ML Engineer: Speech & LLMs
Core
Build state-of-the-art medical speech-to-text systems and optimize large language models for clinical documentation and structured clinical reasoning.
Role type
Senior IC machine-learning researcher (speech/audio or LLMs)
Builds
Production speech recognition models and clinical documentation generation systems for healthcare providers
Domain
Healthcare AI, clinical NLP, medical speech
Deliverable
production ML models
Required skills
Python, PyTorch, transformer architectures, model training and fine-tuning, experimental design, large-scale dataset handling, distributed training, model evaluation and benchmarking
Preferred skills
automatic speech recognition (ASR), Whisper/Conformer/wav2vec architectures, supervised fine-tuning/distillation/preference optimization, structured generation, agentic systems, healthcare AI, clinical documentation workflows, ICD-10/CPT/SNOMED coding systems
Technologies
AWS, PyTorch, transformer-based LLM and speech architectures, open-weight and frontier language models, GPU-based model serving
Responsibilities
Develop and train speech recognition models optimized for medical conversations; Build models for downstream clinical tasks such as medication extraction and ICD-10 coding; Design experiments to measure improvements in real-world clinical outcomes; Build datasets, benchmarks, and evaluation infrastructure; Collaborate with clinicians and platform engineers to deploy models into production; Optimize models for low-latency, real-time inference at production scale
Seniority
Senior, hands-on IC