This role exists to translate Blackrock Neurotech’s brain-computer interface research into reliable, regulated, real-time software that reaches users. The Software Team Lead sits at the critical boundary between experimental neural data processing and production-grade, IEC 62304-compliant systems, ensuring that novel concepts in decoding and signal interpretation are transformed into safe, scalable, and maintainable software.
You will lead a team of 5–8 engineers while also contributing hands-on code, setting technical direction, and owning the architecture of the platforms that acquire, process, and interpret real-time neural and physiological signals. You will partner closely with neuroscience, firmware, hardware, clinical, and regulatory teams to ensure software accelerates rather than constrains the path from lab to patient.
Success In This Role Looks Like
You will operate with meaningful ownership in a high-consequence environment, contributing to systems that must be precise, reliable, and durable.
The Impact You'll Make
This is not incremental work. You will help define how humans interact with technology for decades to come. It requires sound judgment, technical depth, and a commitment to getting important things right.
You will:
The Software Team Lead is a hybrid leadership and hands-on engineering role, spending time both guiding a team of 5–8 engineers and directly contributing to the codebase. You’ll move fluidly between architecture design, technical decision-making, regulatory documentation, and day-to-day engineering work, while also owning core people leadership responsibilities such as hiring, onboarding, performance management, goal-setting, and career development.
You will own the technical direction and architecture of Blackrock Neurotech’s BCI application software used across preclinical research, clinical trials, and future medical devices. This means you are responsible for how the platform acquires, processes, and interprets real-time neural and physiological data, and for ensuring it remains scalable, performant, reliable, and compliant as the system grows and moves toward regulated deployment.
On a day-to-day basis, you’ll work on problems at the intersection of real-time, embedded, and regulated medical-device software while collaborating across multiple disciplines to turn complex neuroscience and engineering challenges into shipped systems.