Principal Applied Scientist, Real-Time Conversational AI , AGI

Amazon is hiring a Principal Applied Scientist, Real-Time Conversational AI , AGI in Sunnyvale, United States. It pays $229k-$309k a year and Level rates it ; you can apply on Amazon.

Level's read on this job

Level rates this applied scientist role Builds AI ●●●●: the job is building AI systems.
The listed pay starts 33% above the typical applied scientist posting on Level.
Tools and skills the posting cites include Runway and speech.
Level lists 21,000+ other open roles at Amazon.
The role was posted in the last few days.

AI in this role

runway

speech

We are looking for a Principal Applied Scientist to drive the research and development of real-time multimodal conversational AI. You will operate across two focus areas: advancing foundation models for speech and audio, and building the post-training systems (reward modeling, reinforcement learning) that shape natural, human-like conversational behavior.

You will be the expert in your area while contributing across the full model lifecycle — from pre-training and architecture design through post-training alignment and real-time deployment. You will work at the frontier of what's possible in conversational AI, with the compute, data, and runway to pursue problems that few teams in the world have the resources to tackle.

As a Principal Scientist, you will set the technical direction for your research area, influence the broader roadmap, and work closely with inference engineers to ensure your models are designed for real-time production deployment from inception.

Key job responsibilities
Foundation Model Scaling

- Build and train large-scale multimodal foundation models for real-time speech and audio generation, from architecture design through production-scale training

- Advance the scaling and efficiency of conversational modes, including the relationship between data, model size, and real time performance.

- Design model architectures informed by hardware constraints and inference requirements, working with inference engineers to ensure models are servable from inception

- Develop training methodologies for multimodal models that jointly process and generate speech, language, and audio in real-time streaming contexts

Post-Training & Reinforcement Learning

- Design and build reward models and reward functions for speech systems — capturing naturalness, fluency, conversational quality, and real-time responsiveness

- Develop and apply reinforcement learning methods to shape conversational behavior — teaching models natural timing, responsiveness, and fluid interaction

- Build the post-training pipeline from SFT through RL alignment, optimized for real-time multimodal outputs rather than text-only generation

- Design evaluation frameworks that capture the quality dimensions unique to real-time conversation

Real-Time Perception & Generation

- Advance the team's capabilities in real-time perception

- Work at the intersection of model architecture and production constraints to ensure multimodal capabilities function within hard real-time latency budgets

About the team
We are a small, focused group of scientists and engineers building the next generation of real-time conversational AI at Amazon — models that interact naturally across speech and audio. We operate with the autonomy and pace of a research lab, backed by frontier-scale compute and a multi-year investment horizon.

Basic qualifications

- Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives
- PhD in Computer Science, Machine Learning, Electrical Engineering, Speech/Audio Processing, or equivalent quantitative field
- 10+ years of applied research experience (industry or combined academic + industry)
- Demonstrated experience training large-scale foundation models — hands-on involvement in scaling exercises, not just using pre-trained models
- Experience with multimodal model architectures that jointly process or generate across speech, text, and audio modalities
- Strong understanding of transformer architectures and their application to speech/audio domains
- Publication record at top-tier venues (NeurIPS, ICML, ICLR, Interspeech, ICASSP, ACL, or equivalent)
- Demonstrated Principal/Staff+ scientific leadership — setting research direction, mentoring researchers, influencing multi-team decisions

Preferred qualifications

- 10+ years of relevant work in industry or academia experience
- Hands-on experience building real-time AI systems — speech, audio, or video
- Track record with post-training methods: reinforcement learning, reward modeling, RLHF/RLAIF, or alignment techniques applied to generative models
- Experience with real-time interactive systems — models that handle concurrent input and output
- Experience building speech-to-speech or audio-to-audio generative models (codec models, autoregressive audio generation)
- Hands-on design of reward models or reward functions specifically for speech/audio quality, naturalness, or conversational behavior
- Experience with distributed training at scale — including parallelism strategies, training stability, and curriculum design
- Familiarity with hardware-informed model design — understanding how architecture choices affect inference latency, memory, and cost
- Background in speech recognition, speech synthesis (TTS), or speech enhancement
- Experience shipping research to production at scale — models serving real users, not just benchmark results
- Contributions to open-source speech/audio ML systems or widely used research codebases
- History of mentoring and growing research teams from individual contributors to technical leaders

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 - 228,700.00 - 309,400.00 USD annually
USA, MA, Boston - 198,900.00 - 269,000.00 USD annually
USA, WA, Seattle - 198,900.00 - 269,000.00 USD annually

How we rate this

Principal Applied Scientist, Real-Time Conversational AI , AGI at Amazon rates 99 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

Principal Applied Scientist, Real-Time Conversational AI , AGI is an open job at Amazon.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $229k-$309k a year.
The role is based in US, CA, Sunnyvale.
The job was posted on October 28, 2026.
Seniority: lead.
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

SpeechRunway

Also common in applied scientist jobs at this level

Python C++Java Deep learning LLM Generative AI

Pay

This job starts at: $229k
Typical applied scientist job: $172k

This posting starts 33% above the typical applied scientist job. See applied scientist jobs

Questions you could be asked

What have you built with speech recognition or text-to-speech, and where did it break?
Walk me through how you've used Runway in your day-to-day work.
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

List these exact terms on your resume: Speech and Runway. 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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