Senior Advanced Algorithm Engineer - Electrophysiology

Develop and implement advanced processing algorithms for complex biological signals with a focus on robustness, scalability, and clinical relevance. Support feasibility studies, prototyping, and technical evaluations to enable successful transition into commercial products. Collaborate closely with the Concept Development Team, contributing to ideation, algorithm design, and iterative refinement. Produce high‑quality technical documentation and follow best practices in software engineering and algorithm development. Work cross‑functionally with Hardware, Software, Systems, and Upstream Marketing teams to ensure cohesive system integration. Partner with physicians, product managers, and regulatory teams to understand clinical needs and translate them into algorithmic requirements. Contribute to continuous improvement of development workflows, tools, and methodologies. Stay informed on emerging technologies—including AI, machine learning, and advanced signal processing—and apply them where appropriate. Participate in technical discussions, design reviews, and collaborations with academic or industry partners as needed. Advanced degree (M.S. required; Ph.D. preferred) in Computer Science, Electrical Engineering, Biomedical Engineering, or a related field. 5+ years of experience in product development within commercial or regulated environments, with demonstrated contributions to innovative solutions. Strong proficiency in C++, MATLAB, Python, or equivalent languages for prototyping, modeling, and data analysis. Experience with modern source code management tools (Git required; AccuRev experience a plus). Solid foundation in data structures, mathematics, applied statistics, and optimization techniques. Background in medical applications, biomedical signal processing, or electrophysiology is highly desirable. Strong communication skills and the ability to work effectively in cross‑functional teams. Experience applying machine learning, inverse problems, or advanced modeling techniques to real‑world engineering challenges. Evidence of technical contributions such as publications, patents, or conference participation is a plus.