Build AI systems to power personalized patient engagement at scale, developing LLM-based applications and predictive models for patient outcomes in a mission-driven startup.
About Kouper Health
Kouper is redefining how care transitions happen. Backed by General Catalyst, CVS Health Ventures, 25madison, and leading health system partners, we’re on a mission to bridge the care transition gap and fundamentally improve the patient experience — helping people live longer, healthier lives.
Position Overview:
We're looking for a Senior ML Engineer to build the AI systems that power personalized patient engagement at scale. You'll develop and optimize LLM-based applications, build predictive models for patient outcomes, and create the evaluation frameworks that ensure our AI delivers on its promise. This is a foundational role where you'll shape how we apply machine learning to transform healthcare.
Responsibilities
Design and build LLM-powered applications for patient communication and care navigation
Develop predictive models for patient engagement, risk stratification, and care optimization
Build robust evaluation frameworks and metrics to measure model quality, safety, and clinical appropriateness
Architect ML systems that handle diverse healthcare data sources while maintaining privacy and compliance
Optimize model performance for latency, cost, and quality across production workloads
Collaborate with product and clinical teams to translate healthcare problems into ML solutions
Stay current on ML research and bring relevant innovations into production applications
Partner with backend engineers to integrate ML systems into the broader platform architecture
Qualifications
5+ years of experience in machine learning engineering with at least 2 years working with LLMs or NLP systems
Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow, Hugging Face)
Hands-on experience building and deploying LLM-based applications in production
Deep understanding of modern ML techniques: fine-tuning, prompt engineering, RAG, embedding models
Experience designing evaluation frameworks and metrics for ML system quality
Strong software engineering fundamentals with ability to write production-quality code
Excellent problem-solving skills and ability to translate ambiguous requirements into technical solutions
Preferred Qualifications
Experience with healthcare AI applications or clinical NLP
Background in conversational AI, dialogue systems, or voice-based applications
Research experience or publications in ML/NLP
Familiarity with healthcare data standards (HL7, FHIR) and privacy requirements (HIPAA)
Experience with ML infrastructure and MLOps (model serving, monitoring, feature stores)
What We Offer
Competitive salary and equity package
Flexible work environment and remote options
Comprehensive health, dental, and retirement benefits
The chance to make a significant impact in a mission-driven startup focused on transforming patient care
Location: NYC, SF, or Remote
Expected Start Date: Feb 2026
