorithms, models, or other technical solutions whilst experiencing Amazon’s customer focused culture. The ideal intern must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. A day in the life At Amazon, you will grow into the high impact person you know you’re ready to be. Every day will be filled with developing new skills and achieving personal growth. How often can you say that your work changes the world? At Amazon, you’ll say it often. Join us and define tomorrow. Some more benefits of an Amazon Science internship include; • All of our internships offer a competitive stipend/salary • Interns are paired with an experienced manager and mentor(s) • Interns receive invitations to different events such as intern program initiatives or site events • Interns can build their professional and personal network with other Amazon Scientists • Interns can potentially publish work at top tier conferences each year About the team Applicants will be reviewed on a rolling basis and are assigned to teams aligned with their research interests and experience prior to interviews. Start dates are available throughout the year and durations can vary in length from 3-6 months for full time internships. This role may available across multiple locations in the EMEA region (Austria, Estonia, France, Germany, Ireland, Israel, Italy, Jordan, Luxembourg, Netherlands, Poland, Romania, Spain, South Africa, UAE, and UK). Please note these are not remote internships.
US, CA, Sunnyvale
The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Applied Scientist with a strong deep learning background, to build Generative Artificial Intelligence (GenAI) technology with Large Language Models (LLMs) and multimodal systems. Key job responsibilities As an Applied Scientist with the AGI team, you will work with talented peers to support the development of GenAI 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 GenAI. About the team The AGI team has a mission to push the envelope with GenAI in LLMs and multimodal systems, in order to provide the best-possible experience for our customers.
US, WA, Seattle
Join us in the evolution of Amazon’s Seller business! The Seller Growth Science 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 growth 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, you will: - Identify opportunities to improve seller partner growth and development processes and translate those opportunities into science problems via principled statistical solutions (e.g. ML, causal inference). - Collaborate with senior scientists and contribute to maintaining high standards of technical rigor and excellence in MLOps. - Design and execute science projects to help seller partners have a delightful selling experience while creating long term value for our shoppers. - Work with engineering partners to meet latency and other system constraints. - Explore new technical and scientific directions under guidance, and drive projects to completion and delivery. - Communicate science innovations to the broader internal scientific community.