Sr. Applied Scientist, Alexa Enterprise

Are you excited about building at the intersection of enterprise AI and customer experience? Are you passionate about applying science to real customer problems? Do you want your work shaped by real-world conditions and validated through customer deployments? The Alexa Enterprise team is looking for a passionate, talented, and inventive Senior Applied Scientist with a strong background in speech and audio machine learning who thrives in a startup-style environment. In this role, you'll set scientific direction and lead the development of techniques to improve speech-to-text accuracy for domain-specific use cases and optimize the performance and latency of end-to-end audio pipelines. You'll lead work across model evaluation and selection, fine-tuning, data and evaluation strategies, and real-time inference optimization. You'll partner closely with software engineers to turn scientific advances into production capabilities, while working with enterprise customers to understand how speech and audio systems perform in their environments. You'll turn improvements inspired by one customer's needs into capabilities that serve many, while influencing teams around a shared scientific vision. We're a small, fast-moving team building AI-powered solutions at the intersection of Alexa AI capabilities and AWS cloud services. Our customers span healthcare, energy, retail, and insurance, and they're deploying in environments where the technical challenges are real and the feedback loops are immediate. Key job responsibilities - Set the scientific direction for improving speech-to-text accuracy across domain-specific use cases and real-world operating conditions - Lead the evaluation, selection, adaptation, and fine-tuning of speech and audio models based on accuracy, latency, cost, reliability, and deployment constraints - Drive improvements to the performance and latency of end-to-end audio pipelines, from signal processing and streaming through inference and transcription - Define datasets, benchmarks, experiments, and evaluation methodologies that reflect customer use cases - Lead the optimization of models and inference pipelines for reliable, real-time operation - Work directly with enterprise customers to understand quality challenges, validate scientific improvements, and identify opportunities for broader platform capabilities - Turn patterns from customer engagements into reusable models, evaluation methods, and scientific capabilities that scale across customers and industries - Influence and collaborate with software engineering and partner teams to productionize models, measure their performance, and continuously improve deployed systems - Write scientific and technical documents, lead reviews, and communicate experimental results and trade-offs to engineering, product, and business leaders - Mentor Applied Scientists and engineers, participate in hiring, and raise the team's science and engineering standards About the team The Alexa Enterprise team builds AI-powered solutions for businesses. We work with enterprise customers across healthcare, energy, retail, and insurance to deploy solutions that transform operations. Our team operates at the intersection of Alexa AI capabilities and AWS cloud services, partnering closely with AWS sales, product, and specialist teams to deliver customer outcomes. Our work brings together applied AI, speech and audio science, real-time systems, and cloud services. Senior Applied Scientists on the team have real ownership, from identifying and framing customer problems through setting scientific direction, experimentation, production integration, and measurement of customer impact. This is an opportunity to lead meaningful scientific work while helping shape a platform in its early stages.