"Total stack" software development and testing for "Finger Tip Blood Pressure Monitor" (FTBPM): medical device firmware, embedded machine learning library, device middle layers, device to mobile Bluetooth communications, mobile application backend, UI and connectivity to cloud APIs, backend and UI- Led software project team, planning, designing and developing portable (embedded and desktop) blood pressure library in C/C++, following IEC 62304/FDA guidelines and requirements from product management- Translated blood pressure algorithm from machine learning (ML/AI) Python to portable C/C++, including code optimization to improve performance on embedded targets- Developed test plans and scripted test execution for portable blood pressure library- Integrated C/C++ portable blood pressure library into FTBPM device firmware (Nordic nRF53 / Cortex-M33 / Zephyr RTOS)- Designed Bluetooth interface and composed Interface Control Document for FTBPM system, interfacing mobile application to device- Developed Bluetooth FTBPM device firmware (Zephyr RTOS)- Coordinated technical aspects of 3rd party React Native mobile application to complete FTBPM software system- Managed builds and deployment of a 3rd party React Native mobile app using Fastlane, Firebase, TestFlight, and GitHub Actions- Designed and developed GitLab continuous integration / continuous delivery scripts, reporting tools, Docker images and environments for FTBPM portable library, other associated software libraries and device firmware- Developed microservice API and full stack application to analyze data and showcase blood pressure algorithm, running on GCP Kubernetes cloud infrastructure and using GCE / kserve cluster of GPU-enabled machines for machine learning- Collaborated across software domains through code reviews and mentoring

Responsible for and involved with all aspects of software and firmware for biometric wearable devices and their supporting mobile, desktop and cloud applications- Designed and developed embedded, Android and iOS cross-target biometric algorithm library product- Designed and developed Python and React Native APIs for native library for cloud applications, demos and testing- Managed all toolchains, build processes and test infrastructure for native library and API wrappers: GCC for ARM and x64, Clang for x64, with complex cmake build system running on heterogenous suite of Jenkins agents running on Ubuntu Server- Instrumented x64 builds using Valgrind to profile performance and run-time memory usage- Instrumented Clang x64 builds with ASAN / UBSAN to ensure clean runs of comprehensive Google test suite- Designed and developed Android Java/Kotlin, IOS C/Objective-C and React Native (Javascript) testing/logging applications and technical sales demos- Designed and developed demonstration Android applications showcasing newest R&D biometrics at CES- Developed core company biometric algorithm firmware in C/C++, technology implemented in dozens of end-products, from startups to large global brands, with volumes in the millions- Transformed internal processes by installing, configuring and administering on-prem GitLab version control system- Represented Valencell as primary Bluetooth SIG liaison- Overhauled Biometrics Lab processes with Python dashboard application/API using Flask MySql Bootstrap- Administered on-prem Jenkins DevOps instance including developing build and test pipelines- Installed and administered on-prem/private instances of OpenMediaVault, Odoo, LAN DNS, ASA/ASDM, VmWare/ESXi, XenServer, Ubuntu/Debian/Raspbian Linux; responsible for networking those VMs and stand-alone servers