Careers

"We see our customers as invited guests to a party, and we are the hosts. It's our job every day to make every important aspect of the customer experience a little bit better." - Jeff Bezos, Founder & CEO. We didn’t make Amazon a trillion-dollar company, our customers did and we want to ensure that our customers always have a positive experience that keeps them coming back to Amazon. To help achieve this, the Worldwide Defect Elimination (WWDE) team, within Amazon Customer Service, relentlessly focuses on maintaining customer trust by building products that offer appropriate resolutions to resolve issues faced by our customers. WWDE scientists solve complex problems and build scalable solutions to help our customers navigate through issues and eliminate systemic defects to prevent future issues. As an Applied Scientist, your role is pivotal in leveraging advanced Artificial Intelligence (AI) and Machine Learning (ML) techniques to address customer issues at scale. You'll develop innovative solutions that summarize and detect issues, organize them using taxonomy, and pinpoint root causes within Amazon systems. Your expertise will drive the identification of responsible stakeholders and enable swift resolution. Utilizing the latest techniques, you will build an AI ecosystem that can efficiently comb over our billions of customer interactions (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 defect elimination research forward. You should have a knack for leveraging AI to translate complex data insights into actionable strategies and can communicate these effectively to both technical and non-technical audiences. Key job responsibilities - Develop ML/GenAI-powered solutions for automating defect elimination workflows - Implement scalable and efficient scientific solutions in production environments - Design and implement robust metrics to evaluate the effectiveness of ML/AI models - Perform statistical analyses and statistical tests, including hypothesis testing and A/B testing - Recognize and adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation A day in the life 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: - Medical, Dental, and Vision Coverage - Maternity and Parental Leave Options - Paid Time Off (PTO) - 401(k) Plan 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

Interested in solving challenging problems using latest developments in Large Language Models and Artificial Intelligence (AI)? Amazon's Consumer Electronics Technology (CE Tech) organization is redefining shopping experiences leveraging state of the art AI technologies. We are looking for a talented Sr. Applied Scientist with a solid background in the design and development of scalable AI and ML systems and services, deep passion for building ML-powered products, a proven track record of executing complex projects, and delivering high business and customer impact. You will help us shape the future of shopping experiences. As a member of our team, you'll work on projects that directly impact millions of customers, and selling partners every single day. This role will provide exposure to state-of-the-art innovations in AI/ML systems (including GenAI). Technologies you will have exposure to, and/or will work with, include AWS Bedrock, Amazon Q, SageMaker, and Foundational Models such as Anthropic’s Claude / Mistral, among others. The types of initiatives you can expect to work on include: - Developing personalized recommendation systems that help customers find the right CE products for their needs. - Creating high quality educational content leveraging complex AI techniques to simplify complex product information. - Building intelligent automation solutions that generate customized bundles, gift guides and warranties personalization at scale This Sr. Applied Scientist is also expected to play a key role in raising the AI/ML skillset within the organization, so a passion for teaching/mentoring is important. This involves bringing deep AI/ML expertise to collaborations with other scientists, leading lunch & learn session, conducting tech talks, setting up regular office hours, evangelizing lessons learned & industry best practices, and more. The ideal candidate is one who possesses notable pedigree in ML-related academic work, along with deep, real-world, hands-on experience in executing/shipping AI-based products in a fast-paced setting. You will be looked up to as an ML expert that our organization’s leadership can rely on for guidance on AI/ML topics. Key job responsibilities - Design, implement, and productionalize AI/ML products at Amazon scale, in collaboration with other applied scientists and engineers, both within Consumer Electronics and more broadly across the Stores organization, - Develop ML/LLM workflows and end-to-end pipelines for data preparation, training, deployment, monitoring, etc., and ensure a high bar for the quality of architecture and design of our AIML systems and data infrastructure, - Leverage AWS AI services and other internal / publicly available external tools & services to accelerate our AI investments in CE Tech, - Be data-driven and possess a quantitative mindset. Grounded, detail-oriented, always backs up ideas with facts. Understand complex application data flows and bridge the gap between technical and business app requirement, - Identify state of the art models / solutions to enable new capabilities for code migration and code testing, drive down tech debt and increase operational efficiency, - Mentor other scientists, especially on AI/ML initiatives, and foster a culture of learning & collaboration. Provide thought leadership and hands-on support in selecting, defining, training and fine-tuning Large Language Models (LLMs), prompt engineering, and other GenAI efforts.

"We see our customers as invited guests to a party, and we are the hosts. It's our job every day to make every important aspect of the customer experience a little bit better." - Jeff Bezos, Founder & CEO. We didn’t make Amazon a trillion-dollar company, our customers did and we want to ensure that our customers always have a positive experience that keeps them coming back to Amazon. To help achieve this, the Worldwide Defect Elimination (WWDE) team, within Amazon Customer Service (CS), relentlessly focuses on maintaining customer trust by building products that offer appropriate resolutions to resolve issues faced by our customers. WWDE scientists solve complex problems and build scalable solutions to help our customers navigate through issues and eliminate systemic defects to prevent future issues. As a Research Scientist, your role is pivotal in leveraging advanced Artificial Intelligence (AI) and Machine Learning (ML) techniques to address customer issues at scale. You'll develop innovative solutions that summarize and detect issues, organize them using taxonomy, and pinpoint root causes within Amazon systems. Your expertise will drive the identification of responsible stakeholders and enable swift resolution. Utilizing the latest techniques, you will build an AI ecosystem that can efficiently comb over our billions of customer interactions (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 defect elimination research forward. You should have a knack for leveraging AI to translate complex data insights into actionable strategies and can communicate these effectively to both technical and non-technical audiences. Key job responsibilities - Develop ML/GenAI-powered solutions for automating defect elimination workflows - Design and implement robust metrics to evaluate the effectiveness of ML/AI models - Perform statistical analyses and statistical tests, including hypothesis testing and A/B testing - Recognize and adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation A day in the life 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: - Medical, Dental, and Vision Coverage - Maternity and Parental Leave Options - Paid Time Off (PTO) - 401(k) Plan 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.

Alexa International Tech (AIT) team is looking for a passionate, talented, and inventive Applied Scientist to help build industry-leading technology with Large Language Models (LLMs) and multimodal systems, requiring strong deep learning and generative models knowledge. Key job responsibilities As an Applied Scientist with the AIT team, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art with LLMs. Your work will directly impact our international customers in the form of products and services that make use of digital assistance technology. You will leverage Amazon’s heterogeneous data sources, unique but diverse international customer nuances and large-scale computing resources to accelerate advances in voice domain in multi-modal setup. The ideal candidate possesses a solid understanding of machine learning fundamentals and a passion for pushing boundaries in this vast and quickly evolving field. They thrive in fast-paced environments to will tackle complex challenges, and excel at swiftly delivering impactful solutions while iterating based on user feedback. A day in the life · Analyze, understand, and model customer behavior and the customer experience based on large scale data. Especially showing passion towards solving for international customer-centric challenges. · Build novel online & offline evaluation metrics an methodologies for personal digital assistants and customer scenarios, on multi-modal devices. · innovate and deliver deep learning based innovation across life-cycle such as policy-based learning, international customer specific model performance tuning. · Quickly experiment and setup experimentation framework for agile model and data analysis or A/B testing · Contribute through industry first research to drive the innovation forward.

Amazon Lab126 is an inventive research and development company that designs and engineers high-profile consumer electronics. Lab126 began in 2004 as a subsidiary of Amazon.com, Inc., originally creating the best-selling Kindle family of products. Since then, we have produced groundbreaking devices like Fire tablets, Fire TV, Amazon Echo, and the Astro household robot. What will you help us create? As a Principal Controls Scientist, you will be responsible for developing solutions to control complex electromechanical systems. You will take responsibility for developing models, performing analysis, and producing algorithms for the control and estimation of robotic systems that guide and inform mechanical and electrical designs, software implementation, and other software modules that affect overall device safety and performance. You will demonstrate cross-functional interaction to accomplish your goals. You will play a role in defining processes and methods to improve the productivity of the entire team. You will interface with Amazon teams outside your immediate organization to identify leverage opportunities with minimized dependencies. You will investigate applicable academic and industry research applications, identify and initiate investigations of production technologies, prototype and test solutions to support product features, and design and validate production designs that deliver an exceptional user experience. Key job responsibilities - Produce models and simulations of complex, high degree-of-freedom dynamic electromechanical systems - Design estimation and control algorithms that achieve performance targets within hardware and software constraints - Hands-on prototyping and testing on physical systems in the lab - Influence hardware and software design decisions owned by other teams to optimize system-level performance - Define key performance indicators and allocate error budgets across hardware and software modules - Perform root cause analysis of system-level failures and distinguish between hardware/software failures and hardware/software mitigations - Balance objectives of safety, performance, and cost in architectural design decisions - Lead cross-functional teams (controls, firmware, perception, planning, sensors, mechanical, electrical, etc.) to solve complex system integration issues - Translate business requirements to engineering requirements and identify trade-offs and sensitivities - Mentor junior and senior engineers in good design practice; actively participate in hiring of new team members About the team The Dynamic Systems and Control team develops models, algorithms, and code to bridge hardware and software development teams and bring robotic products to life. We contributed to Amazon Astro (https://www.amazon.com/Introducing-Amazon-Astro/dp/B078NSDFSB) and Echo Show 10 (https://www.amazon.com/echo-show-10/dp/B07VHZ41L8/), along with several new technology introductions and unannounced products currently in development.

Amazon is looking for a passionate, talented, and inventive Applied Scientist with a strong machine learning, systems, applied statistics and natural language technologies background to join our Learned Systems Group (LSG) and help build industry-leading large scale applied ML, AI and GenAI systems. As part of our LSG 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 systems, machine learning, artificial intelligence and human language technology. Key job responsibilities As a part of the LSG, 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. A day in the life 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 large scale distributed systems, text and structured data sources, and large-scale computing resources to accelerate advances in systems and machine learning. The Learned Systems Group at AWS helps build the scientific foundations of our analytics systems, including Redshift, Athena and RDS. We constantly push the state of the art to deploy state of the art ML and AI techniques into our large scale systems and finding new ways to delight our customers. We are constantly faced with large scale systems and we apply rigorous research methods to improve them with efficient and scalable innovative solutions. About the team 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.

Amazon is looking for a motivated individual with strong analytical and algorithmic skills and practical experience to join the Modeling and Optimization (MOP) Routing Science team. Your main focus will be on developing and improving our last-mile experience, with emphasis on algorithmic and analytical work. We are looking for candidates with proven ability to design, implement, and evaluate state-of-the-art solutions to large-scale optimization problems, working closely with software development engineers. The position requires strong background in combinatorial optimization, algorithms, algorithm engineering, and data structures, particularly as it applies to vehicle routing and related problems. Familiarity with Data Science and Machine Learning techniques is a plus. You will also play an integral role in the network planning, modeling, and analysis that will improve the efficiency and cost effectiveness of global fulfillment operations. You will identify and evaluate opportunities to reduce variable costs by improving the transportation network topology, inventory placement, transportation operations and scheduling, fulfillment center processes, and the execution to operational plans. You will also improve the efficiency of capital investment by helping plan the location and deployment of fixed assets. Finally, you will help create the metrics to quantify improvements to the fulfillment costs (e.g., transportation and labor costs) resulting from the application of these optimization models and tools.

The Smart Home team is focused on making Alexa the user interface for the home. From the simplest voice commands (turn on the lights, turn down the heat) to use cases spanning home security, home entertainment, and the home environment, we are evolving Alexa into intelligent, indispensable companion that automates daily routines, simplifies interaction with appliances and electronics, and alerts when something unusual is detected. You will be part of a team delivering features that are highly anticipated by media and well received by our customers. As a Senior Applied Scientist, you will work with other scientists and software developers to design and build the next generation of Smart Home voice control using the latest Large Language Models. And, you will have the satisfaction of working on a product your friends and family can relate to, and want to use every day. Key job responsibilities Developing new inference and training techniques to improve the performance of Large Language Models for Smart Home control and Automation. Developing robust techniques for synthetic data generation for training large models and maintaining model generalization. Mentoring junior scientists to improve their skills, knowledge, and their ability to get things done. About the team We are a team of Scientists, Machine Learning Engineers, and Software Developers that work together to make Alexa more insightful and proactive through ambient intelligence - with features like Alexa Hunches that automatically control Smart Home devices. We are interdisciplinary and we act like it -- we ask each other questions and value our different perspectives.

Are you passionate about leveraging data to deliver actionable insights that impact daily marketing activities at Amazon? The Customer Targeting team in Amazon is seeking an Applied Scientist to join our team to develop models for optimizing the performance of Amazon’s marketing initiatives across channels and advertising formats. You have experience applying modern machine learning methods to answer key business questions, make strategic and tactical recommendations for change, and work with business leaders to drive these to production. You are entrepreneurial and able to work in a highly collaborative environment. This role requires an individual with strong quantitative modeling skills and experience using statistical methods. The successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail, an ability to work in a fast-paced and ever-changing environment. You will be expected to: - Leverage knowledge of statistics and optimization to frame decision-making problems for determining marketing spends across channels. - Predict future customer behavior and business conditions through machine learning and predictive modeling. - Use analytical and predictive techniques to build models for optimizing targeting. - Present proposals and results in a clear manner backed by data and coupled with actionable conclusions.

Amazon’s global talent is incredibly complex with unique problems to be solved for each line of business. Global Talent Management (GTM) is centrally responsible for managing and evolving Amazon’s human capital through intelligent talent products and processes. GTM Science is a growing interdisciplinary science team within GTM that develops science products and services to facilitate Amazon’s growth and development of talent across all of our businesses and locations around the world. Our vision in GTM Science is to use machine learning and Generative AI to scalably solve organizational challenges focused on talent movement, talent differentiation, employee-role matching, promotion processes, organizational design and succession planning, diversity and inclusion, and new areas that address the evolving needs of our diverse employee base. We are looking for an experienced ML/AI scientist to work on talent science products that draw from a range of fields such as algorithmic fairness, natural language processing, supervised and unsupervised learning, recommendation systems, machine learning on graphs, reinforcement learning and others on rich and novel datasets. The role has high visibility to senior Amazon business leaders and involves working with other scientists, and partnering with engineering and product teams to integrate these models into production systems. As an applied scientist in GTM Science, you will have the opportunity to work on exciting problems in one of the most innovative applications of science in the People Experience and Technology space. You will help to solve high impact business problems in an unconventional domain, and be encouraged to patent and publish your contributions. If this kind of work excites you, reach out to us to find out more! Key Responsibilities · Design and implement models, science-based product ideas and features, project plans and communicate with stakeholders. · Develop fair predictive models to understand important business and people-centered outcomes · Productionize ML and science models at the scale of Amazon