Careers

Do you want to join a team of innovative scientists to research and develop generative AI technology that would disrupt the industry? Do you enjoy dealing with ambiguity and working on hard problems in a fast-paced environment? Amazon Connect is a highly disruptive cloud-based contact center from AWS that enables businesses to deliver intelligent, engaging, dynamic, and personalized customer service experiences. As an Applied Scientist on our team, you will work closely with senior technical and business leaders from within the team and across AWS. You distill insight from huge data sets, conduct cutting edge research, foster ML models from conception to deployment. You have deep expertise in machine learning and deep learning broadly, and extensive domain knowledge in natural language processing, generative AI and LLMs, etc. The ideal candidate has the ability to understand, implement, innovate on the state-of-the-art generative AI based systems. You are comfortable with quickly prototyping and iterating your ideas to build robust ML models using technology such as PyTorch, Tensorflow, AWS Sagemaker, and SparkML. Our team is at an early stage, so you will have significant impact on our ML deliverables with little operational load from existing models/systems. We have a rapidly growing customer base and an exciting charter in front of us that includes solving highly complex engineering and scientific problems. We are looking for passionate, talented, and experienced people to join us to innovate on modern contact centers in the cloud. The position represents a rare opportunity to be a part of a fast-growing business soon after launch, and help shape the technology and product as we grow. You will be playing a crucial role in developing the next generation contact center, and get the opportunity to design and deliver scalable, resilient systems while maintaining a constant customer focus. Our team is leading ML and optimization features in Amazon Connect. We are a team of scientists and engineers working on multiple science projects for Amazon Connect. We use state-of-the-art science and engineering practices to address the hard problems in contact center operation and management for our customers, and we move fast to implement solutions and refine them based on customer feedback. Learn more about Amazon Connect here: https://aws.amazon.com/connect/ 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.

Are you a scientist interested in pushing the state of the art in machine learning and recommendation systems? Are you interested in working on novel ideas that can positively impact millions of customers? Do you wish you had access to large datasets and tremendous computational resources? Answer yes to any of these questions and you will be a great fit for our team at Amazon. Our team is part of Amazon’s Personalization organization, a high-performing group that leverages Amazon’s expertise in machine learning, big data, distributed systems, and user experience design to deliver the best shopping experiences for our customers. Our team builds large-scale machine-learning solutions that delight customers with personzlized content recommendations, at the right time, with the right level of explanation. As an Applied Scientist in our team, you will be responsible for the research, design, and development of new AI technologies for personalization. You will adopt or invent new machine learning and analytical techniques in the realm of recommendations and large language models. You will collaborate with scientists, engineers, and product partners locally and abroad. Your work will include inventing, experimenting with, and launching new features, products and systems. Please visit https://www.amazon.science for more information.

Are you looking to work at the forefront of Machine Learning and AI in the Media and Entertainment industry? Would you be excited to apply Generative AI algorithms to solve real world problems with significant impact? The AWS Industries Team helps AWS customers implement Generative AI solutions and realize transformational business opportunities for AWS customers in the Media & Entertainment, Sports and Games industries. This is a team of data scientists, engineers, and architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI. The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, select and train and fine tune the right models, define paths to navigate technical or business challenges, develop proof-of-concepts, and build applications to launch these solutions at scale. The AWS Industries team provides guidance and implements best practices for applying generative AI responsibly and cost efficiently. You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. In this Data Scientist role you will be capable of using GenAI and other techniques to design, evangelize, and implement and scale modern solutions for never-before-solved problems. Key job responsibilities As a Senior Data Scientist, you will- - Collaborate with AI/ML scientists, engineers, and architects to research, design, develop, and evaluate modern generative AI algorithms and build ML systems to address real-world challenges - Interact with customers directly to understand the business problem, help and aid them in implementation of generative AI solutions, deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and paths to production - Create and deliver best practice recommendations, tutorials, blog posts, publications, sample code, and presentations adapted to technical, business, and executive stakeholder - Provide customer and market feedback to Product and Engineering teams to help define product direction About the team 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.

Welcome to Amazon's Worldwide Returns & ReCommerce (WWR&R) Team At WWR&R, we're revolutionizing returns management through our innovative "Zero Initiative," focusing on eliminating return costs, waste, and defects. Our mission extends beyond conventional business metrics to create lasting value for our customers, company, and environment. As pioneers in Amazon's circular economy, we're transforming how returns are handled through edge technology and operational excellence. Our approach combines sophisticated machine learning, automated routing systems, and innovative reuse channels to create seamless experiences for our customers while significantly reducing environmental impact. Our diverse team of experts in business, technology, and operations works collaboratively to manage the complete lifecycle of returned and damaged products. We're developing next-generation solutions that streamline the returns process, enhance product support, and create sustainable reuse opportunities. Join us in building scalable, high-impact solutions that shape the future of sustainable commerce while delivering exceptional customer experiences. At WWR&R, you'll be part of an innovative team that's committed to transforming returns management while contributing to a more sustainable future. Key job responsibilities -Design, develop, and evaluate highly innovative models for Natural Language Programming (NLP), Large Language Model (LLM), or Large Computer Vision projects. -Use SQL to query and analyze the data. -Use Python, Jupyter notebook, and Pytorch to train/test/deploy ML models. -Use machine learning and analytical techniques to create scalable solutions for business problems. -Research and implement novel machine learning and statistical approaches. -Mentor junior scientists and interns by providing technical guidance for their projects. -Work closely with data & software engineering teams to build model implementations and integrate successful models and algorithms in production systems at very large scale. About the team When a customer returns a package to Amazon, the request and package will be passed through our WWRR machine learning (ML) systems so that we could improve the customer experience, identify return root cause, optimize re-use, and evaluate the returned package. Our problems touch multiple modalities spanning from: textual, categorical, image, to speech data. We operate at large scale and rely on state-of-the-art modeling techniques to power our ML models

Have you ever wondered how that Amazon box with the smile arrives so quickly, where it came from, and how much it cost Amazon to deliver? The WW Amazon Logistics, Business Analytics team manages the delivery of tens of millions of products every week to Amazon's customers, achieving on-time delivery in a cost-effective manner. We are seeking an enthusiastic, customer-obsessed Principal Applied Scientist with strong analytical skills to join our team. This role is crucial in optimizing Amazon's vast delivery network and will have significant impact on the customer experience, particularly in the final phase of delivery. As a Principal Applied Scientist, you will: 1. Address business challenges through building compelling cases and using data to influence change across the organization 2. Develop input and assumptions based on preexisting models to estimate costs and savings opportunities associated with varying levels of network growth and operations 3. Create metrics to measure business performance, identify root causes and trends, and prescribe action plans 4. Manage multiple high-impact projects simultaneously 5. Work with technology teams and product managers to develop new tools and systems supporting business growth 6. Communicate with and support various internal stakeholders and external audiences 7. Implement scheduling solutions, improve metrics, and develop scalable processes and tools The ideal candidate will have: - PhD in Operations Research, Statistics, Engineering, or Supply Chain Management - Extensive experience in operations research and data-driven decision making - Strong analytical and problem-solving skills - Robust program management and research science skills - Ability to work with a team and make independent decisions in ambiguous environments - Customer-obsessed mindset with a focus on improving the Amazon delivery experience This role offers the autonomy to think strategically and make data-driven decisions from day one. Join us in shaping the future of e-commerce delivery and addressing the core challenges in our world-class operations space! Key job responsibilities 1. Advanced Modeling and Algorithm Development: - Design and implement sophisticated machine learning models for logistics optimization - Develop complex time series forecasting algorithms for demand prediction and resource allocation 2. AI and Machine Learning Integration: - Architect and deploy AI-powered systems to enhance decision-making in logistics operations - Implement deep learning techniques for image recognition in package sorting and handling - Develop reinforcement learning algorithms for adaptive scheduling and resource management 3. Big Data Analytics and Processing: - Design and implement distributed computing solutions for processing massive logistics datasets - Utilize cloud computing platforms (e.g., AWS) for scalable data processing and analysis 5. AI-Driven Workflow Optimization: - Design and implement AI agents for autonomous decision-making in logistics processes - Create machine learning models for customer behavior analysis and personalized delivery options 6. Software Development and System Architecture: - Write efficient, scalable code in languages such as Python, Java, or C++ - Develop and maintain complex software systems for logistics optimization - Stay at the forefront of AI and ML research - Publish research findings in top-tier conferences and journals About the team We are Amazon's Last Mile Science and Analytics team, dedicated to improving e-commerce delivery. We work to optimize our vast network, forecast demand using machine learning, and enhance route efficiency. Our efforts focus on developing innovative delivery methods, applying AI to solve complex problems, and conducting geospatial analysis. We create simulations to refine processes and plan capacity effectively. Operating globally, we strive to develop adaptable solutions for diverse markets. We aim to advance logistics science, continually improving speed, efficiency, and customer satisfaction, in support of Amazon's mission to be Earth's most customer-centric company.

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’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

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 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.

The Ads Measurement Science team in the Measurement, Ad Tech, and Data Science (MADS) team of Amazon Ads serves a centralized role developing solutions for a multitude of performance measurement products. We create solutions which measure the comprehensive impact of their ad spend, including sales impacts both online and offline and across timescales, and provide actionable insights that enable our advertisers to optimize their media portfolios. We leverage a host of scientific technologies to accomplish this mission, including Generative AI, classical ML, Causal Inference, Natural Language Processing, and Computer Vision. As a Senior Applied Scientist on the team, you will lead measurement solutions end-to-end from inception to production. You will propose, design, analyze, and productionize models to provide novel measurement insights to our customers. Key job responsibilities - Lead a team of scientists to innovate on state-of-the-art ads measurement solutions leveraging artificial intelligence, causal inference, natural language processing, computer vision, and large language models. - Directly contribute to the end-to-end delivery of production solutions through careful designs and owning implementation of significant portions of critical-path code - Lead the decomposition of problems and development of roadmaps to execute on it. - Set an example for others with exemplary analyses; maintainable, extensible code; and simple, effective solutions. - Influence team business and engineering strategies. - Communicate clearly and effectively with stakeholders to drive alignment and build consensus on key initiatives. - Foster collaborations between scientists to move faster, with broader impact. - Actively engage in the development of others, both within and outside the team. - Regularly engage with the broader scientific community with presentations, publications, and patents. About the team We are a team of scientists across Applied, Research, Data Science and Economist disciplines. You will work with colleagues with deep expertise in ML, NLP, CV, Gen AI, and Causal Inference with a diverse range of backgrounds. We partner closely with top-notch engineers, product managers, sales leaders, and other scientists with expertise in the ads industry and on building scalable modeling and software solutions. Team Video: https://youtu.be/zD_6Lzw8raE

Join the next revolution in robotics at Amazon's Frontier AI & Robotics team. As a Senior Applied Scientist, you'll spearhead the development of breakthrough foundation models that enable robots to perceive, understand, and interact with the world in unprecedented ways. You'll drive technical excellence in areas such as perception, manipulation, science understanding, sim2real transfer, multi-modal foundation models, and multi-task learning, designing novel algorithms that bridge the gap between research and real-world deployment at Amazon scale. In this role, you'll combine hands-on technical work with scientific leadership, ensuring your team delivers robust solutions for dynamic real-world environments. You'll leverage Amazon's vast computational resources to tackle ambitious problems in areas like very large multi-modal robotic foundation models and efficient, promptable model architectures that can scale across diverse robotic applications. Key job responsibilities - Lead technical initiatives in robotics foundation models, driving breakthrough approaches through hands-on research and development in areas like open-vocabulary panoptic scene understanding, scaling up multi-modal LLMs, sim2real/real2sim techniques, end-to-end vision-language-action models, efficient model inference, video tokenization - Design and implement novel deep learning architectures that push the boundaries of what robots can understand and accomplish - Guide technical direction for specific research initiatives, ensuring robust performance in production environments - Mentor fellow scientists while maintaining strong individual technical contributions - Collaborate with engineering teams to optimize and scale models for real-world applications - Influence technical decisions and implementation strategies within your area of focus A day in the life - Develop and implement novel foundation model architectures, working hands-on with our extensive compute infrastructure - Guide fellow scientists in solving complex technical challenges, from sim2real transfer to efficient multi-task learning - Lead focused technical initiatives from conception through deployment, ensuring successful integration with production systems - Drive technical discussions within your team and with key stakeholders - Conduct experiments and prototype new ideas using our massive compute cluster - Mentor team members while maintaining significant hands-on contribution to technical solutions 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 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! About the team At Frontier AI & Robotics, we're not just advancing robotics – we're reimagining it from the ground up. Our team is building the future of intelligent robotics through innovative foundation models and end-to-end learned systems. We tackle some of the most challenging problems in AI and robotics, from developing sophisticated perception systems to creating adaptive manipulation strategies that work in complex, real-world scenarios. What sets us apart is our unique combination of ambitious research vision and practical impact. We leverage Amazon's massive computational infrastructure and rich real-world datasets to train and deploy state-of-the-art foundation models. Our work spans the full spectrum of robotics intelligence – from multimodal perception using images, videos, and sensor data, to sophisticated manipulation strategies that can handle diverse real-world scenarios. We're building systems that don't just work in the lab, but scale to meet the demands of Amazon's global operations. Join us if you're excited about pushing the boundaries of what's possible in robotics, working with world-class researchers, and seeing your innovations deployed at unprecedented scale.