What are the responsibilities and job description for the Staff ML Engineer position at Knowtex?
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
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
- 5 years experience in ML engineering with focus on NLP/speech recognition
- Strong expertise in PyTorch or TensorFlow
- Experience with transformer architectures and large language models
- Proficiency in building production ML pipelines at scale
- Understanding 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 field
- Healthcare or clinical NLP experience
- Familiarity with medical terminology and clinical documentation
- Experience with speech recognition systems (Whisper, Conformer architectures)
- Knowledge of medical coding systems (CPT, ICD-10, SNOMED)
- Publications in ML/NLP conferences
- Meaningful equity compensation
- Unlimited PTO
- Premium health, dental, and vision coverage
- 401(k) plan
- Hybrid work model: 3 days/week in our San Francisco office
Salary : $200,000 - $250,000