In this role, you'll develop and apply scientific 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 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. The improvements inspired by one customer's needs become capabilities that serve many.
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
- Develop and apply modeling techniques to improve speech-to-text accuracy for domain-specific use cases and real-world operating conditions
- Evaluate, select, adapt, and fine-tune speech and audio models based on accuracy, latency, cost, reliability, and deployment constraints
- Improve the performance and latency of end-to-end audio pipelines, from signal processing and streaming through inference and transcription
- Design datasets, benchmarks, experiments, and evaluation methodologies that reflect customer use cases
- Optimize 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
- Collaborate with software engineers 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 stakeholders
- Contribute to the team's scientific direction, mentor teammates, participate in hiring, and improve science and engineering processes
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. Applied Scientists on the team have real ownership, from identifying and framing customer problems through experimentation, production integration, and measurement of customer impact. This is an opportunity to solve meaningful scientific problems while helping shape a platform in its early stages.
BASIC QUALIFICATIONS
- 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience programming in Java, C++, Python or related language
- Knowledge of standard speech and machine learning techniques
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
PREFERRED QUALIFICATIONS
- Have publications at top-tier peer-reviewed conferences or journals
- Experience applying machine learning to speech or audio processing, including generative models, speech enhancement, source separation, or related applications
- Familiarity with voice-processing techniques such as beamforming, acoustic echo cancellation, and noise reduction
- Experience optimizing speech or audio models for real-time, low-latency production systems
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, CA, Sunnyvale - 171,600.00 - 222,200.00 USD annually
USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually
