Sr. Applied Scientist, Alexa Enterprise

Amazon is hiring a Sr. Applied Scientist, Alexa Enterprise in Seattle, United States. It pays $192k-$260k a year and Level rates it ; you can apply on Amazon.

Level's read on this job

On Level's scale, this applied scientist role is Builds AI ●●●●: the job is building AI systems.
The listed pay starts 12% above the typical applied scientist posting on Level.
Tools and skills the posting cites include fine tuning, AI evaluation and speech.
Level classifies it as a senior role.
Level lists 20,000+ other open roles at Amazon.

AI in this role

Lead scientific development to improve speech-to-text accuracy and audio pipeline performance for Alexa Enterprise.

fine-tuningai-evaluationspeechmachine-learningspeech-recognitionaudio-processingmodel-fine-tuninginference-optimization

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 employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

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 - 192,200.00 - 260,000.00 USD annually
USA, WA, Seattle - 167,100.00 - 226,100.00 USD annually

How we rate this

Sr. Applied Scientist, Alexa Enterprise at Amazon rates 95 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Sr. Applied Scientist, Alexa Enterprise is an open job at Amazon.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $192k-$260k a year.
The role is based in US, WA, Seattle.
The job was posted on September 4, 2026.
Seniority: senior.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Fine-tuningAI EvaluationSpeechMachine learningSpeech RecognitionAudio ProcessingModel Fine TuningInference Optimization

Also common in applied scientist jobs at this level

LLM Generative AI NLP Reinforcement learning TensorFlow Spark

Pay

This job starts at: $192k
Typical applied scientist job: $172k

This posting starts 12% above the typical applied scientist job. See applied scientist jobs

Questions you could be asked

Walk me through fine-tuning a model: what data did you use, and how did you check the result?
How do you decide that one model's output is better than another's for a given task?
What have you built with speech recognition or text-to-speech, and where did it break?
Tell me about a project where machine learning was part of your work. What did you do?
Tell me about a project where speech recognition was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Fine-tuning, AI Evaluation, Speech, Machine learning, and Speech Recognition. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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