Careers

As a Senior Applied Scientist in Worldwide Defect Elimination at Amazon, your role is pivotal in leveraging advanced AI and ML techniques to address customer issues at scale. You'll lead the development of innovative solutions that summarize and detect problems, organize them using ontologies, and pinpoint root causes within Amazon systems. Your expertise will drive the identification of responsible stakeholders and enable swift resolution. You will utilize the latest in AI/ML to to develop an LLM ecosystem that can comb over our billions of contacts (using a combination of media). As a part of this role, you will collaborate with a large team of experts in the field and move the state of research forward. Key job responsibilities * Research and Development of Cutting Edge Modeling techniques for NLP, NLU, and Prediction. * Establishing scientific culture and standards for all the scientists (publication, best practices, reviews, etc.) * Delivering solutions to the core business problems above and influencing business partners * Develop scientific talent on the team 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! 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 About the team The Worldwide defect elimination team's mission is to understand and resolve all issues impacting customers at scale. The Economics team is a force multiplier within this group, helping to understand the impact of these issues, changes to our policies, and optimizing the customer experience.

Does the idea of creating technology solutions for delivering 11 Billion+ packages across the globe excite you? If yes, come join a fun-loving, diverse, and creative team at Amazon Last Mile! The vision of the team is "To create Earth’s safest, most adaptive, and efficient plans for Last Mile logistics". The Last Mile Delivery Technology team is instrumental in impacting customer satisfaction directly, by devising innovative ways to deliver packages quickly and cost-effectively to the customers, and at scale using Artificial Intelligence (AI), Machine Learning and Operations Research solutions. Last Mile Delivery Technology organization supports the design, planning and execution of last mile transportation for Amazon’s various parcel and grocery delivery programs. All these programs require a large number of decision support systems to operate at scale and serve our customers, spanning demand planning, jurisdiction planning, delivery channel and network design, capacity planning for on the road and under the roof at delivery stations, routing inputs and route optimization. While these decision support systems have thus far been approached through the lens of traditional optimization and machine learning, we are looking to re-envision this space and pursue Foundational AI research, to innovate and advance the state of these decision support systems. Specifically, we are looking to develop foundational models (including Large Language Models, Multimodal Language Models, Multimodal Models), and adaptations to serve last mile use cases. Beyond Amazon the work developed will spur new fundamental knowledge and innovation in the logistics space. We are looking for candidates with knowledge and experience in designing and developing state-of-art AI solutions (including development and application of advanced deep learning algorithms, foundational models, multimodal generative AI solutions, reinforcement learning), to join our team. Demonstrated experience scaling and optimizing the training and inference of these models, building real world solutions, to meet the customer use cases is preferred. Proven track record of publishing in major AI conferences and demonstrated experience working in industry will be preferred. Job Location : Bellevue WA or Austin TX. Key job responsibilities Candidates will be responsible for developing Foundational AI solutions, to serve the myriad of decision support use cases across last mile. In this role, you will be expected to define new research avenues, explore, adopt, and invent new machine learning techniques, implement scalable science and engineering solutions, contribute software to production systems, conduct rigorous experiments, publish results, influence technical and business leadership and ensuring that research is translated into practice. You will be working with a team of scientists and engineers, helping shape the strategic and tactical vision, and contribute hands on to foundational research efforts in last mile. A day in the life Sitting at the core of Amazon’s Last Mile business, Routing and Planning (RaP) invents technology solutions that deliver toward the RaP vision: to create earth’s safest, most adaptive, and efficient plans for Last Mile logistics. RaP serves a diverse set of external and internal customers. For Amazon End Customers and transporters, we build solutions to deliver 11B packages and services to arrive at the right place and time, while meeting the growing preference for speed and precision. For internal customers, we build and delivery routing solutions Worldwide adding up to a $1B USD, across multiple amazon businesses ranging from Amazon Logistics, Amazon X-tra Large to Same/Sub-Same Day Deliveries, Fresh and Groceries etc using multiple mode of transports. If the opportunity to innovate, create and deliver first-time solutions alongside world-class engineers and scientists e.g. building a new delivery foundational model from scratch utilizing data at an unprecedented scale in the industry excites you, this is the place for you. About the team The Last Mile (LM) Science organization serves two primary functions: (1) maintaining and enhancing the components which provide the essential intelligence in nearly every LM system, and (2) creating the science which will enable the continued growth of Amazon in the future. The systems used on a daily basis by the Last Mile to deliver packages from the station to the customer’s doorstep contains embedded models developed by the science team, or relies on inputs derived from these models. These models determine how efficiently Amazon can serve its customers and at what cost.

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. Within AWS UC, Amazon Dedicated Cloud (ADC) roles engage with AWS customers who require specialized security solutions for their cloud services. AWS AI/ML is looking for world class scientists and engineers to work on foundation models, large-scale representation learning, and distributed learning methods and systems. At AWS AI/ML you will invent, implement, and deploy state of the art machine learning algorithms and systems. You will build prototypes and innovate on new representation learning solutions. You will interact closely with our customers and with the academic and research communities. You will be at the heart of a growing and exciting focus area for AWS and work with other acclaimed engineers and world famous scientists. Large-scale foundation models have been the powerhouse in many of the recent advancements in computer vision, natural language processing, automatic speech recognition, recommendation systems, and time series modeling. Developing such models requires not only skillful modeling in individual modalities, but also understanding of how to synergistically combine them, and how to scale the modeling methods to learn with huge models and on large datasets. Join us to work as an integral part of a team that has diverse experiences in this space. We actively work on these areas: - Hardware-informed efficient model architecture, training objective and curriculum design - Distributed training, accelerated optimization methods - Continual learning, multi-task/meta learning - Reasoning, interactive learning, reinforcement learning - Robustness, privacy, model watermarking - Model compression, distillation, pruning, sparsification, quantization A day in the life 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.

The JP Economics team is a central science team working across a variety of topics in the JP Retail business and beyond. We work closely with JP business leaders to drive change at Amazon. We focus on solving long-term, ambiguous and challenging problems, while providing advisory support to help solve short-term business pain points. Key topics include pricing, product selection, delivery speed, profitability, and customer experience. We tackle these issues by building novel economic/econometric models, machine learning systems, and high-impact experiments which we integrate into business, financial, and system-level decision making. Our work is highly collaborative and we regularly partner with JP- EU- and US-based interdisciplinary teams. In this role, you will build production-grade machine learning models to serve best-in-class shopping and delivery experience to millions of customers on Amazon. This requires you to formulate ambiguous business problems into solvable scientific problems, work with large-scale data pipelines, perform extensive data cleaning and exploration, train and evaluate your models in a robust manner, design and conduct live experiments to validate model performance, and automate model inference on AWS infrastructure. The ideal candidate is an experienced data scientist or machine learning engineer who has built machine learning systems in production that delivers business impact at scale in a B2C industry. You are a self-starter who enjoys ambiguity in a fast-paced and ever-changing environment. You are extremely proficient in Python, SQL and distributed computing frameworks. You have excellent understanding of how machine learning models work under the hood. In addition, you may have worked with AWS infrastructure and causal uplift modeling techniques. You think big on the next game-changing opportunity but also dive deep into every detail that matters. You insist on the highest standards and are consistent in delivering results. We are open to consider high-potential candidates with less experiences for a more junior position. Key job responsibilities - Work with Product, Finance and Engineering to formulate business problems into scientific ones - Build large-scale data pipelines for training and evaluating the models using PySpark/SparkSQL - Extensively clean and explore the datasets - Train and evaluate ML models in a robust manner - Design and conduct live experiments to validate model performance - Automate model inference and monitoring and on AWS infrastructure

As part of the AWS Solutions organization, we have a vision to provide business applications, leveraging Amazon’s unique experience and expertise, that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers’ businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. We blend vision with curiosity and Amazon’s real-world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are no-brainers to buy and easy to use. Amazon Go is a new kind of store with no lines and no checkout—you just grab and go! Customers simply use the Amazon Go app to enter the store, take what they want from our selection of fresh, delicious meals and grocery essentials, and go! Our checkout-free shopping experience is made possible by our Just Walk Out Technology, which automatically detects when products are taken from or returned to the shelves and keeps track of them in a virtual cart. When you’re done shopping, you can just leave the store. Shortly after, we’ll charge your Amazon account and send you a receipt. Check it out at amazon.com/go. Designed and custom-built by Amazonians, our Just Walk Out Technology uses a variety of technologies including computer vision, sensor fusion, and advanced machine learning. Innovation is part of our DNA! Our goal is to be Earths’ most customer centric company and we are just getting started. We need people who want to join an ambitious program that continues to push the state of the art in computer vision, machine learning, distributed systems and hardware design. The Role: Everyone on the team needs to be entrepreneurial, wear many hats and work in a highly collaborative environment that’s more startup than big company. We’ll need to tackle problems that span a variety of domains: computer vision, image recognition, machine learning, real-time and distributed systems. As an Applied Scientist, you will help solve a variety of technical challenges and mentor other engineers. You will tackle challenging, novel situations every day and given the size of this initiative, you’ll have the opportunity to work with multiple technical teams at Amazon in different locations. You should be comfortable with a degree of ambiguity that’s higher than most projects and relish the idea of solving problems that, frankly, haven’t been solved at scale before - anywhere. Along the way, we guarantee that you’ll learn a ton, have fun and make a positive impact on millions of people. About the team Diverse Experiences AWS 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. 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.

The Senior Applied Scientist will play a critical role in leading the research, development, and implementation of solutions to key challenges in developing conversational AI systems that can understand and communicate with customers in a natural and contextually appropriate manner. This involves tackling complex problems in areas such as multi-turn dialogue management, knowledge grounding, and open-ended generation. Key job responsibilities 1. Lead the research and development of LLM-based chatbots and conversational AI systems for customer service applications. 2. Design and implement state-of-the-art NLP and ML models for tasks such as language understanding, dialogue management, and response generation. 3. Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to integrate LLM-based solutions into Amazon's customer service platforms. 4. Develop and implement strategies for data collection, annotation, and model training to ensure high-quality and robust performance of the chatbots. 5. Conduct experiments and evaluations to measure the performance of the developed models and systems, and identify areas for improvement. 6. Stay up-to-date with the latest advancements in NLP, LLMs, and conversational AI, and explore opportunities to incorporate new techniques and technologies into Amazon's customer service solutions. 7. Collaborate with internal and external research communities, participate in conferences and publications, and contribute to the advancement of the field. 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” About the team Join our team of scientists and engineers who develop and deploy LLM-based Conversational AI systems to enhance Amazon's customer service experience and effectiveness. We work on innovative solutions that help customers solve their issues and get their questions answered efficiently, and associate-facing products that support our customer service associate workforce.

As an Applied Scientist on our Learning and Development team, you will play a critical role in driving the design, development, and delivery of learning programs and initiatives aimed at enhancing leadership and associate development within the organization. You will leverage your expertise in learning science, data analysis, and statistical model design to create impactful learning journey roadmap that align with organizational goals and priorities. Key job responsibilities 1) Research and Analysis: Conduct research on learning and development trends, theories, and best practices related to leadership and associate development. Analyze data to identify learning needs, performance gaps, and opportunities for improvement within the organization. Use data-driven insights to inform the design and implementation of learning interventions. 2) Program Design and Development: Collaborate with cross-functional teams to develop comprehensive learning programs focused on leadership development and associate growth. Design learning experiences using evidence-based instructional strategies, adult learning principles, and innovative technologies. Create engaging and interactive learning materials, including e-learning modules, instructor-led workshops, and multimedia resources. 3) Evaluation and Continuous Improvement: Develop evaluation frameworks to assess the effectiveness and impact of learning programs on leadership development and associate performance. Collect and analyze feedback from participants and stakeholders to identify strengths, areas for improvement, and future learning needs. Iterate on learning interventions based on evaluation results and feedback to continuously improve program outcomes. 4) Thought Leadership and Collaboration: Serve as a subject matter expert on learning science, instructional design, and leadership development within the organization. Collaborate with stakeholders across the company to align learning initiatives with strategic priorities and business objectives. Share knowledge and best practices with colleagues to foster a culture of continuous learning and development.

We are looking for an Applied Scientist who is passionate about building services and tools for developers that leverage artificial intelligence and machine learning. You will be part of a team building Large Language Model (LLM)-based services with the focus on enhancing the developer experience in the Cloud. The team works in close collaboration with other AWS services such as AWS Cloud9, the AWS IDE Toolkit and AWS Bedrock. If you are excited about working in cloud computing and building new AWS services, then we'd love to talk to you. As an Applied Scientist, you are recognized for your expertise, advise team members on a range of machine learning topics, and work closely with software engineers to drive the delivery of end-to-end modeling solutions. Your work focuses on ambiguous problem areas where the business problem or opportunity may not yet be defined. The problems that you take on require scientific breakthroughs. You take a long-term view of the business objectives, product roadmaps, technologies, and how they should evolve. You drive mindful discussions with customers, engineers, and scientist peers. You bring perspective and provide context for current technology choices, and make recommendations on the right modeling and component design approach to achieve the desired customer experience and business outcome. Key job responsibilities Understand the challenges that developers face when building software today, and develop generalizable solutions. Collaborate with developers and pave the way towards bringing your solution into production systems. Lead cross team projects and ensure technical blockers are resolved Communicate and document your research via publishing papers in external scientific venues. About the team About AWS Diverse Experiences AWS 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. 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. This team is part of AWS Utility Computing: Utility Computing (UC) 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.

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 fascinated by the power of Natural Language Processing (NLP) and Large Language Models (LLM) to transform the way we interact with technology? Are you passionate about applying advanced machine learning techniques to solve complex challenges in the e-commerce space? If so, Amazon's International Seller Services team has an exciting opportunity for you as an Applied Scientist. At Amazon, we strive to be Earth's most customer-centric company, where customers can find and discover anything they want to buy online. Our International Seller Services team plays a pivotal role in expanding the reach of our marketplace to sellers worldwide, ensuring customers have access to a vast selection of products. As an Applied Scientist, you will join a talented and collaborative team that is dedicated to driving innovation and delivering exceptional experiences for our customers and sellers. You will be part of a global team that is focused on acquiring new merchants from around the world to sell on Amazon’s global marketplaces around the world. The position is based in Seattle but will interact with global leaders and teams in Europe, Japan, China, Australia, and other regions. Join us at the Central Science Team of Amazon's International Seller Services and become part of a global team that is redefining the future of e-commerce. With access to vast amounts of data, cutting-edge technology, and a diverse community of talented individuals, you will have the opportunity to make a meaningful impact on the way sellers engage with our platform and customers worldwide. Together, we will drive innovation, solve complex problems, and shape the future of e-commerce. Please visit https://www.amazon.science for more information Key job responsibilities - Apply your expertise in LLM models to design, develop, and implement scalable machine learning solutions that address complex language-related challenges in the international seller services domain. - Collaborate with cross-functional teams, including software engineers, data scientists, and product managers, to define project requirements, establish success metrics, and deliver high-quality solutions. - Conduct thorough data analysis to gain insights, identify patterns, and drive actionable recommendations that enhance seller performance and customer experiences across various international marketplaces. - Continuously explore and evaluate state-of-the-art NLP techniques and methodologies to improve the accuracy and efficiency of language-related systems. - Communicate complex technical concepts effectively to both technical and non-technical stakeholders, providing clear explanations and guidance on proposed solutions and their potential impact.