Careers

Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video subscriptions such as Apple TV+, HBO Max, Peacock, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video team member, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! We are looking for an Applied Science Manager who will take care of the Content Understanding for Prime Video. Content Understanding team helps Prime Video "see" and "understand" what's actually happening inside its videos - the characters, scenes, dialogue, events, and visual elements. We build the systems that analyze video content so that we can build customer experiences on top of our work. This manager will also lead a team of scientists and engineers who are building the next generation of video understanding and search for Prime Video. You will own the strategy, execution, and delivery of systems that help machines watch, describe, and find content across the largest streaming catalog in the world. Key job responsibilities As an Applied Science Manager, you will: - Define and drive the technical direction and roadmap across our "understanding" and "search" workstreams — making sure our work connects to Prime Video's broader goals around content intelligence. - Lead and grow a high-performing team of scientists and engineers, building a culture of scientific excellence, customer focus, and reliable delivery. - Partner with teams across Prime Video (personalization, search etc) to understand what they need from us, shape our outputs to be reliable building blocks for their products, and drive adoption. - Own delivery end-to-end — from early research and experimentation all the way through launching production systems that run at the scale of Prime Video's full catalog. - Define and track success metrics for quality, reliability, and real-world impact on downstream products, continuously raising the bar on what "good" looks like. - Manage ambiguity across a broad set of workstreams, make clear prioritization decisions, and communicate trade-offs effectively to senior leadership. About the team The Prime Video - Content Localization, Understanding and Enrichment team's mission is to deeply understand content to automate & scale existing solutions, and launch new experiences across Prime Video while accelerating science outputs & forward-investing in science. This manager will lead Content Understanding that defines content at a fundamental scene-level by generating & maintaining a comprehensive set of Content Understanding attributes which are leveraged across Prime Video for their varied use-cases; ranging from content moderation to metadata generation, ad placement identification, etc.

Do you have proven analytical capabilities to identify business opportunities, develop predictive models and optimization algorithms to help us build state of the art Support organization? At Amazon, we are working to be the most customer-centric company on earth. To get there, we need exceptionally talented, bright, and driven people. We set big goals and are looking for people who can help us reach and exceed them. Amazon Web Services (AWS) is one of the world’s most comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from data centers globally. Amazon Web Services, Inc. provides services for broad range of applications including compute, storage, databases, networking, analytics, machine learning and artificial intelligence (AI), Internet of Things (IoT), security, and application development, deployment, and management. AWS Support's Capacity Planning team is looking for a strong, talented Data Scientist to model contact and volume forecasting, discovering insights and identifying opportunities through the use of statistics, machine learning, and combinatorial optimization problems to drive business and operational improvements. You are passionate about building solutions that will help drive a more efficient operations network and optimize cost. In this role, you will partner with data engineering, tooling team, operations, training, workforce management and finance teams, driving optimization and prediction solutions across the network influencing the long-term strategy of the business. We are looking for an experienced and motivated Data Scientist with proven abilities to build and manage modeling projects, forecasting solutions, identify data requirements, build methodology and tools that are statistically grounded. You are an expert in the areas of data science, forecasting, optimization, machine learning and statistics, and is comfortable facilitating ideation and working from concept through execution. You are customer obsessed, innovative, independent, results-oriented and enjoys working in a fast-paced growing organization. An interest in operations, process improvement is helpful. The ability to embrace this ambiguity and work with a highly distributed team of experts is critical. While this is a small team, there is opportunity to own globally impactful work and grow your career in technical, programmatic or people leadership. You will likely to work in Python or R, building forecasting, predictive and optimization models. Your problem solving ability, knowledge of data models and ability to drive results through ambiguity are more important to us. About the team About Us Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon 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.

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 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 200 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. The Observability and Triage team is looking for an Applied Scientist for our London office experienced in generative AI and large models. This is a wide impact role working with development teams across the UK, India, and the US. This greenfield project will deliver features that reduce the operational load for internal Prime Video builders and for this, you will develop AI-driven solutions that automatically detect anomalies, identify root causes, recommend resolution paths and take action for operational incidents. We consume petabytes of data daily across multiple metric, log and data based events and you would be experimenting on how to shape the future through this data. You will have strong technical ability, excellent teamwork and communication skills, and a strong motivation to deliver customer value from your research. Our position offers opportunities to grow your technical and non-technical skills and make a global impact. Key job responsibilities - Design and develop machine learning and generative AI systems for automated incident triage, root cause analysis, and resolution recommendation at scale - Rapidly prototype and evaluate hypotheses in a high-ambiguity environment, leveraging both quantitative experimentation and domain expertise in operational systems - Build evaluation frameworks (including LLM-as-a-Judge approaches) to measure model accuracy across triage accuracy and root cause prediction - Collaborate with software engineering teams to integrate ML models into production observability systems serving hundreds of development teams - Communicate results and insights to both technical and non-technical audiences, including through publications, presentations, and written reports A day in the life On a typical day, you analyse patterns across thousands of operational incidents to improve an automated triage model, then design an experiment to test whether a new Generative-AI based approach better identifies root causes for complex multi-service incidents. Your internal customers are Prime Video development teams who rely on your solutions to reduce the time and effort spent responding to operational events. You will collaborate closely with software engineers, and operational stakeholders across the world to ensure your research translates into production systems that measurably remove customer impact. About the team Our team builds AI-powered observability and triage solutions for Prime Video development teams, consuming petabytes of data daily to automatically detect, diagnose, and recommend resolutions for operational incidents.

Do you want to work on Reinforcement Learning (RL) post-training of frontier Large Language Models (LLMs) to revolutionize customer service? Come join the world class researchers and academics in the AWS AI endeavor, and develop the science that powers countless new businesses in cloud computing! AWS, the world-leading provider of cloud services. Our customers bring problems that will give Applied Scientists like you endless opportunities to see your research have a positive and immediate impact in the world. You will have the opportunity to partner with technology and business teams to solve real-world problems, have access to virtually endless data and computational resources, and to world-class engineers and developers that can help bring your ideas into the world. As part of the team, we expect that you will develop innovative solutions to hard problems, and publish your findings at peer reviewed conferences and journals. The scientific topics you are going to work on include, but are not limited to: LLM post-training to improve capabilities particularly for instruction following, reasoning over long context, and tool use, etc. About the team 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. 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. 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. 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.

Are you driven by the challenge of solving complex problems that directly impact the safety and well-being of millions of Amazon Associates worldwide? Do you want to push the boundaries of artificial intelligence (AI) to build advanced solutions that make workplaces safer and more efficient? If so, we invite you to join our WHS Data-Tech team as a Senior Applied Scientist and take your career to the next level. At WHS Data-Tech, we leverage computer vision (CV), large language models (LLMs), and AI-driven innovations to develop industry-leading solutions that proactively enhance workplace safety. Our work spans real-time risk assessment, analytics, and AI-powered insights, all aimed at creating a safer work environment at scale. As a Senior Applied Scientist specializing in CV and LLMs, you will play a pivotal role in shaping our next-generation safety solutions. You’ll lead the innovation, design and implementation of AI-powered features that redefine workplace safety. Your work will drive strategic decisions, optimize system architecture, and influence best practices, ensuring our technology remains pioneering. If you are not sure that every qualification listed describes you perfectly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skill-sets. If you’re passionate about this role and want to make an impact on a global scale, please apply! Key job responsibilities • Invent and apply novel CV and LLM approaches to analyze complex, multimodal data. Distinguish problems that require fundamentally new solutions from those addressable through existing methods. • Architect and implement core scientific components of CV and LLM-based solutions. Deploy scalable, production-grade models across on-device and cloud environments in collaboration with engineering teams. • Design evaluation frameworks and conduct rigorous experiments. Benchmark against state-of-the-art and iterate on model architectures to advance performance. • Stay at the forefront of computer vision, LLMs, and generative AI research. Proactively identify and prototype novel techniques for integration into production solutions. • Collaborate with product managers, program managers, and business stakeholders to translate ambiguous problems into well-scoped ML solutions with measurable impact. • Build consensus on complex projects and decompose them into independent workstreams. Identify and resolve technical bottlenecks that limit innovation. • Propose research initiatives, secure leadership alignment, and present technical trade-offs and strategic recommendations to stakeholders. • Author internal technical documents and research papers. Contribute to the scientific community through conferences and peer reviews. • Actively mentor team members, elevating scientific capabilities and fostering a culture of innovation and rigorous inquiry. About the team WHS Data-Tech's charter is to deliver technology solutions and data insights that help reduce workplace risks and injuries at Amazon. Our customers are Worldwide (WW) Operations and the WHS organization. The technology solutions landscape for WHS Data-Tech includes applications built using native Amazon Web Services (AWS) technologies and device-software hybrid solutions that leverage generative artificial intelligence (AI), computer vision, sensors, and Internet of Things (IoT) technologies. The team also conducts scientific research and modeling to generate safety insights, and provides analytical solutions ranging from senior leadership deliverables to business-unit-specific reports.

Amazon is the 4th most popular site in the US. Our product search engine, one of the most heavily used services in the world, indexes billions of products and serves hundreds of millions of customers world-wide. The Search Query Understanding team is at the forefront of revolutionizing the online shopping experience through the Amazon search page. Our ambition is to transform the search engine into a shopping engine. Leveraging advances in Large Language Models (LLMs), we aim to deeply understanding our users' shopping missions, preferences, and goals. By developing responsive and scalable solutions, we not only accomplish the shopping mission but also foster unparalleled trust among our customers. Through our advanced technology, we generate valuable insights, ensuring a comprehensive and holistic shopping experience. Our dedication to continuous improvement through constant measurement and enhancement of the shopper experience is crucial, as we strategically navigate the balance between immediate results and long-term business growth. We are seeking an Applied Scientist who is not just adept in the theoretical aspects of Machine Learning (ML), Artificial Intelligence (AI), and Large Language Models (LLMs) but also possesses a pragmatic, hands-on approach to navigating the complexities of innovation. The ideal candidate should have a profound expertise in one or more areas including but not limited to Retrieval Augmented Generation (RAG), post-training of foundation models and LLM inference optimizations. You will take the lead in conceptualizing, building, and launching innovative models that significantly improve our understanding of search missions and capabilities in enhancing the search experience. A successful applicant will display a comprehensive skill set across machine learning model development, implementation, and optimization. This includes a strong foundation in data management, software engineering best practices, and awareness of the latest developments in model lifecycle management. We are looking for individuals who are analytically rigorous, passionate about applied sciences, creative, and possess strong logical reasoning abilities. Join the Search Query Understanding team, a group of pioneering ML scientists and engineers dedicated to building core ML models and developing the infrastructure for model innovation. As part of Amazon Search, you will experience the dynamic, innovative culture of a startup, backed by the extensive resources of Amazon.com (AMZN), a global leader in internet services. Our collaborative, customer-centric work environment spans across our offices in Palo Alto, CA, and Seattle, WA, offering a unique blend of opportunities for professional growth and innovation. Key job responsibilities Collaborate with cross-functional teams to identify requirements for ML model development, focusing on enhancing mission understanding through innovative AI techniques, including retrieval-Augmented Generation or LLM in general. Design and implement scalable ML models capable of processing and analyzing large datasets to improve search and shopping experiences. Must have a strong background in machine learning, AI, or computational sciences. Lead the management and experiments of ML models at scale, applying advanced ML techniques to optimize science solution. Serve as a technical lead and liaison for ML projects, facilitating collaboration across teams and addressing technical challenges. Requires strong leadership and communication skills, with a PhD in Computer Science, Machine Learning, or a related field.

Define the joint optimization of model compression and silicon architecture for Amazon's next generation of edge and cloud inference accelerators. Your work will set the technical targets that propagate across the model, compiler, runtime, and silicon stack. We are hiring a Sr. Applied Scientist to be the technical leader who closes the loop between compression science and silicon design. Today's generation ships advanced quantization and large-model distillation in production, running multi-billion parameter language models at inference economics typical of much larger systems. Future generations target significantly larger models at the edge and in the cloud. You will be a senior architect of the next-generation accelerator and of the compression algorithms it executes natively. Few roles in the industry let one technical leader influence the model, the compiler, the runtime, and the silicon without organizational friction. This is one of them. You have spent the last several years thinking about why hardware decisions and accuracy decisions live in different teams, and you want to be the person who owns both. You have published at MLSys, ISCA, MICRO, NeurIPS, or ICML on quantization, pruning, or hardware-aware training, and you want your next paper to ship in a chip rather than in a benchmark suite. You want a vertical stack—model, compression, compiler, runtime, operating system, silicon—where the same engineering organization owns every layer and a sr. architect can move all of them. Key job responsibilities • Define the hardware-aware compression roadmap for next-generation accelerators, working backward from accuracy targets on standard language and reasoning benchmarks including Massive Multitask Language Understanding (MMLU), GSM8K, HumanEval, and Instruction Following Evaluation (IFEval). • Own the joint optimization of compression algorithms (post-training quantization, quantization-aware training, knowledge distillation, structured pruning) with the underlying hardware. • Represent applied science in silicon architecture reviews and influence decisions across the memory and compute subsystems of the accelerator. • Set the science roadmap for the compression techniques the next architecture must support; validate that compression algorithms achieve target accuracy on the benchmarks our products are evaluated against. • Mentor a team of senior and mid-level applied scientists working on compression and hardware-aware training. • Serve as a single-threaded technical leader for the codesign agenda, accountable to senior leadership review. About the team Amazon's Devices and Services organization has shipped multiple generations of first-party silicon for consumer devices. The differentiating intellectual property across this portfolio is a custom machine learning processor co-designed with the compression algorithms it runs. This role sits at the intersection of three teams. The Applied Science team produces compressed model checkpoints. The Silicon Engineering team designs the Application-Specific Integrated Circuits (ASICs). The Compiler and Runtime team lowers compressed models to silicon. You will be the Sr. architect who closes the loop across all three.

The Alexa International Science team is looking for a passionate, talented, and inventive Senior Applied Scientist with a strong background in speech models (understanding and generation) and deep learning, to help build industry-leading Generative AI technology with speech-to-speech models and multilingual systems. At this level, you will drive cross-team scientific strategy for speech quality across international locales, influence partner teams, and deliver solutions that have broad impact across Alexa's global products. Key job responsibilities As a Senior Applied Scientist with the Alexa International team, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art in multilingual speech generation, text-to-speech synthesis, and speech-to-speech models. Your work will directly impact customers across multiple languages in the form of natural, expressive, and locale-appropriate voice experiences for Alexa+. You will leverage Amazon's heterogeneous data sources and large-scale computing resources to accelerate advances in speech synthesis, voice quality, and pronunciation accuracy for non-English locales. The ideal candidate possesses a solid understanding of machine learning, speech synthesis (TTS/S2S), multilingual phonetics, modern model architectures, and evaluation methodology. They thrive in a fast-paced environment, tackle complex challenges in low-resource language settings, excel at delivering impactful solutions while iterating based on customer feedback, and are able to influence and align multiple teams around a shared scientific vision for international speech quality. A day in the life You will start your day reviewing experiment results and iterating on model architectures for speech generation. You will collaborate with software engineers to optimize model performance for production deployment, and partner with product managers to align research priorities with customer needs. You will participate in science reviews, paper reading groups, and brainstorming sessions with fellow scientists across the organization. Your work directly impacts how Alexa sounds and communicates with customers in international markets, making every day an opportunity to solve meaningful problems at global scale. About the team The Alexa International Tech team helps Alexa' global expansion scalable, reliable, and locally relevant for customers. We build the science, engineering, evaluation, and quality platforms behind global AI product delivery: multi-model AI orchestration, multilingual model and data readiness, speech and language quality, reward modeling, synthetic data generation, automated evaluation, developer tooling, defect analysis, and launch mechanisms. Our work sits at the intersection of applied AI, speech, distributed systems, developer experience, and customer quality automation. The goal is simple but hard: help teams build Alexa+ experiences once and scale them across languages, countries, devices, models, and customer expectations without reinventing the same mechanisms every time.

The Alexa International Science team is looking for a passionate, talented, and inventive Senior Applied Scientist with a strong background in speech models (understanding and generation) and deep learning, to help build industry-leading Generative AI technology with speech-to-speech models and multilingual systems. At this level, you will drive cross-team scientific strategy for speech quality across international locales, influence partner teams, and deliver solutions that have broad impact across Alexa's global products. Key job responsibilities As a Senior Applied Scientist with the Alexa International team, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art in multilingual speech generation, text-to-speech synthesis, and speech-to-speech models. Your work will directly impact customers across multiple languages in the form of natural, expressive, and locale-appropriate voice experiences for Alexa+. You will leverage Amazon's heterogeneous data sources and large-scale computing resources to accelerate advances in speech synthesis, voice quality, and pronunciation accuracy for non-English locales. The ideal candidate possesses a solid understanding of machine learning, speech synthesis (TTS/S2S), multilingual phonetics, modern model architectures, and evaluation methodology. They thrive in a fast-paced environment, tackle complex challenges in low-resource language settings, excel at delivering impactful solutions while iterating based on customer feedback, and are able to influence and align multiple teams around a shared scientific vision for international speech quality. A day in the life You will start your day reviewing experiment results and iterating on model architectures for speech generation. You will collaborate with software engineers to optimize model performance for production deployment, and partner with product managers to align research priorities with customer needs. You will participate in science reviews, paper reading groups, and brainstorming sessions with fellow scientists across the organization. Your work directly impacts how Alexa sounds and communicates with customers in international markets, making every day an opportunity to solve meaningful problems at global scale. About the team The Alexa International Tech team helps Alexa+ global expansion scalable, reliable, and locally relevant for customers. We build the science, engineering, evaluation, and quality platforms behind global AI product delivery: multi-model AI orchestration, multilingual model and data readiness, speech and language quality, reward modeling, synthetic data generation, automated evaluation, developer tooling, defect analysis, and launch mechanisms. Our work sits at the intersection of applied AI, speech, distributed systems, developer experience, and customer quality automation. The goal is simple but hard: help teams build Alexa+ experiences once and scale them across languages, countries, devices, models, and customer expectations without reinventing the same mechanisms every time.

The Alexa International Science team is looking for a passionate, talented, and inventive Applied Science Manager with a strong background in speech models (understanding and generation) and deep learning, to lead a team building industry-leading Generative AI technology with speech-to-speech models and multilingual systems. You will lead a team of Applied Scientists, drive cross-team scientific strategy for speech quality across international locales, influence partner teams, and deliver solutions with broad impact across Alexa's global products. You will own programs with global visibility and interact with a cross-functional group of Science, Product, and Engineering leaders. Your team's work will advance the state of the art in multilingual speech generation, text-to-speech synthesis, and speech-to-speech models, directly impacting customers across 20+ languages with natural, expressive, and locale-appropriate voice experiences for Alexa+. You will leverage Amazon's heterogeneous data sources and large-scale computing resources to accelerate advances in speech synthesis, voice quality, and pronunciation accuracy for non-English locales. The ideal candidate possesses a solid understanding of machine learning, speech synthesis (TTS/S2S), multilingual phonetics, modern model architectures, and evaluation methodology. They thrive in a fast-paced environment, tackle complex challenges in low-resource language settings, and are able to influence and align multiple teams around a shared scientific vision. Core Leadership and Team Management - Lead and manage applied scientists focused on multilingual speech generation and voice personality - Build and develop high-performing science teams focused on speech synthesis, pronunciation, evaluation, and multilingual model adaptation - Set technical direction and raise the bar on scientific rigor, experimental methodology, and publication quality - Hire, mentor, and grow scientists at multiple levels Cross-Organizational Collaboration - Partner with cross org stakeholders to align goals and accelerate delivery - Establish clear communication channels and workflows across organizational boundaries - Drive alignment between science roadmaps and product launch timelines across 20+ locales Delivery and Execution - Own end-to-end delivery of speech quality improvements from research through production deployment - Define success metrics and evaluation frameworks for multilingual speech quality - Balance long-term research investments with near-term launch commitments Key job responsibilities * Lead and manage a team of Applied and Data scientists responsible for building and enhancing capabilities for Alexa+ * Collaborate with cross-functional teams to build methods to align Amazon’s LLMs with human preferences. * Identify and prioritize research opportunities that have the potential to significantly impact our AI systems. * Mentor and guide team members to achieve their career goals and objectives. * Communicate research findings and progress to senior leadership and stakeholders. * Rapidly experiment and drive productisation to deliver customer impact. * Drive academic partnership with top tier Indian university as part of the org’s AI/ML Center initiative. * Participate in and drive science publications in peer-reviewed venues of repute. About the team The Alexa International Science team drives multilingual AI quality for Alexa+, ensuring customers across all supported languages receive a natural, accurate, and culturally appropriate voice experience. We work at the intersection of speech science, LLMs, and international product launches.