Senior Staff Research Scientist, Speech Technologies

Bellevue, WA, US Senior Research Scientist

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Skills & Technologies

PythonPytorch

About This Role

AI job market dashboard showing open roles by category

The Opportunity

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Healthcare has a access problem — not enough clinicians, too many patients, and critical gaps that technology hasn't meaningfully closed. Hippocratic AI is changing that. Our safety\-focused, healthcare\-only LLM platform enables autonomous, clinical\-grade conversations with patients at a scale no human workforce could achieve. With over $404M in funding, a $3\.5B valuation, and partnerships with leading health systems, we're not iterating on existing tools — we're building a new category.

At the center of that platform is voice. As a Senior Staff Research Scientist in Speech Technologies, you'll lead the research and engineering that makes our AI not just intelligent, but genuinely conversational — accurate, fast, and trustworthy in the highest\-stakes environments imaginable.

What You'll Accomplish

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  • You'll define the ASR foundation for healthcare's most advanced conversational AI. From architecture selection to production deployment, you'll shape a speech recognition system built from the ground up for clinical accuracy — one that sets the standard for what's possible when safety and performance aren't trade\-offs.
  • You'll solve speech recognition problems that don't have off\-the\-shelf answers. Medical terminology, diverse patient populations, real\-world acoustic conditions — you'll design and validate models that perform where general\-purpose ASR falls short, pushing the frontier of what conversational AI can reliably understand.
  • You'll build the data infrastructure that makes breakthrough models possible. You'll architect the pipelines and curation processes for large\-scale medical speech datasets, creating the training foundation that gives Hippocratic AI a durable, compounding advantage in clinical speech recognition.
  • You'll bring research into the real world at meaningful scale. You'll close the gap between state\-of\-the\-art methods and production systems — optimizing for latency, accuracy, and resource efficiency so that patients and clinicians experience the results of your work in every conversation.

Location Requirements

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We believe the best ideas happen together. We're on the hunt for a great space in the Bellevue area — and when we find it, this role will be in office five days a week. In the meantime, you'll work fully remote with quarterly trips to our Menlo Park, CA headquarters to connect and collaborate with the team.

Responsibilities

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  • Design, develop, and iterate on data\-driven ASR models for streaming and non\-streaming conversational speech applications
  • Research and implement state\-of\-the\-art end\-to\-end speech recognition architectures tailored to the medical domain
  • Train, evaluate, and optimize ASR models across accuracy, latency, and resource utilization dimensions
  • Preprocess and curate large\-scale speech datasets to support robust model training
  • Collaborate closely with LLM, product, and clinical teams to integrate speech technologies into the broader Hippocratic AI platform
  • Contribute to the team's research culture through experimentation, documentation, and knowledge sharing

Basic Qualifications

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  • PhD with 7\+ years of hands\-on ASR research and engineering experience, or a Master's degree with 10\+ years of industry experience in speech recognition
  • Deep experience designing and developing algorithms for accurate, efficient speech recognition in both streaming and non\-streaming contexts
  • Proven track record training and optimizing ASR models for production — balancing accuracy, latency, and compute constraints
  • Experience preprocessing and curating large speech datasets for model training
  • Strong Python and C\+\+ programming skills
  • Comfortable working in Linux/Unix command\-line environments
  • Clear communicator — you can translate complex technical work for cross\-functional partners

Preferred Qualifications

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  • Hands\-on experience building ASR systems from 0 to 1, including data pipelines, model architecture selection, and evaluation frameworks
  • Practical experience with ESPnet, Kaldi, and PyTorch
  • Experience with CUDA for GPU\-accelerated training and inference
  • Familiarity with leveraging LLMs to enhance speech recognition quality
  • Experience with neural and end\-to\-end endpointer modeling
  • Publications in tier\-1 venues in speech recognition or NLP (Interspeech, ICASSP, ACL, etc.)

What You'll Love About Hippocratic AI

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  • The mission is real. Every improvement you make to speech recognition translates directly into better patient experiences — more accurate conversations, fewer errors, broader access to care for people who currently have none.
  • The team is exceptional. You'll work alongside researchers and engineers from Google, Meta, Microsoft, NVIDIA, and Stanford, as well as clinicians and health system leaders who keep the work grounded in what actually matters to patients.
  • The technical problems are genuinely hard. This isn't fine\-tuning an existing API. It's building a purpose\-built, safety\-critical speech stack for one of the most complex and consequential domains in the world.
  • The strategic moment is now. With $404M raised, a $3\.5B valuation, and real deployments across leading health systems, Hippocratic AI has both the resources and the momentum to define this category — and the equity upside to match.

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Ready to Apply?

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If you've spent your career pushing what speech recognition can do and you want that work to matter in ways that reach millions of patients — we'd like to talk. Apply with your resume and, if you have relevant publications or projects you're proud of, share those too. We review every application and move quickly with candidates who are a strong fit.

Role Details

Company Hippocratic AI
Title Senior Staff Research Scientist, Speech Technologies
Location Bellevue, WA, US
Category Research Scientist
Experience Senior
Salary Not disclosed
Remote No

About This Role

Research Scientists push the boundaries of what AI can do. They design experiments, develop novel architectures, publish papers, and translate research breakthroughs into production capabilities. This is where the fundamental advances happen, from attention mechanisms to diffusion models to reasoning chains.

The work is intellectually demanding and often ambiguous. You might spend months on an approach that doesn't pan out. The best research scientists combine deep mathematical intuition with engineering pragmatism. They know when to go deep on theory and when to run experiments. They read papers voraciously and can spot incremental contributions from genuine breakthroughs.

Across the 3,823 AI roles we're tracking, Research Scientist positions make up 3% of the market. At Hippocratic AI, this role fits into their broader AI and engineering organization.

Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.

What the Work Looks Like

A typical week includes: reading and discussing recent papers with your team, designing and running experiments on multi-GPU clusters, analyzing results and iterating on hypotheses, writing up findings for internal review or publication, and collaborating with engineering teams to productionize promising results. The ratio of thinking to coding is higher than in engineering roles.

Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.

Skills Required

Python (52% of roles) Pytorch (16% of roles)

PhD strongly preferred for most roles. Deep expertise in a specific area (NLP, computer vision, reinforcement learning, multimodal) is expected. PyTorch is the standard. Publication track record matters. Strong mathematical foundations in linear algebra, probability, optimization, and information theory are assumed.

Beyond the fundamentals, companies value experience with large-scale distributed training, novel architecture design, and the ability to bridge theory and practice. Understanding of current frontier topics (reasoning, multimodal, long-context, alignment) is essential. Code quality matters more than many researchers expect. Labs want researchers who can implement their ideas cleanly.

Strong research postings specify the research area, mention the team you'd join, and describe the problems they're working on. They often list recent publications from the team. Vague 'AI research' postings without specifics usually mean the company wants to sound impressive but doesn't have a real research agenda.

Compensation Benchmarks

Research Scientist roles pay a median of $223,400 based on 280 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400.

Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.

Hippocratic AI AI Hiring

Hippocratic AI has 1 open AI role right now. They're hiring across Research Scientist. Based in Bellevue, WA, US.

Location Context

Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 median).

Career Path

Common paths into Research Scientist roles include PhD Student, Research Engineer, Postdoc.

From here, career progression typically leads toward Research Lead, Distinguished Scientist, VP of Research.

The PhD is the entry point for most paths. Choose your advisor and research area carefully since they'll define your first industry position. Publish consistently, contribute to open-source projects in your area, and build relationships at conferences. Industry research offers better compensation and compute resources than academia, but the pressure to show product impact is real.

What to Expect in Interviews

Research interviews are multi-stage: a research talk (present your best paper), technical deep-dives on your methodology, and often a 'research proposal' exercise where you design an experiment to test a hypothesis. Coding rounds test implementation ability alongside theoretical knowledge. Be prepared to implement a paper from scratch and discuss the design choices the authors made. Strong candidates can critique papers constructively and identify gaps in experimental methodology.

When evaluating opportunities: Strong research postings specify the research area, mention the team you'd join, and describe the problems they're working on. They often list recent publications from the team. Vague 'AI research' postings without specifics usually mean the company wants to sound impressive but doesn't have a real research agenda.

AI Hiring Overview

The AI job market has 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.

The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 roles).

Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.

The AI Job Market Today

The AI job market spans 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.

The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (112) are outnumbered by mid-level (1,798) and senior (1,516) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 397 positions, representing the bottleneck between technical execution and organizational strategy.

Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.

AI compensation is structured in clear tiers. The market median sits at $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.

Category matters for compensation. AI Engineering Manager roles lead at $275,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.

The most in-demand skills across all AI postings: Python (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.

Frequently Asked Questions

Based on 280 roles with disclosed compensation, the median salary for Research Scientist positions is $223,400. Actual compensation varies by seniority, location, and company stage.
PhD strongly preferred for most roles. Deep expertise in a specific area (NLP, computer vision, reinforcement learning, multimodal) is expected. PyTorch is the standard. Publication track record matters. Strong mathematical foundations in linear algebra, probability, optimization, and information theory are assumed.
About 15% of the 3,823 AI roles we track offer remote work. Remote availability varies by company and seniority level, with senior and leadership roles more likely to offer location flexibility.
Hippocratic AI is among the companies actively hiring for AI and ML talent. Check our company profiles for detailed breakdowns of open roles, salary ranges, and hiring trends.
Common next steps from Research Scientist positions include Research Lead, Distinguished Scientist, VP of Research. Progression depends on whether you lean toward technical depth, people management, or product strategy.

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