Algorithm Engineer - Automated Insulin Delivery (AID)

We are seeking an Algorithm Engineer to join the core development team building next-generation Automated Insulin Delivery (AID) technology. This individual will play a key role in the design, implementation, simulation, and evaluation of closed-loop glycemic control algorithms used within a safety-critical medical device environment. This role sits at the intersection of algorithm development, control systems, physiological modeling, and medical device software engineering. Candidates should bring direct experience within automated insulin delivery, closed-loop diabetes systems, insulin pump technologies, CGM-integrated systems, or highly related physiological control applications. We are open to a range of experience levels — from highly technical M.S./Ph.D. candidates coming from directly relevant diabetes technology research environments to experienced industry engineers who have contributed to commercial AID or insulin delivery platforms. Responsibilities Design and refine closed-loop insulin dosing algorithms focused on safety, robustness, and glycemic performance Develop and tune control-system components including predictive control, parameter optimization, meal/exercise response handling, and glucose trend analysis Implement algorithms in Python and/or C/C++ for simulation and embedded deployment environments Contribute to development of next-generation insulin delivery and glucose prediction capabilities Build, maintain, and extend in silico simulation frameworks used to evaluate algorithm performance Design simulation studies evaluating edge cases, CGM signal behavior, insulin delivery variability, and patient population diversity Analyze algorithm performance using clinically relevant glycemic metrics and statistical methodologies Support translation of simulation performance into clinical validation activities Support preparation of algorithm releases for feasibility and clinical studies Analyze CGM, pump, and clinical study datasets to identify algorithm behaviors, failure modes, and optimization opportunities Participate in verification, validation, and systems-level testing activities Collaborate cross-functionally with software, systems, clinical, quality, and regulatory teams throughout product development Develop clean, testable, and maintainable code within a regulated software development environment Support software documentation, algorithm specifications, verification activities, and traceability efforts Contribute to reproducible simulation environments and software lifecycle best practices Requirements B.S., M.S., or Ph.D. in Biomedical Engineering, Electrical Engineering, Computer Science, Applied Mathematics, Controls Engineering, or a related technical field Direct experience in one or more areas including: Automated Insulin Delivery (AID,) Closed-loop insulin delivery systems, Artificial pancreas technologies, Insulin pump algorithms, CGM-integrated control systems, Diabetes simulation/modeling environments Strong understanding of glucose-insulin physiology, insulin pharmacodynamics/pharmacokinetics, CGM behavior, and insulin delivery system interactions Experience with control systems and predictive algorithms applied to physiological or safety-critical systems Programming experience in Python and/or C/C++ Experience building or working within simulation/modeling environments Familiarity with clinical data analysis, time-series physiological data, or wearable device datasets Exposure to regulated medical device software development practices is strongly preferred Strong systems-thinking mindset with the ability to operate within a highly collaborative technical environment #J-18808-Ljbffr BioTalent