Senior Applied Scientist — Enterprise Speech & AI

Amazon; Sunnyvale (CA); On-site; USD 192,000 - 260,000; Full time

Job summary

Amazon.com Services LLC's Alexa Enterprise team seeks a Senior Applied Scientist with a strong background in speech and audio ML to lead scientific direction and production-ready solutions at the intersection of Alexa AI and AWS cloud services. You will work with enterprise customers to validate improvements and scale capabilities.

You will mentor teams, guide model evaluation, and help shape platform capabilities while delivering real customer impact in a fast-moving environment.

Qualifications

• 3+ years building ML models for business applications.
• PhD, or Master's with 6+ years of applied research.
• Proficiency in Java, C++, or Python.
• Experience with neural deep learning methods and machine learning.

Responsibilities

• Set scientific direction for improving speech-to-text accuracy across domain-specific use cases and conditions.
• Lead evaluation, adaptation, and fine-tuning of speech/audio models considering accuracy, latency, cost, reliability, and deployment constraints.
• Drive performance and latency improvements of end-to-end audio pipelines from processing to transcription.
• Define datasets, benchmarks, experiments, and evaluation methodologies reflecting customer use cases.
• Collaborate with software engineers to productionize models and measure deployment impact.
• Translate customer insights into reusable models and evaluation methods for broader use.

Skills

Programming languages (Java/C++/Python

Deep learning

ML for business applications

Education

PhD or Masters with 6+ years applied research

Job description

Amazon.com Services LLC's Alexa Enterprise team seeks a Senior Applied Scientist with a strong background in speech and audio ML to lead scientific direction and production-ready solutions at the intersection of Alexa AI and AWS cloud services. You will work with enterprise customers to validate improvements and scale capabilities.

You will mentor teams, guide model evaluation, and help shape platform capabilities while delivering real customer impact in a fast-moving environment.