Applied Scientist, Alexa Enterprise

Amazon.com Services LLC; Seattle (WA); On-site; USD 210,000 - 320,000; Full time

Job summary

Amazon.com Services LLC is seeking a Senior Applied Scientist specializing in speech and audio machine learning to advance ASR for domain-specific use cases and optimize end-to-end audio pipelines.

You will set strategic direction, lead model evaluation and inference optimization, and collaborate with enterprise customers and software engineers to productionize scientific advances at scale.

Qualifications

• 3+ years building ML models for business application
• PhD or Master’s +6 years applied research
• Experience programming in Java, C++, Python or related language
• Experience with neural deep learning methods and ML

Responsibilities

• Set the scientific direction for improving speech-to-text accuracy across domain-specific use cases and real-world operating conditions
• Lead 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 reflecting customer use cases
• Lead the optimization of models and inference pipelines for reliable, real-time operation
• Work with enterprise customers to understand quality challenges and validate improvements
• Translate customer engagements into reusable models and evaluation methods
• Collaborate with software engineers to productionize models and measure deployed systems
• Write scientific documents, lead reviews, and communicate results to leaders
• Mentor scientists and engineers and help raise team standards

Skills

Speech/audio ML

ML research

Real-world deployment

Leadership

Beamforming

Echo cancellation

Noise reduction

Education

PhD in related field

Master's + 6+ years applied research

Tools

Java

C++

Python

Job description

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.

Basic Qualifications:

• 3+ years of building machine learning models for business application experience
• PhD, or Master's degree and 6+ years of applied research experience
• Experience programming in Java, C++, Python or related language
• Experience with neural deep learning methods and machine learning

Preferred Qualifications:

• PhD or equivalent research experience, or a PhD and experience in patents or publications at top-tier peer-reviewed conferences or journals
• Experience leading a science team
• 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

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with e