Staff ML Engineer

Reposted 3 Days Ago
San Francisco, CA
In-Office
200K-250K Annually
Senior level
Healthtech • Software
The Role
As a Staff ML Engineer, you will develop models for medical speech recognition and clinical NLP, optimizing performance for real-time applications and collaborating with clinical teams on validation and evaluation frameworks.
Summary Generated by Built In

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 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

Preferred Qualifications

  • 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

Benefits

  • 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

Top Skills

Aws Govcloud
Aws Sagemaker
Gcp Vertex Ai
Ml
Nlp
PyTorch
TensorFlow
Triton Inference Server
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The Company
HQ: San Francisco, California
12 Employees

What We Do

Knowtex captures natural conversation between a clinician and patient, identifies relevant medical information, and generates a pre-filled note with medical coding suggestions, for clinician review and sign-off.

For clinicians, we’re decreasing time spent on manual documentation and allowing them to focus on patient care. For healthcare organizations, we’re improving accuracy and efficiency in medical billing and coding to help with reimbursements.

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