Careers

Amazon's Optimal Inventory Health (OIH) org in Supply Chain Optimization (SCOT) group is looking for a Principal Applied Scientist to optimize one of the most complex eCommerce systems in the world. The Optimal Inventory Health (OIH) drives long-term cash flow (LTFCF) growth by determining optimal inventory dispositions under uncertainties in demand, pricing, and supply across Amazon’s 21 marketplaces global network. OIH is in the unique position within SCOT to drive the joint optimization across supply chain and marketing across the levers of Markdowns, Removals, Outlet, Deals, Sponsored Ads, and Paid Search etc. Our systems delivers hundreds of million dollar saving to Amazon each year. The Principal Applied Scientist will lead the science vision and implementation to optimize across inventory disposition channels and deliver best experience to Amazon customers through those levers. We are investing and building the next generation inventory disposition decision models based on cutting-edge technologies like Reinforcement learning, Causal inference, Deep Learning Prediction etc. Academic and/or practical background in Machine Learning and Operations Research are particularly relevant for this position. Experience in model-based engineering and/or multidisciplinary analysis & optimization is also a plus. This position requires drive and self-motivation, superior analytical thinking, data-driven disposition, application of technical knowledge to a business context, effective collaboration with fellow scientists, software development engineers, and product managers, effective communication of technical designs to technical and non-technical audiences, and close partnership with many stakeholders from operations, finance, IT, and business leadership. Key job responsibilities - Seek to understand in depth the end to end value chain of eCommerce across supply chain and marketing and identify areas of opportunities to grow our business using science solutions. - Lead science strategy and roadmap in OIH space - Drive alignment across organizations to achieve business goals - Lead/guide scientists and engineers across teams to develop, test, launch and improve of science models designed to optimize inventory value and customer experience. - Be responsible for communicating our innovations to the broader internal & external scientific community and business leadership. - Mentor and guide the applied scientists in our organization and hold us to a high standard of technical rigor and excellence in ML. A day in the life - You will engage with distinguished scientists and Senior Principal scientists across organizations to shape the vision of the eCommerce decision systems across supply chain and marketing. - You will collaborate with talented product managers and software engineers to build the end to end systems. - You will work with stakeholders across retail, supply chain, finance etc. to understand the business operation process and bottlenecks and build solution to provide the best experience to Amazon customers through automated OIH actions. - You have the access to the richest eCommerce data and will be able to see the actual significant business impact quickly with the models you build. About the team Supply Chain Optimization Technology (SCOT) is the core of the Amazon eCommerce business, which leverage science models and systems to automate the decisions and operations of the most complex supply chain in the world. Optimal Inventory Health (OIH) maximize the inventory value in Amazon through all the levers across traffic, marketing, pricing and reverse logistics.

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 algorithmic 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 and Data Sciences team for India Consumer Businesses. If you have an entrepreneurial spirit, know how to deliver, love to work with data, are deeply technical, highly innovative and long for the opportunity to build solutions to challenging problems that directly impact the company's bottom-line, we want to talk to you. Major 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, development, evaluate and deploy innovative and highly scalable models for predictive learning - Research and implement novel machine learning and statistical approaches - Work closely with software engineering teams to drive real-time model implementations and new feature creations - Work closely with business owners and operations staff to optimize various business operations - Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation - Mentor other scientists and engineers in the use of ML techniques We are open to hiring candidates to work out of one of the following locations: Bengaluru, KA, IND

Amazon’s Last Mile Team is looking for a passionate individual with strong optimization and analytical skills to join its Last Mile Science team in the endeavor of designing and improving the most complex planning of delivery network in the world. Last Mile builds global solutions that enable Amazon to attract an elastic supply of drivers, companies, and assets needed to deliver Amazon's and other shippers' volumes at the lowest cost and with the best customer delivery experience. Last Mile Science team owns the core decision models in the space of jurisdiction planning, delivery channel and modes network design, capacity planning for on the road and at delivery stations, routing inputs estimation and optimization. Our research has direct impact on customer experience, driver and station associate experience, Delivery Service Partner (DSP)’s success and the sustainable growth of Amazon. Optimizing the last mile delivery requires deep understanding of transportation, supply chain management, pricing strategies and forecasting. Only through innovative and strategic thinking, we will make the right capital investments in technology, assets and infrastructures that allows for long-term success. Our team members have an opportunity to be 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, scientists, and software engineers in the industry. Key job responsibilities Candidates will be responsible for developing solutions to better manage and optimize delivery capacity in the last mile network. The successful candidate should have solid research experience in one or more technical areas of Operations Research or Machine Learning. These positions will focus on identifying and analyzing opportunities to improve existing algorithms and also on optimizing the system policies across the management of external delivery service providers and internal planning strategies. They require superior logical thinkers who are able to quickly approach large ambiguous problems, turn high-level business requirements into mathematical models, identify the right solution approach, and contribute to the software development for production systems. To support their proposals, candidates should be able to independently mine and analyze data, and be able to use any necessary programming and statistical analysis software to do so. Successful candidates must thrive in fast-paced environments, which encourage collaborative and creative problem solving, be able to measure and estimate risks, constructively critique peer research, and align research focuses with the Amazon's strategic needs. As a senior scientist, you will also help coach/mentor junior scientists in the team.

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.

Have you ever wondered how Amazon predicts when your order will arrive and how we ensure that it actually arrives on at the promised date/time? Have you wondered where all those Amazon semi-trucks on the road are headed? Are you passionate about increasing efficiency and reducing carbon footprint? Does the idea of having worldwide impact on Amazon's logistics network including our planes, trucks, and vans sound exciting to you? If so, then we want to talk with you! At Amazon's Supply Chain Optimization Technologies (SCOT), we are tasked with optimizing the fulfilment on customer orders so that we fulfil all orders worldwide in the most intelligent manner while ensuring Amazon customers get their orders on time. Amazon Fulfillment Planning & Execution (FPX) Science team within SCOT- Fulfilment Optimization group is seeking a Senior Applied Scientist with expertise in Machine Learning and a proven record of solving business problems through scalable ML solutions. FPX Science tackles some of the most mathematically complex challenges in transportation planning and execution space to improve Amazon's operational efficiency worldwide. We own Amazon’s global fulfilment center and transportation planning and execution. The team also owns the short-term network planning and execution that determines the optimal flow of customer orders through Amazon fulfilment network. This includes developing sophisticated math models and controllers that assign orders to fulfilment centers to be picked and packed and then planning the optimal ship method in terms of cost, speed and carbon impact to deliver to the customer. These plans drive downstream decisions that are in the billions of dollars at Amazon Scale worldwide. The systems we build are entirely in-house, and are on the cutting edge of both academic and applied research in large scale supply chain planning, optimization, machine learning and statistics. These systems operate at various scales, from real-time decision system that completes thousands of transactions per seconds, to large scale distributed system that optimize Amazon’s fulfilment network. As Amazon continues to build and expand the first party delivery network, this role will be critical to realize this vision. Your tech solution will have large impacts to the physical supply chain of Amazon, and play a key role in improving Amazon consumer business’s long-term profitability. If you are interested in diving into a multi-discipline, high impact space this is the team for you. We’re looking for a passionate, results-oriented, and inventive Senior Applied Scientist who can create and improve ML models for our outbound transportation planning systems. In addition, you will be working on design, development and evaluation of highly innovative OR and ML models for solving complex business problems in the area of outbound transportation planning systems. The position is located at Bellevue, WA, just next to Seattle with beautiful outdoors and great city life. Watch http://bit.ly/amazon-scot to get the big picture. Key job responsibilities As a Senior Applied Scientist within FPX Science team, 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. You will have an opportunity to be 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, and software engineers to integrate scientific work into production systems. You will bring deep technical expertise in the area of Machine Learning, and will play an integral part in building Amazon's Fulfillment Optimization systems. Other responsibilities include: - 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. - Work closely with software engineering teams to build model implementations and integrate successful models and algorithms in production systems at very large scale. - Technically lead and mentor other scientists in team. - Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation. A day in the life This is a great role for someone who likes to learn new things. You will have the opportunity to learn all about how Amazon plans for and executes within its logistics network including Fulfillment Centers, Air Stations, Sort Centers, Delivery Stations, and more. You will need to meet with many internal customers to understand their business and their challenges as you develop an effective solution to enable us to collectively scale. Our leadership is very interested in this effort so you will find lots of opportunities to get your ideas and plans in front of them for evaluation and alignment. We are seeking someone who wants to lead projects that require innovative thinking and deep technical problem-solving skills to create production-ready machine learning solutions. A successful candidate is able to quickly approach large ambiguous problems, turn high-level business requirements into mathematical models, identify the right solution approach, and contribute to the software development for production systems. Successful candidates must thrive in fast-paced environments, which encourage collaborative and creative problem solving, be able to measure and estimate risks, constructively critique peer research, and align research focuses with the Amazon's strategic needs. We look for individuals who know how to deliver results and show a desire to develop themselves, their colleagues, and their career. About the team Fulfillment Planning & Execution Science team contains a group of scientists with different technical backgrounds including Machine Learning and Operations Research, who will collaborate closely with you on your projects. Our team directly supports critical functional areas across Fulfillment Optimization and the research needs of the corresponding product and engineering teams. We tackle some of the most mathematically complex challenges in facility and transportation planning and execution to improve Amazon's operational efficiency worldwide and at a scale that is unique to Amazon. We often seek the opportunity of applying hybrid techniques in the space of Operations Research and Machine Learning to tackle some of our biggest technical challenges. We disambiguate complex supply chain problems and create ML and optimization solutions to solve those problems at scale.

Technology is giving the beauty industry a makeover! Are you interested to disrupt and redefine the way customers buy Beauty products online? Are you interested in using the latest advances in machine learning, computer vision, and big-data technologies to build online customer experiences for Beauty products that can equal or even surpass an in-store experience? Amazon Beauty is reinventing the shopping experience for all beauty customers across the largest selection of brands to become the most trusted beauty destination. Beauty is unique in retail with a diverse customer set along with products that are emotional, fun, and creative. This is your chance to get in on the ground floor to build something entirely new and transform an industry! To achieve our vision, we think big and tackle technological challenges every day. We need builders and disruptors who are not afraid to innovate! Our architecture and development processes support rapid experimentation, global deployments, and self-service capabilities that allow us to scale better. We build: - Amazon scale systems: All our technology needs to work at Amazon scale, serving millions of customers with millisecond-level latency. - Immersive customer experiences: We will create elevated and immersive customer experiences that using cutting-edge UI-technologies and user-centric design patterns. - Computer Vision and augmented reality (AR) experiences: We bring exciting experiences directly to the customer's mobile phone using their cameras and combinations of computer vision and AR. - Personalization using machine learning: We use latest advances in ML and GenAI to provide better-personalized shopping experiences. - Data & analytics pipelines: Amazon is data-driven, and a robust data backbone is necessary for our systems. We build on core AWS services such as EC2, S3, DynamoDB, SageMaker, StepFunctions, etc. - Multi-device support: We build for all traditional surfaces - desktop browsers, mobile browsers, and mobile applications. Key job responsibilities We are looking for talented and innovation-driven scientists who are passionate about leveraging the latest advances in Computer Vision (CV), Graphics, AR/VR, Virtual Try-On, Generative AI, Diffusion Models, Image Processing, and related technologies, to solve customer problems in the Beauty space. You will have an opportunity to revolutionize the customer shopping experience across the world's most extensive catalog of beauty products. You will be directly responsible for leading the ideation, design, prototyping, development, and launch of innovative scientific solutions that address customer problem in the beauty and shopping space. You will closely partner with product managers, UX designers, engineers, and the broader Amazon scientific community to pioneer state-of-the-art solutions to extremely challenging problems in machine learning and computer vision. You will help hire, mentor, and develop the best and brightest science and engineering talent while our organization rapidly continues to expand. You will be our organization's Tech Evangelist and represent our organization in key internal and external AI, ML, CV or RecSys conferences. About the team Amazon Beauty Tech is a key and essential part of the Consumables organization and North America Stores. We are a passionate group of engineers, scientists, product managers, and designers who drive technological innovation to improve the customer shopping experience. We have a startup-like work culture where innovation is encouraged; we are never afraid to propose big ideas for fear of failing!

Do you want to join an innovative team of scientists who use machine learning and statistical techniques to help Amazon provide the best customer experience by preventing eCommerce fraud? Are you excited by the prospect of analyzing and modeling terabytes of data and creating state-of-the-art algorithms 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 enjoy collaborating in a diverse team environment? If yes, then you may be a great fit to join the Amazon Buyer Risk Prevention (BRP) Machine Learning group. We are looking for a talented scientist who is passionate to build advanced algorithmic systems that help manage safety of millions of transactions every day. Key job responsibilities Use machine learning and statistical techniques to create scalable risk management systems Learning and understanding large amounts of Amazon’s historical business data for specific instances of risk or broader risk trends Design, development and evaluation of highly innovative models for risk management Working closely with software engineering teams to drive real-time model implementations and new feature creations Working closely with operations staff to optimize risk management operations, Establishing scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation Tracking general business activity and providing clear, compelling management reporting on a regular basis Research and implement novel machine learning and statistical approaches

Amazon is looking for a passionate, talented, and inventive Applied Scientist with a strong machine learning background to help build industry-leading language technology. Our mission is to provide a delightful experience to Amazon’s customers by pushing the envelope in Natural Language Processing (NLP), Generative AI, Large Language Model (LLM), Natural Language Understanding (NLU), Machine Learning (ML), Retrieval-Augmented Generation, Responsible AI, Agent, Evaluation, and Model Adaptation. As part of our AI team in Amazon AWS, you will work alongside internationally recognized experts to develop novel algorithms and modeling techniques to advance the state-of-the-art in human language technology. Your work will directly impact millions of our customers in the form of products and services, as well as contributing to the wider research community. You will gain hands on experience with Amazon’s heterogeneous text and structured data sources, and large-scale computing resources to accelerate advances in language understanding. The Science team at AWS Bedrock builds science foundations of Bedrock, which is a fully managed service that makes high-performing foundation models available for use through a unified API. We are adamant about continuously learning state-of-the-art NLP/ML/LLM technology and exploring creative ways to delight our customers. In our daily job we are exposed to large scale NLP needs and we apply rigorous research methods to respond to them with efficient and scalable innovative solutions. At AWS Bedrock, you’ll experience the benefits of working in a dynamic, entrepreneurial environment, while leveraging AWS resources, one of the world’s leading cloud companies and you’ll be able to publish your work in top tier conferences and journals. We are building a brand new team to help develop a new NLP service for AWS. You will have the opportunity to conduct novel research and influence the science roadmap and direction of the team. Come join this greenfield opportunity! AWS Bedrock Science Team is a part of AWS Utility Computing 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. About the team 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.

Amazon is looking for a passionate, talented, and inventive Applied Scientist with a strong machine learning background to help build industry-leading language technology. Our mission is to provide a delightful experience to Amazon’s customers by pushing the envelope in Natural Language Processing (NLP), Generative AI, Large Language Model (LLM), Natural Language Understanding (NLU), Machine Learning (ML), Retrieval-Augmented Generation, Responsible AI, Agent, Evaluation, and Model Adaptation. As part of our AI team in Amazon AWS, you will work alongside internationally recognized experts to develop novel algorithms and modeling techniques to advance the state-of-the-art in human language technology. Your work will directly impact millions of our customers in the form of products and services, as well as contributing to the wider research community. You will gain hands on experience with Amazon’s heterogeneous text and structured data sources, and large-scale computing resources to accelerate advances in language understanding. The Science team at AWS Bedrock builds science foundations of Bedrock, which is a fully managed service that makes high-performing foundation models available for use through a unified API. We are adamant about continuously learning state-of-the-art NLP/ML/LLM technology and exploring creative ways to delight our customers. In our daily job we are exposed to large scale NLP needs and we apply rigorous research methods to respond to them with efficient and scalable innovative solutions. At AWS Bedrock, you’ll experience the benefits of working in a dynamic, entrepreneurial environment, while leveraging AWS resources, one of the world’s leading cloud companies and you’ll be able to publish your work in top tier conferences and journals. We are building a brand new team to help develop a new NLP service for AWS. You will have the opportunity to conduct novel research and influence the science roadmap and direction of the team. Come join this greenfield opportunity! AWS Bedrock Science Team is a part of AWS Utility Computing 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. About the team 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.

Do you want to join an innovative team of scientists who use machine learning and statistical techniques to help Amazon provide the best customer experience by preventing eCommerce fraud? Are you excited by the prospect of analyzing and modeling terabytes of data and creating state-of-the-art algorithms 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 enjoy collaborating in a diverse team environment? If yes, then you may be a great fit to join the Amazon Buyer Risk Prevention (BRP) Machine Learning group. We are looking for a talented scientist who is passionate to build advanced algorithmic systems that help manage safety of millions of transactions every day. Key job responsibilities Use machine learning and statistical techniques to create scalable risk management systems Learning and understanding large amounts of Amazon’s historical business data for specific instances of risk or broader risk trends Design, development and evaluation of highly innovative models for risk management Working closely with software engineering teams to drive real-time model implementations and new feature creations Working closely with operations staff to optimize risk management operations, Establishing scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation Tracking general business activity and providing clear, compelling management reporting on a regular basis Research and implement novel machine learning and statistical approaches