Careers

Machine learning (ML) has been strategic to Amazon from the early years. We are pioneers in areas such as recommendation engines, product search, eCommerce fraud detection, and large-scale optimization of fulfillment center operations. The Generative AI team helps AWS customers accelerate the use of Generative AI to solve business and operational challenges and promote innovation in their organization. As an applied scientist, you are proficient in designing and developing advanced ML models to solve diverse challenges and opportunities. You will be working with terabytes of text, images, and other types of data to solve real-world problems. You'll design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. We’re looking for talented scientists capable of applying ML algorithms and cutting-edge deep learning (DL) and reinforcement learning approaches to areas such as drug discovery, customer segmentation, fraud prevention, capacity planning, predictive maintenance, pricing optimization, call center analytics, player pose estimation, event detection, and virtual assistant among others. Key job responsibilities The primary responsibilities of this role are to: • Design, develop, and evaluate innovative ML models to solve diverse challenges and opportunities across industries • Interact with customer directly to understand their business problems, and help them with defining and implementing scalable Generative AI solutions to solve them • Work closely with account teams, research scientist teams, and product engineering teams to drive model implementations and new solution A day in the life ABOUT AWS: 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 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.

The Geospatial science team solves problems at the interface of ML/AI and GIS for Amazon's last mile delivery programs. We have access to Earth-scale datasets and use them to solve challenging problems that affect hundreds of thousands of transporters. We are looking for strong candidates to join the transportation science team which owns time estimation, GPS trajectory learning, and sensor fusion from phone data. You will join a team of GIS and ML domain experts and be expected to develop ML models, present research results to stakeholders, and collaborate with SDEs to implement the models in production. Key job responsibilities - Understand business problems and translate them into science problems - Develop ML models - Present research results - Write and publish papers - Write production code - Collaborate with SDEs and other scientists

Job Description AOP(Analytics Operations and Programs) team is responsible for creating core analytics, insight generation and science capabilities for ROW Ops. We develop scalable analytics applications and research modeling to optimize operation processes.. You will work with professional Product Managers, Data Engineers, Data Scientists, Research Scientists, Applied Scientists and Business Intelligence Engineers using rigorous quantitative approaches to ensure high quality data/science products for our customers around the world. We are looking for an Applied Scientist to join our growing Science Team in Bangalore/Hyderabad. As an Applied Scientist, you are able to use a range of science methodologies to solve challenging business problems when the solution is unclear. You will be responsible for building ML models to solve complex business problems and test them in production environment. The scope of role includes defining the charter for the project and proposing solutions which align with org's priorities and production constraints but still create impact . You will achieve this by leveraging strong leadership and communication skills, data science skills and by acquiring domain knowledge pertaining to the delivery operations systems. You will provide ML thought leadership to technical and business leaders, and possess ability to think strategically about business, product, and technical challenges. You will also be expected to contribute to the science community by participating in science reviews and publishing in internal or external ML conferences. Our team solves a broad range of problems that can be scaled across ROW (Rest of the World including countries like India, Australia, Singapore, MENA and LATAM). Here is a glimpse of the problems that this team deals with on a regular basis: • Using live package and truck signals to adjust truck capacities in real-time • HOTW models for Last Mile Channel Allocation • Using LLMs to automate analytical processes and insight generation • Using ML to predict parameters which affect truck scheduling • Working with global science teams to predict Shipments Per Route for $MM savings • Deep Learning models to classify addresses based on various attributes Key job responsibilities 1. 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 2. Design, develop, evaluate and deploy, innovative and highly scalable ML models 3. Work closely with other science and engineering teams to drive real-time model implementations 4. Work closely with Ops/Product partners to identify problems and propose machine learning solutions 5. Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model maintenance 6. Work proactively with engineering teams and product managers to evangelize new algorithms and drive the implementation of large-scale complex ML models in production 7. Leading projects and mentoring other scientists, engineers in the use of ML techniques As part of our team, candidate in this role will work in close collaboration with other applied scientists and cross functional teams on high visibility projects with direct exposure to the senior leadership team on regular basis. About the team This team is responsible for applying science based algo and techniques to solve the problems in operation and supply chain. Some of these problems include Truck Scheduling, LM capacity planning, LLM and so on.

Amazon is the 4th most popular site in the US. Our product search engine is one of the most heavily used services in the world, indexes billions of products, and serves hundreds of millions of customers world-wide. We are working on a new AI-first initiative to re-architect and reinvent the way we do search through the use of extremely large scale next-generation deep learning techniques. Our goal is to make step function improvements in the use of advanced Machine Learning (ML) on very large scale datasets, specifically through the use of aggressive systems engineering and hardware accelerators. This is a rare opportunity to develop cutting edge ML solutions and apply them to a problem of this magnitude. Some exciting questions that we expect to answer over the next few years include: - Can combining supervised multi-task training with unsupervised training help us to improve model accuracy? - Can we transfer our knowledge of the customer to every language and every locale ? - Can we build foundational ML models that can serve different business lines. This is a unique opportunity to get in on the ground floor, shape, and build the next-generation of Amazon ML. We are looking for exceptional scientists and ML engineers who are passionate about innovation and impact, and want to work in a team with a startup culture within a larger organization. Key job responsibilities Train large deep learning models with hundreds of billions parameters. Build foundational ML models that can be applied to different business applications in Amazon such as Search and Ads. Set science directions for the team, in areas such as efficient model architecture, training and data optimization/scaling, model/data/pipeline parallel techniques, and much more.

Amazon is the 4th most popular site in the US. Our product search engine is one of the most heavily used services in the world, indexes billions of products, and serves hundreds of millions of customers world-wide. We are working on a new AI-first initiative to re-architect and reinvent the way we do search through the use of extremely large scale next-generation deep learning techniques. Our goal is to make step function improvements in the use of advanced Machine Learning (ML) on very large scale datasets, specifically through the use of aggressive systems engineering and hardware accelerators. This is a rare opportunity to develop cutting edge ML solutions and apply them to a problem of this magnitude. Some exciting questions that we expect to answer over the next few years include: - Can combining supervised multi-task training with unsupervised training help us to improve model accuracy? - Can we transfer our knowledge of the customer to every language and every locale ? - Can we build foundational ML models that can serve different business lines. This is a unique opportunity to get in on the ground floor, shape, and build the next-generation of Amazon ML. We are looking for exceptional scientists and ML engineers who are passionate about innovation and impact, and want to work in a team with a startup culture within a larger organization. Key job responsibilities Train large deep learning models with hundreds of billions parameters. Build foundational ML models that can be applied to different business applications in Amazon such as Search and Ads. Set science directions for the team, in areas such as efficient model architecture, training and data optimization/scaling, model/data/pipeline parallel techniques, and much more.

Do you want to be part of a team that's revolutionizing Amazon's fulfillment and packaging technology? Can you commit to optimizing systems that process tens-of-millions of customer packages daily with the lowest cost to serve and a defect-free customer experience? Do you have a passion for solving complex science challenges and building a sustainable e-commerce experience? Your statistical and machine learning skills can help make that a reality on the Mechatronics and Sustainable Packaging team. We are seeking a Principal Applied Scientist who will join a team of experts in the field of Statistics, Operational Research, Machine Learning (ML), Computer Vision and Generative AI to work together to break new ground in the world of automated packaging solutions. You'll work in a collaborative environment where you can pursue ambitious research with many peta-bytes of data, work on problems that haven’t been solved before, quickly implement and deploy your algorithmic ideas at scale, understand whether they succeed via statistically relevant experiments across millions of customers, and publish your research. You'll see the work you do directly improve the packaging experience of Amazon customers in the fulfillment technology space. If you are interested in robotics, computer vision, machine learning, statistics, big data, and building scalable solutions, this role is for you. The successful candidate will have a PhD in Computer Science, Statistics, or Engineering with a strong focus on data analysis, machine learning, generative AI or a related field, and 10+ years of practical experience solving complex problems in computer vision, anomaly detection, robotics. or multi-modal classification systems. Manufacturing, packaging and/or logistic experience is a plus, but not a requirement Key job responsibilities - Advance exploratory research projects in machine learning, statistics and related fields to create defect-free packaging customer experiences - Analyze large amounts of Amazon shipments to discover patterns, find opportunities, and develop highly innovative, scalable algorithms to seize these opportunities - Validate new or improved models via statistically relevant experiments across millions of customers - Work closely with software engineering teams to build scalable prototypes for testing, and integrate successful models and algorithms in production systems at very large scale

AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector. The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success. AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services. The Generative Artificial Intelligence (AI) Innovation Center team at AWS provides opportunities to innovate in a fast-paced organization that contributes to game-changing projects and technologies leveraging cutting-edge generative AI algorithms. As an Applied Scientist, you'll partner with technology and business teams to build solutions that surprise and delight our customers. We’re looking for Applied Scientists capable of using generative AI and other ML techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems. Key job responsibilities - Collaborate with scientists and engineers to research, design and develop cutting-edge generative AI algorithms to address real-world challenges - Work across customer engagement to understand what adoption patterns for generative AI are working and rapidly share them across teams and leadership - 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 for generative AI - 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. A day in the life Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. 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. What if I don’t meet all the requirements? That’s okay! We hire people who have a passion for learning and are curious. You will be supported in your career development here at AWS. You will have plenty of opportunities to build your technical, leadership, business and consulting skills. Your onboarding will set you up for success, including a combination of formal and informal training. You’ll also have a chance to gain AWS certifications and access mentorship programs. You will learn from and collaborate with some of the brightest technical minds in the industry today.

The AWS Neuron Compiler team is actively seeking applied scientists to join our efforts in developing a state-of-the-art deep learning compiler stack. This stack is designed to optimize application models across diverse domains, including Large Language and Vision, originating from leading frameworks such as PyTorch, TensorFlow, and JAX. Your role will involve working closely with our custom-built Machine Learning accelerators, including Inferentia/Trainium, which represent the forefront of AWS innovation for advanced ML capabilities, powering solutions like Generative AI. The Automated Reasoning Group in the AWS Neuron Compiler team works on the intersection of Artificial Intelligence and program analysis to raise the code quality bar in compiler stack. In this role as an Applied Scientist, you'll be instrumental in designing, developing, and deploying analyzers for ML compiler stages and compiler IRs. You will contribute to the design and semantics of DSLs that our customers love when crafting neural architexctures. You will architect and implement business-critical tooling, publish cutting-edge research, and mentor a brilliant team of experienced scientists and engineers. You will need to be technically capable, credible, and curious in your own right as a trusted AWS Neuron engineer, innovating on behalf of our customers. Your responsibilities will involve tackling crucial challenges alongside a talented engineering team, contributing to leading-edge design and research in compiler technology and deep-learning systems software. Strong experience in programming languages, compilers, program analyzers, and program synthesis engines will be a benefit in this role. A background in machine learning and AI accelerators is preferred but not required. We expect a strong publication record in compilers, IR semantics, static analysis or verification. A day in the life AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services. Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

Come transform Amazon Search using Large Language Models (LLMs). We are building new approaches to bring in a step change to both Amazon Rufus and Amazon Search. You will innovate with your team to provide delightful answers to customers by incorporating world knowledge in matching and ranking models, and helping the models deeply understand semantic meaning in descriptive and conversational queries such as "light tent for snow camping with my son", “best toys for on the go” or “cheap plus size summer pajamas”. Key job responsibilities - You will analyze large scale datasets - define metrics that reflect customer experience - invent techniques that improve capabilities such as understanding of natural language queries, questions and conversations - test your ideas in controlled experiments - train, fine-tune and align Large Language Models (LLMs). - distill Large Language Models into Fast Language Models and deploy them to operate at Amazon scale with imperceptible latencies

We are seeking a Data Scientist who will apply expertise in statistical analysis, machine learning, and data mining to uncover patterns and insights that drive operational improvements. As a Data Scientist, you will collaborate cross-functionally to understand business challenges and gather requirements. You will design and implement solutions utilizing statistical modeling, machine learning, text mining, causal inference, and other advanced analytical techniques to provide data-driven recommendations. This opportunity is ideal for talented data scientists who demonstrate strong technical skills in manipulating large, disparate datasets, building scalable ML models leveraging AWS services, advanced statistical analysis, and modeling, combined with the ability to communicate technical insights concisely to business partners. Key job responsibilities Partner with stakeholders to translate business challenges into appropriate data science solutions Collect, analyze, synthesize data into useful business insights and recommended actions Perform statistical analysis and modeling to uncover trends, correlations, drivers and recommend operational improvements Work with large, disparate datasets across databases. Use AWS services to build scalable ML models Communicate technical insights concisely and non-technically to business owners Design and implement machine learning solutions to automate analysis A day in the life If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply! Benefits Summary: Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan Learn more about our benefits HERE About the team Operations Technology Solutions (OTS) provides IT support and deploying cutting-edge technology infrastructure for Amazon’s operations, fulfilling Amazon's commitment to customers globally. The Operations Excellence team aims to empower leadership with data-driven insights, improve efficiency, and support strategic initiatives. We are seeking a Data Scientist who will apply expertise in statistical analysis, machine learning, and data mining to uncover patterns and insights that drive operational improvements.