AI Researcher / ML Engineer

About The Role

We're looking for an AI Researcher / ML Engineer to lead the development of intelligent features across TERP. Healthcare generates rich, structured data — therapy session notes, scheduling patterns, billing cycles, patient progress trajectories — and we're building the AI layer that turns this data into actionable clinical and operational insights. You'll work on problems like: automated clinical note summarization using LLMs, intelligent scheduling optimization that accounts for therapist specializations and patient needs, predictive models for patient no-shows and billing anomalies, and NLP pipelines that extract structured data from Hebrew-language therapy notes. This is an applied research role. We don't publish papers for the sake of publishing — we ship models that run in production and make real healthcare professionals' lives measurably better. You'll own the full ML lifecycle: problem formulation, data exploration, model development, evaluation, deployment, and monitoring. You'll work closely with our engineering team to integrate models into the product and with our customer-facing teams to understand the clinical workflows your models need to support. Healthcare AI is uniquely rewarding — every model you ship has the potential to improve patient outcomes at scale.

Requirements

• 4+ years of experience in machine learning, NLP, or AI research — academic or industry
• Strong programming skills in Python with experience in PyTorch, TensorFlow, or JAX
• Hands-on experience with Large Language Models — fine-tuning, prompt engineering, RAG architectures, evaluation
• Experience deploying ML models to production — model serving, monitoring, drift detection
• Strong statistical foundations — experimental design, hypothesis testing, evaluation methodology
• Ability to translate ambiguous business problems into concrete ML formulations
• Experience working with real-world messy data — missing values, class imbalance, noisy labels
  
  

• Experience with Hebrew NLP — tokenization, morphological analysis, pre-trained Hebrew models
• Healthcare AI experience — clinical NLP, EHR data mining, medical ontologies
• Experience with Google Cloud AI/ML services (Vertex AI, Cloud Functions for inference)
• Published research in relevant domains (NLP, healthcare AI, recommender systems)
• Experience with data privacy frameworks relevant to healthcare (anonymization, differential privacy)
  
  

• Competitive salary with significant equity participation
• Hybrid work model — Holon office + remote flexibility
• Flexible working hours
• Comprehensive health insurance
• GPU compute budget for research and experimentation
• Conference and publication budget
• Opportunity to build healthcare AI from the ground up