Company Overview About Us Raport LLC is a health tech company transforming how data intelligence to enhance cara delivery, and optimize patient outcomes. We’re solving problems at the intersection of data silos, inefficient systems, integration, and AI—using modern machine learning and LLM-driven tools to create the new norm. The Role We’re seeking a Machine Learning Engineer who’s passionate about applying ML in high-impact, real-world healthcare settings. You’ll work directly with our technical and clinical teams to build and optimize tools. This is a high-autonomy, high-impact role where your work goes into production fast. Responsibilities Build and deploy scalable ML models for healthcare use cases Fine-tune and optimize LLM pipelines Engineer dynamic feature pipelines Implement transparency tooling Requirements 1+ years of experience in applied ML or data science Strong Python skills (PyTorch, scikit-learn, Hugging Face Transformers, etc.) Experience working with LLMs (fine-tuning, prompt engineering, deployment) Familiarity with healthcare data standards (EHRs, HL7, FHIR) a major plus Comfort working in fast-moving, agile startup environments Strong communication and documentation skills Nice to Have Experience building decision support tools or clinical workflows Knowledge of HIPAA/GxP compliance frameworks Experience with AWS, GCP, or Azure ML pipelines Background in biostatistics or health outcomes research Why Join Raport Mission-driven team reshaping healthcare delivery Immediate ownership of core features with production impact Flexible remote-first work culture Equity vesting as early critical employee Zero bureaucracy; rapid feedback loops Direct visibility into client and user impact To Apply:Submit your resume and a short note about what excites you about working in ML and health tech. Links to GitHub, published models, or relevant projects encouraged. Job Types: Full-time, Part-time, Contract Pay: $50.00 - $60.00 per hour Benefits: Paid time off Compensation Package: Bonus opportunities Stock options Schedule: Choose your own hours Monday to Friday Weekends as needed Work Location: Remote