Careers

Amazon launched the Generative AI Innovation Center (GenAIIC) in June 2023 to help AWS customers accelerate the use of generative AI to solve business and operational problems and promote innovation in their organization. This is a team of strategists, data scientists, engineers, and solution architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI. (https://press.aboutamazon.com/2023/6/aws-announces- generative-ai-innovation-center). We’re looking for Data Scientists to use generative AI and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems. 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. As an early-in-career joiner, you will initially join our A2C (Associate to Consultant) program for intensive training on AWS technology and delivery approach. Emirati nationality is required. Key job responsibilities As a Data Scientist, you will - Collaborate with AI/ML scientists, engineers, and architects to Research, design, develop, and evaluate cutting-edge generative AI algorithms 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, 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 The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, select and train or fine tune the right models, define paths to navigate technical or business challenges, develop proof-of-concepts, and make plans for launching solutions at scale. The Generative AI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently. 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.

EU INTech Partner Growth Experience(PGX) is seeking an Applied Scientist to lead the development of machine learning solutions for the EU Consumer Electronics business. In this role, you will push the boundaries of advanced ML techniques and collaborate closely with product and engineering teams to create innovative buying and forecasting solutions for the business. These new models will primarily benefit Smart Retail project that aims to revolutionize CPFR (Collaborative Planning, Forecasting, and Replenishment) Retail operations, driving automation, enhancing decision-making processes, and achieving scale across eligible categories such as PC, Home Entertainment or Wireless. Smart Retail solution is composed of an internal interface automating selection management mechanisms currently performed manually, followed by the creation of a vendor-facing interface on Vendor Central reducing time spent collecting required inputs. The project's key functionalities include (i) a Ranging model operating from category to product attributes level, pre-ASIN creation and when selection is substitutable, (ii) an advanced forecasting model designed for new selection and accounting cannibalization, (iii) ordering inputs optimization in line with for SCOT guideline compliance, and intelligent inventory management for sell-through tracking. Smart Retail success also depends on its integration with existing systems (SCOT) to minimize manual intervention and increase accuracy. Key job responsibilities * Design, develop, and deploy advanced machine learning models to address complex, real-world challenges at scale. * Build new forecasting and time-series models or enhance existing methods using scalable techniques. * Partner with cross-functional teams, including product managers and engineers, to identify impactful opportunities and deliver science-driven solutions. * Develop and optimize scalable ML solutions, ensuring seamless production integration and measurable impact on business metrics. * Continuously enhance model performance through retraining, parameter tuning, and architecture improvements using Amazon’s extensive data resources. * Lead initiatives, mentor junior scientists and engineers, and promote the adoption of ML methodologies across teams. * Stay abreast of advancements in ML research, contribute to top-tier publications, and actively engage with the scientific community.

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 and 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.

The Selling Partner Fees team owns the end-to-end fees experience for two million active third party sellers. We own the fee strategy, fee seller experience, fee accuracy and integrity, fee science and analytics, and we provide scalable technology to monetize all services available to third-party sellers. We are looking for a Senior Economist to lead the development of economic models and tools to optimize the structure and magnitude of fees paid by >4MM of heterogeneous Sellers Worldwide. This person will work on the development of economic, statistical and machine learning models to understand third party seller behaviors and enhance our fee optimization models. The ideal candidate needs to be comfortable transitioning between theoretical Economic models and empirical ones, and use the combination of these models to provide guidance for fee setting. A successful Economist in this role will enjoy dealing with ambiguous problems and working in a fast-paced and dynamic environment. The position also requires collaboration with other scientists (Economists, Data Scientists…), Strategy Analysts, Product Managers and Software Developers. Key job responsibilities - Design and develop theoretical and empirical models to assess the causal impact of fees on third party sellers’ behavior and business performance. - Lead enhancements into existing fee calculation models to maximize the long term health of the Amazon third-party marketplace. - Collaborate with product managers, data scientists, and software developers to incorporate models into production processes and influence senior leaders. - Act as ambassador of the fees scientific community.

The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Senior Applied Scientist with a strong deep learning background, to lead the development of industry-leading technology with multimodal systems. Key job responsibilities As a Senior Applied Scientist with the AGI team, you will lead the development of novel algorithms and modeling techniques to advance the state of the art with multimodal systems. Your work will directly impact our customers in the form of products and services that make use of vision and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate development with multimodal Large Language Models (LLMs) and Generative Artificial Intelligence (GenAI) in Computer Vision. About the team The AGI team has a mission to push the envelope with multimodal LLMs and GenAI in Computer Vision, in order to provide the best-possible experience for our customers.

Alexa is the voice activated digital assistant powering devices like Amazon Echo, Echo Dot, Echo Show, and Fire TV, which are at the forefront of this latest technology wave. To preserve our customers’ experience and trust, the Alexa Sensitive Content Intelligence (ASCI) team creates policies and builds services and tools through Machine Learning techniques to detect and mitigate sensitive content across Alexa. We are looking for an experienced Senior Applied Scientist to build industry-leading technologies in attribute extraction and sensitive content detection across all languages and countries. A Senior Applied Scientist will be a tech lead for a team of exceptional scientists to develop novel algorithms and modeling techniques to advance the state of the art in NLP or CV related tasks. You will work in a hybrid, fast-paced organization where scientists, engineers, and product managers work together to build customer facing experiences. You will collaborate with and mentor other scientists to raise the bar of scientific research in Amazon. Your work will directly impact our customers in the form of products and services that make use of speech, language, and computer vision technologies. We are looking for a leader with strong technical experiences a passion for building scientific driven solutions in a fast-paced environment. You should have good understanding of Artificial Intelligence (AI), Natural Language Understanding (NLU), Machine Learning (ML), Dialog Management, Automatic Speech Recognition (ASR), and Audio Signal Processing where to apply them in different business cases. You leverage your exceptional technical expertise, a sound understanding of the fundamentals of Computer Science, and practical experience of building large-scale distributed systems to creating reliable, scalable, and high-performance products. In addition to technical depth, you must possess exceptional communication skills and understand how to influence key stakeholders. You will be joining a select group of people making history producing one of the most highly rated products in Amazon's history, so if you are looking for a challenging and innovative role where you can solve important problems while growing as a leader, this may be the place for you. Key job responsibilities You'll lead the science solution design, run experiments, research new algorithms, and find new ways of optimizing customer experience. You set examples for the team on good science practice and standards. Besides theoretical analysis and innovation, you will work closely with talented engineers and ML scientists to put your algorithms and models into practice. Your work will directly impact the trust customers place in Alexa, globally. You contribute directly to our growth by hiring smart and motivated Scientists to establish teams that can deliver swiftly and predictably, adjusting in an agile fashion to deliver what our customers need. A day in the life You will be working with a group of talented scientists on researching algorithm and running experiments to test scientific proposal/solutions to improve our sensitive contents detection and mitigation. This will involve collaboration with partner teams including engineering, PMs, data annotators, and other scientists to discuss data quality, policy, and model development. You will mentor other scientists, review and guide their work, help develop roadmaps for the team. You work closely with partner teams across Alexa to deliver platform features that require cross-team leadership. About the hiring group About the team The mission of the Alexa Sensitive Content Intelligence (ASCI) team is to (1) minimize negative surprises to customers caused by sensitive content, (2) detect and prevent potential brand-damaging interactions, and (3) build customer trust through appropriate interactions on sensitive topics. The term “sensitive content” includes within its scope a wide range of categories of content such as offensive content (e.g., hate speech, racist speech), profanity, content that is suitable only for certain age groups, politically polarizing content, and religiously polarizing content. The term “content” refers to any material that is exposed to customers by Alexa (including both 1P and 3P experiences) and includes text, speech, audio, and video.

Our mission is to create best-in-class AI agents that seamlessly integrate multimodal inputs like speech, images, and video, enabling natural, empathetic, and adaptive interactions. We develop cutting-edge Large Language Models (LLMs) that leverage advanced architectures, cross-modal learning, interpretability, and responsible AI techniques to provide coherent, context-aware responses augmented by real-time knowledge retrieval. We seek a talented Applied Scientist with expertise in LLMs, speech, audio, NLP, or multimodal learning to pioneer innovations in data simulation, representation, model pre-training/fine-tuning, generation, reasoning, retrieval, and evaluation. The ideal candidate will build scalable solutions for a variety of applications, such as streaming real-time conversational experiences, including multilingual support, talking avatar interactions, customizable personalities, and conversational turn-taking. With a passion for pushing boundaries and rapid experimentation, you'll deliver high-impact solutions from research to customer-facing products and services. Key job responsibilities As an Applied Scientist, you'll leverage your expertise to research novel algorithms and modeling techniques to develop data simulation approaches mimicking real-world interactions with a focus on the speech modality. You'll acquire and curate large, diverse datasets while ensuring privacy, creating robust evaluation metrics and test sets to comprehensively assess LLM performance. Integrating human-in-the-loop feedback, you'll iterate on data selection, sampling, and enhancement techniques to improve the core model performance. Your innovations in data representation, model pre-training/fine-tuning on simulated and real-world datasets, and responsible AI practices will directly impact customers through new AI products and services.

Our mission is to create best-in-class AI agents that seamlessly integrate multimodal inputs like speech, images, and video, enabling natural, empathetic, and adaptive interactions. We develop cutting-edge Large Language Models (LLMs) that leverage advanced architectures, cross-modal learning, interpretability, and responsible AI techniques to provide coherent, context-aware responses augmented by real-time knowledge retrieval. We seek a talented Applied Scientist with expertise in LLMs, speech, audio, NLP, or multimodal learning to pioneer innovations in data simulation, representation, model pre-training/fine-tuning, generation, reasoning, retrieval, and evaluation. The ideal candidate will build scalable solutions for a variety of applications, such as streaming real-time conversational experiences, including multilingual support, talking avatar interactions, customizable personalities, and conversational turn-taking. With a passion for pushing boundaries and rapid experimentation, you'll deliver high-impact solutions from research to customer-facing products and services. Key job responsibilities As an Applied Scientist, you'll leverage your expertise to research novel algorithms and modeling techniques to develop data simulation approaches mimicking real-world interactions with a focus on the speech modality. You'll acquire and curate large, diverse datasets while ensuring privacy, creating robust evaluation metrics and test sets to comprehensively assess LLM performance. Integrating human-in-the-loop feedback, you'll iterate on data selection, sampling, and enhancement techniques to improve the core model performance. Your innovations in data representation, model pre-training/fine-tuning on simulated and real-world datasets, and responsible AI practices will directly impact customers through new AI products and services.

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.

The Artificial General Intelligence (AGI) team is looking for a highly skilled and experienced Senior Applied Scientist, to lead the development and implementation of algorithms and models for supervised fine-tuning and reinforcement learning through human feedback; with a focus across text, image, and video modalities. As a Senior Applied Scientist, you will play a critical role in driving the development of Generative AI (GenAI) technologies that can handle Amazon-scale use cases and have a significant impact on our customers' experiences. Key job responsibilities - Collaborate with cross-functional teams of engineers, product managers, and scientists to identify and solve complex problems in GenAI - Design and execute experiments to evaluate the performance of different algorithms and models, and iterate quickly to improve results - Think big about the arc of development of GenAI over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems - Communicate results and insights to both technical and non-technical audiences, including through presentations and written reports - Mentor and guide junior scientists and engineers, and contribute to the overall growth and development of the team