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- 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 RequirementsWe 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- 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- 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- 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.)
Ready to Apply?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.
