About this role
RapidClaims is a Series A healthcare startup specializing in AI-driven revenue cycle management. The company is scaling a cloud-native platform that utilizes transformer-based Large Language Models fine-tuned on clinical notes and claims to automate medical coding. As a Machine Learning Engineer, you will be responsible for engineering autonomous coding pipelines, delivering reimbursement insights, and solving complex clinical AI challenges. Key Responsibilities: Develop, deploy, and maintain ML models and pipelines for NLP tasks; design and set up self-hosted models; establish workflows for fine-tuning, feedback loops, and online learning; implement prompt refinement techniques; research and evaluate state-of-the-art AI advancements; streamline processes for scaling; enhance testing tools; and productionize deep learning models. Requirements: Bachelor’s degree in Computer Science, Machine Learning, or a related field; 2-4 years of experience in machine learning or applied AI; strong Python skills with experience in hosting and maintaining models at scale; proficiency in PyTorch or TensorFlow; ability to evaluate research papers; and a solid foundation in ML principles and statistical techniques. Preferred Qualifications: Familiarity with cloud platforms, Docker, and Kubernetes; experience with clinical or biomedical datasets; interest in co-authoring research; knowledge of advanced NLP techniques including prompt engineering; and exposure to signal processing.