Join to apply for the Staff ML Engineer role at Knowtex
Join to apply for the Staff ML Engineer role at Knowtex
This range is provided by Knowtex. Your actual pay will be based on your skills and experience talk with your recruiter to learn more.
Base pay range
$200,000.00 / yr - $250,000.00 / yr
About Knowtex
Knowtex is building the future of voice AI operating systems for clinicians, transforming how healthcare documentation happens at the point of care. Founded by Stanford AI scientists with deep clinical experience, we're experiencing explosive growth across both commercial health systems and federal healthcare, with our ambient documentation platform scaling rapidly to thousands of clinicians across hundreds of specialties. We're at an inflection point where cutting-edge AI meets real clinical impact, giving clinicians hours back each day to focus on what matters most - their patients.
Position Overview
We're seeking a Staff ML Engineer to advance our voice AI and clinical NLP capabilities. You'll work on cutting?edge problems in medical speech recognition, clinical language understanding, and agentic AI systems for healthcare.
Key Responsibilities
- Develop and optimize models for medical speech recognition across 200+ specialties
- Build clinical NLP pipelines for automated E&M coding and ICD-10 classification
- Implement note quality evaluation systems using LLMs and clinical rubrics
- Scale inference infrastructure using Triton Inference Server on AWS GovCloud
- Create specialty?specific language models for gastroenterology, dermatology, and emerging markets
- Design agentic AI systems for clinical decision support and documentation assistance
- Optimize model performance for real?time inference with sub?200ms latency requirements
- Collaborate with clinical teams to validate model outputs against MDM levels
- Build evaluation frameworks for MIPS quality measures compliance
Required Qualifications
5+ years experience in ML engineering with focus on NLP / speech recognitionStrong expertise in PyTorch or TensorFlowExperience with transformer architectures and large language modelsProficiency in building production ML pipelines at scaleUnderstanding of model optimization techniques (quantization, distillation, pruning)Experience with cloud ML platforms (AWS SageMaker, GCP Vertex AI)Master's or PhD in Computer Science, ML, or related fieldPreferred Qualifications
Healthcare or clinical NLP experienceFamiliarity with medical terminology and clinical documentationExperience with speech recognition systems (Whisper, Conformer architectures)Knowledge of medical coding systems (CPT, ICD-10, SNOMED)Publications in ML / NLP conferencesBenefits
Meaningful equity compensationUnlimited PTOPremium health, dental, and vision coverage401(k) planHybrid work model : 3 days / week in our San Francisco officeSeniority level
Mid-Senior level
Employment type
Full-time
Job function
Engineering and Information Technology
Industries : Hospitals and Health Care
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