Senior Staff Research Scientist, Speech Technologies

About the role

The Senior Staff Research Scientist in Speech Technologies at Hippocratic AI will lead the development of advanced speech recognition systems for healthcare applications. This role involves defining and implementing state-of-the-art ASR models, preprocessing and curating large speech datasets, and collaborating with interdisciplinary teams to integrate speech technologies into the Hippocratic AI platform.

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

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
• 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
• Publishations in tier-1 venues in speech recognition or NLP (Interspeech, ICASSP, ACL, etc.)