Knowtex
ML Scientist (Research)
San Francisco · Exec
Sponsorship not specifiedDetected 140 days ago
PythonAWSGCPPlatform EngineeringMachine LearningTensorFlowPyTorchData EngineeringNLPLLMsAgentic AIComplianceHIPAAICD-10Research
About the role
- 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.
- This role reports to the CTO and plays a central part in defining the next generation of clinical AI infrastructure.
Responsibilities
- Research and implement clinical NLP pipelines for automated E&M coding and ICD-10 classification
- Design and evaluate note quality scoring systems using LLMs and structured clinical rubrics
- Create specialty-specific language models (e.g., gastroenterology, dermatology, emerging markets)
- Design and prototype agentic AI systems for clinical decision support and documentation assistance
- Optimize models for real-time inference with sub-200ms latency requirements
- Build rigorous evaluation frameworks for clinical accuracy, MDM validation, and MIPS quality measure compliance
- Collaborate with clinical experts to validate outputs and ensure alignment with regulatory and documentation standards
- Proven ability to design and build production-grade ML pipelines at scale
Requirements
- Strong expertise in PyTorch or TensorFlow
- Deep experience with transformer architectures and large language models
- Strong understanding of model optimization techniques (quantization, distillation, pruning)
- Experience working with cloud ML platforms (AWS SageMaker, GCP Vertex AI, or equivalent)
Nice to have
- Experience with speech recognition systems (Whisper, Conformer architectures, etc.)
- Publications in leading ML/NLP conferences
- Experience deploying models in regulated environments (e.g., GovCloud, HIPAA-compliant systems)
- Python, PyTorch, TensorFlow
- Transformer-based LLM architectures
- Triton Inference Server (AWS GovCloud deployments)
- AWS (SageMaker, EKS, S3, Lambda)
- Real-time inference systems with strict latency constraints (<200ms)
Compensation
- Meaningful equity compensation
Benefits
- Develop and optimize models for medical speech recognition across 200+ specialties
- 5+ years of experience in machine learning research or ML engineering with a focus on NLP and/or speech recognition
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