Careers

AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we’re looking for talented people who want to help. You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion. Are you an experienced in sustainability science professional who is passionate about making a big impact? Are you interested in a high impact role at the world’s preeminent cloud computing company? The AWS Sustainability Science team is hiring a Sr. Sustainability Scientist. This role will support our Climate Pledge goal of net zero carbon by 2040 by developing scalable methods and models to assess and improve the environmental impacts of AWS data centers and cloud computing services from manufacturing, transportation, use, and end-of-life. This work will drive a deeper understanding of AWS’s environmental impacts, and enable strategic management of our carbon emissions. The ideal candidate will have industry experience in driving Life Cycle Assessments (LCAs) of products and services, possess a strong understanding of the GHG Protocol and carbon accounting practices, and have a detailed knowledge of hardware manufacturing, design, development, and/or sourcing. The candidate should be comfortable working with imperfect data, identifying sources of uncertainty, and finding public data to fill the gaps where needed. The successful candidate must have strong analytical skills and the ability to apply systems thinking to complex, fast moving problems. The candidate should have familiarity with LCA methods and applications. The successful candidate will act as a subject matter expert, including designing research, gathering data, interpreting results, and developing metrics and reports. The candidate will coordinate with cross-functional project teams in gathering and analyzing large amounts of data. Key job responsibilities In this role you will be responsible for: * Serving as an AWS subject matter expert in Sustainability * Developing Life Cycle Assessment (LCA) methodologies to ensure AWS has an accurate and credible basis for sustainability efforts. * Developing internal LCA models for AWS infrastructure and services including server hardware and mechanical and electrical systems * Conducting LCAs including research, data collection, modeling, data analysis, data visualization, and reporting to quantify environmental impacts of our data centers and cloud computing services * Developing reports, dashboards and metrics which distill complex data into actionable insights to inform improvements * Building and developing relationships with internal and external stakeholders to drive programs to completion * Work closely with software engineering teams to drive real-time model implementations and new features * Having fun and working hard! A day in the life Each day you will interact with different teams responsible for all aspects of hardware and data centers. Your work will span the life cycle of our operations and allow you to influence how we develop and implement sustainability practices. You will have the opportunity to work on projects locally and globally. About the team 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. 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. 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. 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 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.

Amazon is investing heavily in building a world class advertising business and we are responsible for defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities. The Sponsored Brands Advertiser Control team is a versatile environment, with a wide variety of challenges. We guide advertisers to make informed decisions by sharing insights and forecasts. We help advertisers deliver effective campaigns automatically by optimizing bids and targets on behalf of them. We enable advertisers to achieve brand advertising goals with maximum efficiency. We look at mega size data from both retail and advertising space, and coming up with ML and DL based science solutions through multiple products. In this role you will: - Research and build innovative machine learning and deep learning models utilizing the latest technologies such as LLM to provide personalized targeting, real-time forecasting and simplify campaign creation and management - Develop optimization solutions to automate bidding , targeting and budgeting on behalf of advertisers - Perform hands-on big data analysis and modeling to develop insights that increase advertiser monetization and merchandise sales without compromising shopper experience. - Design and run A/B experiments that affect hundreds of millions of customers, evaluate the impact of your optimizations and communicate your results to various business stakeholders. - Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving. - Write production code to bring models into production. - Work closely with software engineers on detailed requirements, technical designs and implementation of end-to-end solutions in production. - Work with scientists and economists to model the interaction between organic sales and sponsored content and to further evolve Amazon's marketplace. Why you love this opportunity Amazon is investing heavily in building a world-class advertising business. This team is responsible for defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate. Impact and Career Growth You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven fundamentally from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us

The Supply Chain Optimization Technologies (SCOT) team builds technology to automate and optimize Amazon’s supply chain of physical goods. We seek a Data Scientist with strong analytical and communication skills to join our team. SCOT manages Amazon's inventory under uncertainty of demand, pricing, promotions, supply, vendor lead times, and product life cycle. We optimize complex trade-offs between customer experience, inventory costs, fulfillment costs, fulfillment center capacity, etc. We develop sophisticated algorithms that involve learning from large amounts of data such as prices, promotions, similar products, and other data from our product catalog in order to automatically act on millions of dollars’ worth of inventory weekly and establish plans for tens of thousands of employees. As a Data Scientist, you will contribute to the research community, by working with other scientists across Amazon and our Supply Chain, as well as collaborating with academic researchers and publishing papers both internally and externally. Key job responsibilities Major responsibilities include: - Analysis of large amounts of data from different parts of the supply chain and their associated business functions - Improving upon existing machine learning methodologies by developing new data sources, developing and testing model enhancements, running computational experiments, and fine-tuning model parameters for new models - Formalizing assumptions about how models are expected to behave, creating definitions of outliers, developing methods to systematically identify these outliers, and explaining why they are reasonable or identifying fixes for them - Communicating verbally and in writing to business customers with various levels of technical knowledge, educating them about our research, as well as sharing insights and recommendations - Utilizing code (Python, R, Scala, etc.) for analyzing data and building statistical and machine learning models and algorithms A day in the life As a Data Scientist in SCOT, you will be tasked to understand and work with cutting edge research to enable the implementation of sophisticated models on big data. As a successful data scientist in the SCOT team, you are an analytical problem solver who enjoys diving into data from various businesses, is excited about investigations and algorithms, can multi-task, and can credibly interface between scientists, engineers and business stakeholders. Your expertise in synthesizing and communicating insights and recommendations to audiences of varying levels of technical sophistication will enable you to answer specific business questions and innovate for the future.

The Private Brands team is looking for an Applied Scientist to join the team in building science solutions at scale. Our team applies Optimization, Machine Learning, Statistics, Causal Inference, and Econometrics/Economics to derive actionable insights. We are an interdisciplinary team of Scientists, Engineers, and Economists and primary focus on building optimization and machine learning solutions in supply chain domain with specific focus on Amazon private brand products. Key job responsibilities You will work with business leaders, scientists, and economists to translate business and functional requirements into concrete deliverables, including the design, development, testing, and deployment of highly scalable optimization solutions and ML models. This is a unique, high visibility opportunity for someone who wants to have business impact, dive deep into large-scale problems, enable measurable actions on the consumer economy, and work closely with scientists and economists. As a senior scientist, you bring business and industry context to science and technology decisions. You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems, acquiring expertise as needed. You decompose complex problems into straightforward solutions. We are particularly interested in candidates with academic and/or practical background in Operations Research and Machine Learning. Experience in applying Operations Research and/or ML to supply chain problems is a plus.

The Private Brands team is looking for an Applied Scientist to join the team in building science solutions at scale. Our team applies Optimization, Machine Learning, Statistics, Causal Inference, and Econometrics/Economics to derive actionable insights. We are an interdisciplinary team of Scientists, Engineers, and Economists and primary focus on building optimization and machine learning solutions in supply chain domain with specific focus on Amazon private brand products. Key job responsibilities You will work with business leaders, scientists, and economists to translate business and functional requirements into concrete deliverables, including the design, development, testing, and deployment of highly scalable optimization solutions and ML models. This is a unique, high visibility opportunity for someone who wants to have business impact, dive deep into large-scale problems, enable measurable actions on the consumer economy, and work closely with scientists and economists. As a scientist, you bring business and industry context to science and technology decisions. You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems, acquiring expertise as needed. You decompose complex problems into straightforward solutions. We are particularly interested in candidates with experience in predictive and machine learning models and working with distributed systems. Academic and/or practical background in Machine Learning are particularly relevant for this position. Familiarity and experience in applying Operations Research techniques to supply chain problems is a plus.

Amazon is continuing to invest in its Advertising business to tap into the growing online advertising market. The Publisher Technologies team builds and operates extensible services that empower 1P Publishers to improve the monetization of their customer experiences, along with the experiences themselves. We bias toward standards-based and flexible designs that allow Publishers the ability to invent on top of our solutions and to interoperate well with other advertising technology providers; both internal and external. The Publisher Technology Data, Insights, and Analytics team enables faster data-driven decision making for Publishers and Monetization teams by providing them with near real time data, data management tools, actionable insights, and an easy-to-use reporting experience. Our data products provide Publishers and Monetization teams with the capabilities necessary to better understand the performance of their Advertising products along with supporting machine learning at scale. In this role, you will join a team whose data products and services empower hundreds of teams across Amazon with near real time data to support big data analytics, insights, and machine learning at scale. You will collaborate with cross-functional teams to design, develop, and implement advanced data tools, predictive models, and machine learning algorithms to support Advertising strategies and optimize revenue streams. You will analyze large-scale data to identify patterns and trends, and design and run A/B experiments to improve Publisher and advertiser experiences. Key job responsibilities - Design and lead large projects and experiments from beginning to end, and drive solutions to complex or ambiguous problems - Create tools and solve challenges using statistical modeling, machine learning, optimization, and/or other approaches for quantifiable impact on the business - Use broad expertise to recommend the right strategies, methodologies, and best practices, teaching and mentoring others - Key influencer of your team’s business strategy and of related teams’ strategies - Communication and documentation of methodologies, insights, and recommendations for senior leaders with various levels of technical knowledge

Do you want to join an innovative team of scientists who use machine learning and statistical techniques to create state-of-the-art solutions for providing better value to Amazon’s customers? Do you want to build and deploy advanced ML systems that help optimize millions of transactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data to solve real-world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Machine Learning team for India Consumer Businesses. Machine Learning, Big Data and related quantitative sciences have been strategic to Amazon from the early years. Amazon has been a pioneer in areas such as recommendation engines, ecommerce fraud detection and large-scale optimization of fulfillment center operations. As Amazon has rapidly grown and diversified, the opportunity for applying machine learning has exploded. We have a very broad collection of practical problems where machine learning systems can dramatically improve the customer experience, reduce cost, and drive speed and automation. These include product bundle recommendations for millions of products, safeguarding financial transactions across by building the risk models, improving catalog quality via extracting product attribute values from structured/unstructured data for millions of products, enhancing address quality by powering customer suggestions We are developing state-of-the-art machine learning solutions to accelerate the Amazon India growth story. Amazon India is an exciting place to be at for a machine learning practitioner. We have the eagerness of a fresh startup to absorb machine learning solutions, and the scale of a mature firm to help support their development at the same time. As part of the India Machine Learning team, you will get to work alongside brilliant minds motivated to solve real-world machine learning problems that make a difference to millions of our customers. We encourage thought leadership and blue ocean thinking in ML. Key job responsibilities Use machine learning and analytical techniques to create scalable solutions for business problems Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes Design, develop, evaluate and deploy, innovative and highly scalable ML models Work closely with software engineering teams to drive real-time model implementations Work closely with business partners to identify problems and propose machine learning solutions Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model maintenance Work proactively with engineering teams and product managers to evangelize new algorithms and drive the implementation of large-scale complex ML models in production Leading projects and mentoring other scientists, engineers in the use of ML techniques About the team International Machine Learning Team is responsible for building novel ML solutions that attack India first (and other Emerging Markets across MENA and LatAm) problems and impact the bottom-line and top-line of India business. Learn more about our team from https://www.amazon.science/working-at-amazon/how-rajeev-rastogis-machine-learning-team-in-india-develops-innovations-for-customers-worldwide

Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply cutting edge Generative AI algorithms to solve real world problems with significant impact? The Generative AI Innovation Center at AWS is a new strategic team that helps AWS customers implement Generative AI solutions and realize transformational business opportunities. This is a team of strategists, data scientists, engineers, and solution architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI. You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. We’re looking for ML Data Scientists capable of using GenAI and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems. Key job responsibilities As an ML Data Scientist, you will * Collaborate with ML scientist and architects to Research, design, develop, and evaluate cutting-edge generative AI algorithms to address real-world challenges * Interact with customers directly to understand the business problem, help and aid them in implementation of generative AI solutions, deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and paths to production * Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder * Provide customer and market feedback to Product and Engineering teams to help define product direction About the team The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, select and train the right models, define paths to navigate technical or business challenges, develop proof-of-concepts, and make plans for launching solutions at scale. The GenAI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently. 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 (CORE) and AmazeCon (gender diversity) 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.

Amazon's AGI Web & Knowledge Services group is seeking a passionate, talented, and inventive Applied Scientist to lead the development of industry-leading structured Information retrieval systems. As part of our cutting-edge AGI-SIR team, you will play a pivotal role in developing efficient AI solutions for Knowledge Graphs, Graph Search and Question Answering Systems. In this role, your work will focus on creating scalable and efficient AI-driven technologies that push the boundaries of information retrieval. You will work on a broad range of problems, from low-level data processing to the development of novel retrieval models, leveraging state-of-the-art machine learning methods. Key job responsibilities - Lead the development of advanced algorithms for knowledge graphs, graph search and question answering systems, guiding the team in solving complex problems and setting technical direction. - Design models that address customer needs, making informed trade-offs to balance accuracy, efficiency, and user experience. - Collaborate with engineering teams to implement successful models into scalable, reliable Amazon production systems. - Present results to technical and business audiences, ensuring clarity, statistical rigor, and relevance to business goals. - Establish and uphold high scientific and engineering standards, driving best practices across the team. - Promote a culture of experimentation and continuous learning within Amazon’s applied science community.

The North America Capacity Planning team in Amazon Stores' Supply Chain organization is charged with planning, managing, and optimizing the use of inbound, storage, and fulfillment capacity in North America. Optimal planning and usage of this capacity is critical in enabling us to deliver several billion items annually at continually lower costs and higher speeds. The decision space extends from tactical short-term actions (what capacity constraints do we face next week and how do we alleviate them?) to large-scale long-term strategy (what kind of fulfillment capacity should we invest in, where, over the next three years?). The team works in close partnership with several other business and tech teams to develop capacity plans, and ensure the delivery and optimal use of fulfillment capacity. As a Principal Research Scientist in this team, you will interact with subject matter experts within and outside the team, as well as scientists in a range of partner organizations, to develop scientific models for capacity planning and optimization. You will leverage these models to influence senior leadership to make high-impact decisions that are critical to building Amazon's future supply chain. You will also be an active participant in the overall Amazon scientific community, generating intellectual capital, participating in reviews and conferences, publishing in internal and external venues, and incorporating scientific rigor in the team's practices. Key job responsibilities - Develop scientific models for large-scale fulfillment capacity planning under uncertainty - Partner with stakeholder science teams for development and use of their scientific models for various aspects of capacity planning such as demand estimation, inventory flows, and multi-echelon supply chain management - Develop strategic plans for long-term capacity investments, in close collaboration with subject matter experts within and outside the team - Influence senior leadership on large-scale one-way capital and technological investments for designing our future fulfillment network - Partner with scientists across Amazon in developing scientific models that jointly optimize the Amazon supply chain