Applied Research Scientist, Clinical AI

Applied Research Scientist, Clinical AI Remote US - significant overlap with PST hours | Full-Time Employee | Engineering RhythmScience Inc. We believe that healthcare should be proactive, not reactive. Research shows that continuous remote monitoring can reduce hospital visits and improve patient survival rates by over 50%. Our solutions ensure that cardiac patients receive timely care, minimizing risks and enhancing quality of life. Role Overview We are entering an exciting phase of growth and heavily leaning into clinical AI for our H2 roadmap. As an Applied Research Scientist, Clinical AI, you will own the dedicated machine learning depth required to scale our AI Data Viz, AI Report Builder and Heart Failure AI features. Reporting directly to the Head of Engineering, you won’t just build models in isolation - you will own model quality, evaluation, and prediction deployment. You will turn complex cardiac data into the real-world population-outcomes reporting our customers are asking for, bringing velocity and rigor to our engineering organization. This is a US-remote position with close, asynchronous collaboration across US time zones Key Responsibilities Design & Deploy Rigorous Evaluations: Define clinical “correctness” for ML outputs and catch critical clinical errors beyond basic average accuracy so that our features are fundamentally safe for patient data Ship Production Models: Take models completely from experimental notebooks to live, working services integrated with our RS360 backend application Build Population Analytics : Develop cohort and outcome analytics from messy, patient-level monitoring data, accurately accounting for confounders Measure & Iterate Quality: Establish historical backtesting against human-written notes to build trust with internal engineering, product, and clinical teams Protect Patient Privacy Handle Protected Health Informatio n (PHI) safely, striking the optimal balance between data utility and compliance privacy tradeoffs Required Skills & Qualifications Core Tech Stack: Advanced proficiency in Python, PyTorch (or equivalent framework) and SQL Domain Expertise: Demonstrated experience building and deploying clinical or biomedical ML models (using EHR, time-series, sensor, or imaging data) Data Fluency: Deep comfort dealing with real-world, messy, sparse or weakly labeled device data Evaluation Integrity: Strong grasp of ML evaluation methodologies, including data leakage prevention and customized metric design Communication: Exceptional written communication skills to thrive and exert technical influence across our remote, asynchronous team Advanced degree in related field Compensation Details: The salary for this position is currently being benchmarked, but will include an annual salary, plus bonus, equity ownership opportunity, and benefits. In determining your salary, we will consider your location, experience, and other job-related factors. RhythmScience is…