Careers

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 inspired by invention? Is problem solving through teamwork in your DNA? Do you like the idea of seeing how your work impacts the bigger picture? Answer yes to any of these and you’ll fit right in here at Amazon Robotics. We are a smart team of doers who work passionately to apply cutting edge advances in robotics and software to solve real-world challenges that will transform our customers’ experiences. We invent new improvements every day. We are Amazon Robotics and we will give you the tools and support you need to invent with us in ways that are rewarding, fulfilling, and fun. Amazon Robotics is seeking students to join us for a 5-6 month internship (full-time, 40 hours per week) as Data Science Co-op. Please note that by applying to this role you would be considered for Data Scientist spring co-op and fall co-op roles on various Amazon Robotics teams. The internship/co-op project(s) and location are determined by the team the student will be working on. Learn more about Amazon Robotics: https://amazon.jobs/en/teams/amazon-robotics About the team Amazon empowers a smarter, faster, more consistent customer experience through automation. Amazon Robotics automates fulfillment center operations using various methods of robotic technology including autonomous mobile robots, sophisticated control software, language perception, power management, computer vision, depth sensing, machine learning, object recognition, and semantic understanding of commands. Amazon Robotics has a dedicated focus on research and development to continuously explore new opportunities to extend its product lines into new areas.

We are seeking a motivated and experienced Senior Applied Scientist with expertise in Machine Learning (ML), Artificial Intelligence (AI), Big Data, and Service Oriented Architecture. You should have a deep understanding of the digital advertising business and scaled marketing across communication channels. In this role, you will collaborate with a cross-functional team of talented scientists and engineers to innovate, iterate, and solve real-world marketing problems with cutting-edge AWS technologies. You will lead in-depth analyses of the key problems faced by Amazon Ads customers and the challenges faced by marketing teams in meeting customer needs at scale. To address these problems, you will build innovative large-scale ML/AI solutions such as bespoke omni-channel recommender systems, and specialized LLM-powered assistants for customers and marketers. You will independently drive research and prototyping to deliver functional proofs of concept (POCs), and then partner with engineers to inform the technology roadmap and deploy successful POCs as scalable batch and real-time applications in production. Key job responsibilities • Define and execute a research and development plan that enables data-driven marketing decisions and delivers inspiring customer experiences • Evaluate, evolve, and invent scientific techniques to effectively address customer needs and business problems • Establish and drive science prototyping best practices to ensure coherence and integrity of data feeding into production ML/AI solutions • Collaborate with colleagues across science and engineering disciplines for rapid prototyping at scale • Partner with engineering teams to solve complex technical problems, define system-level requirements, develop implementation plans, and guide the adaptation of techniques to meet production needs • Partner with product managers and stakeholders to define forward-looking product visions and prospective business use-cases • Drive and lead of culture of data-driven innovation within and outside across Amazon Ads Marketing organization • Influence organizational vision across Ads Marketing organization About the team The Marketing Decisions Science team provides AI/ML products to enable Amazon Ads Marketing to deliver relevant and compelling guidance, education, and inspiration to prospective and active advertisers across marketing channels. We own the product, technology, and deployment roadmap for AI/ML products across Amazon Ads Marketing. We analyze the needs, experiences, and behaviors of Amazon advertisers at petabytes scale, to deliver the right marketing communications to the right advertiser at the right time. Our products enable applications and synergies across Ads organization, spanning marketing, product, and sales use cases.

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

Come build the future of entertainment with us. Are you interested in shaping the future of movies and television? Do you want to define the next generation of how and what Amazon customers are watching? Prime Video is a premium streaming service that offers customers a vast collection of TV shows and movies - all with the ease of finding what they love to watch in one place. We offer customers thousands of popular movies and TV shows from Originals and Exclusive content to exciting live sports events. We also offer our members the opportunity to subscribe to add-on channels which they can cancel at anytime and to rent or buy new release movies and TV box sets on the Prime Video Store. Prime Video is a fast-paced, growth business - available in over 240 countries and territories worldwide. The team works in a dynamic environment where innovating on behalf of our customers is at the heart of everything we do. If this sounds exciting to you, please read on. We are looking for an applied scientist who will work on the latest research and machine learning to build scalable personalisation solutions. You will be responsible for developing and disseminating customer-facing personalised recommendation models. This is a hands-on role working with a multidisciplinary group of engineers and scientists in the London office, focused on improving the customer experience for Prime Video and the wider Amazon organization. You will lead the design of machine learning models that scale to large quantities of data and serve low-latency recommendations to all customers worldwide. You will embody scientific rigor in designing and executing experiments to demonstrate the technical efficacy and business value of your methods. You will work alongside a science and engineering team that embodies the customer obsession principle by developing recommendation systems and raise the profile of Amazon as a global leader in machine learning and personalisation. Successful candidates will have strong technical ability, a focus on customers by applying a customer-first approach, and excellent teamwork and communication skills. The position offers exceptional opportunities for every candidate to grow their technical and non-technical skills. Key job responsibilities - Research, design, and implement recommendation systems that personalise across different customer experience touch points. - Collaborate with engineers to deploy and integrate successful model experiment results into large-scale, complex Amazon production systems with low latency. - Provide machine learning thought leadership to both technical and business leaders, with the ability to think strategically about business, product, and technical challenges. - Define the science roadmap and research agenda that aligns with the organisation's priorities and production constraints. - Work with technical product managers to work backwards from what's important to customers and deliver machine-backed solutions. - Report and share results with the team and wider scientific community by authoring documents that are both statistically rigorous and compellingly relevant, exemplifying good scientific practice in a business environment. A day in the life You'll be a research leader in the space and a hands-on ML practitioner, guiding and collaborating with talented teams of engineers and leaders in the Offer Tech organisation. You will be innovating and experimenting in a complex technical and business space - dealing with Amazon scale, different types of video assets (Movies, TV Shows, Live Sports, Short Videos) and balancing various business offerings (Prime, Third party channels), positively impacting millions of customers worldwide using your knowledge research, experience in building ML models to positively impact customers. About the team As a member of the Offer Recommendations team, you will spend your time as a hands-on machine learning practitioner and a research leader. You will play a key role on the team, building and guiding machine learning models from the ground up. At then of the day, you will have the reward of seeing your contributions benefit millions of Amazon.com customers worldwide.

We’re pioneering the development of a cutting-edge Seller Foundation Model designed to capture seller interactions, predict future behaviors, and simulate responses across varied conditions. Our goal is to enhance support for our diverse seller community and foster improved outcomes for both sellers and the broader Amazon ecosystem. We are looking for passionate innovators who are excited about technology, driven by customer experience, and eager to make a lasting impact on the industry. In this role, you'll collaborate with top-tier scientists, engineers, and technical program managers (TPMs) to drive innovation and deliver exceptional results for our customers. You will lead the effort to leverage Amazon's large-scale computing resources to accelerate advances in machine learning and foundation models. If you’re enthusiastic about joining a dynamic and motivated team, this is your chance to be part of an exciting journey. Apply now and help us shape the future of seller support at Amazon!

Amazon.com’s Buyer Risk Prevention's (BRP) mission is to make Amazon the safest and most trusted place worldwide to transact online. BRP safeguards every financial transaction across all Amazon sites. As such, BRP designs and builds the software systems, risk models, and operational processes that minimize risk and maximize trust in Amazon.com. The BRP organization is looking for an Applied Scientist for the Buyer Abuse team, whose mission is to combine advanced analytics with investigator insight to create mechanisms to proactively and reactively reduce the impact of abuse across Amazon. Key job responsibilities As an Applied Scientist, you will be responsible for modeling complex problems, discovering insights, and building cutting edge risk algorithms that identify opportunities through statistical models, machine learning, and visualization techniques to improve operational efficiency and reduce monetary losses and improve customer trust. You will need to collaborate effectively with business and product leaders within BRP and cross-functional teams to build scalable solutions against high organizational standards. The candidate should be able to apply a breadth of tools, data sources, and ML techniques to answer a wide range of high-impact business questions and proactively present new insights in concise and effective manner. The candidate should be an effective communicator capable of independently driving issues to resolution and communicating insights to non-technical audiences. This is a high impact role with goals that directly impacts the bottom line of the business. Responsibilities: - Invent, implement, and deploy state of the art machine learning algorithms and systems - Build prototypes and explore conceptually new solutions - Define and conduct experiments to validate/reject hypotheses, and communicate insights and recommendations to Product and Tech teams - Take ownership of how ML solutions impact Amazon resources and Customer experience - Develop efficient data querying infrastructure for both offline and online use cases - Collaborate with cross-functional teams from multidisciplinary science, engineering and business backgrounds to enhance current automation processes - Learn and understand a broad range of Amazon’s data resources and know when, how, and which to use and which not to use. - Research and implement novel machine learning and statistical approaches - Maintain technical document and communicate results to diverse audiences with effective writing, visualizations, and presentations Please visit https://www.amazon.science for more information

The Learning & Development Science team in Amazon Logistics (AMZL) builds state-of-the-art Artificial Intelligence (AI) solutions for enhancing leadership and associate development within the organization. We develop technology and mechanisms to map the learner journeys, answer real-time questions through chat assistants, and drive the right interventions at the right time. As an Applied Scientist on the team, you will play a critical role in driving the design, research, and development of these science initiatives. The ideal candidate will lead the research on learning and development trends, and develop impactful learning journey roadmap that align with organizational goals and priorities. By parsing the information of different learning courses, they will utilize the latest advances in Gen AI technology to address the personalized questions in real-time from the leadership and associates through chat assistants. Post the learning interventions, the candidate will apply causal inference or A/B experimentation frameworks to assess the associated impact of these learning programs on associate performance. As a part of this role, this candidate will collaborate with a large team of experts in the field and move the state of learning experience research forward. They should have the ability to communicate the science insights effectively to both technical and non-technical audiences. Key job responsibilities * Apply science models to extract actionable information from learning feedback * Leverage GenAI/Large Language Model (LLM) technology for scaling and automating learning experience workflows * Design and implement metrics to evaluate the effectiveness of AI models * Present deep dives and analysis to both technical and non-technical stakeholders, ensuring clarity and understanding and influencing business partners * Perform statistical analysis 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

Are you excited about developing cutting-edge generative AI, large language models (LLMs), and foundation models? Are you looking for opportunities to build and deploy them on real-world problems at a truly vast scale with global impact? At AFT (Amazon Fulfillment Technologies) AI, a group of around 50 scientists and engineers, we are on a mission to build a new generation of dynamic end-to-end prediction models (and agents) for our warehouses based on GenAI and LLMs. These models will be able to understand and make use of petabytes of human-centered as well as process information, and learn to perceive and act to further improve our world-class customer experience – at Amazon scale. We are looking for a Sr. Applied Scientist who will become of the research leads in a team that builds next-level end-to-end process predictions and shift simulations for all systems in a full warehouse with the help of generative AI, graph neural networks, and LLMs. Together, we will be pushing beyond the state of the art in simulation and optimization of one of the most complex systems in the world: Amazon's Fulfillment Network. Key job responsibilities In this role, you will dive deep into our fulfillment network, understand complex processes, and channel your insights to build large-scale machine learning models (LLMs and Transformer-based GNNs) that will be able to understand (and, eventually, optimize) the state and future of our buildings, network, and orders. You will face a high level of research ambiguity and problems that require creative, ambitious, and inventive solutions. You will work with and in a team of applied scientists to solve cutting-edge problems going beyond the published state of the art that will drive transformative change on a truly global scale. You will identify promising research directions, define parts of our research agenda and be a mentor to members of our team and beyond. You will influence the broader Amazon science community and communicate with technical, scientific and business leaders. If you thrive in a dynamic environment and are passionate about pushing the boundaries of generative AI, LLMs, and optimization systems, we want to hear from you. 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: 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 Amazon Fulfillment Technologies (AFT) powers Amazon’s global fulfillment network. We invent and deliver software, hardware, and data science solutions that orchestrate processes, robots, machines, and people. We harmonize the physical and virtual world so Amazon customers can get what they want, when they want it. The AFT AI team has deep expertise developing cutting edge AI solutions at scale and successfully applying them to business problems in the Amazon Fulfillment Network. These solutions typically utilize machine learning and computer vision techniques, applied to text, sequences of events, images or video from existing or new hardware. We influence each stage of innovation from inception to deployment, developing a research plan, creating and testing prototype solutions, and shepherding the production versions to launch.

Come build the future of entertainment with us. Are you interested in helping shape the future of movies and television? Do you want to help define the next generation of how and what Amazon customers are watching? Prime Video is a premium streaming service that offers customers a vast collection of TV shows and movies - all with the ease of finding what they love to watch in one place. We offer customers thousands of popular movies and TV shows including Amazon Originals and exclusive licensed content to exciting live sports events. We also offer our members the opportunity to subscribe to add-on channels which they can cancel at anytime and to rent or buy new release movies and TV box sets on the Prime Video Store. Prime Video is a fast-paced, growth business - available in over 240 countries and territories worldwide. The team works in a dynamic environment where innovating on behalf of our customers is at the heart of everything we do. If this sounds exciting to you, please read on. We are looking for an Applied Scientist to embark on our journey to build a Prime Video Sports tech team in Israel from ground up. Our team will focus on developing products to allow for personalizing the customers’ experience and providing them real-time insights and revolutionary experiences using Computer Vision (CV) and Machine Learning (ML). You will get a chance to work on greenfield, cutting-edge and large-scale engineering and science projects, and a rare opportunity to be one of the founders of the Israel Prime Video Sports tech team in Israel. Key job responsibilities We are looking for an Applied Scientist with domain expertise in Computer Vision or Recommendation Systems to lead development of new algorithms and E2E solutions. You will be part of a team of applied scientists and software development engineers responsible for research, design, development and deployment of algorithms into production pipelines. As a technologist, you will also drive publications of original work in top-tier conferences in Computer Vision and Machine Learning. You will be expected to deal with ambiguity! We're looking for someone with outstanding analytical abilities and someone comfortable working with cross-functional teams and systems. You must be a self-starter and be able to learn on the go. About the team In September 2018 Prime Video launched its first full-scale live streaming experience to world-wide Prime customers with NFL Thursday Night Football. That was just the start. Now Amazon has exclusive broadcasting rights to major leagues like NFL Thursday Night Football, Tennis major like Roland-Garros and English Premium League to list few and are broadcasting live events across 30+ sports world-wide. Prime Video is expanding not just the breadth of live content that it offers, but the depth of the experience. This is a transformative opportunity, the chance to be at the vanguard of a program that will revolutionize Prime Video, and the live streaming experience of customers everywhere.