Greg Kubiski-Moshansky
Embedded & Systems Software Engineer
I build embedded Linux and systems software for sensor-driven edge devices, usually in industrial safety, monitoring, and automation use cases.
My work experience has been centered around performance-sensitive Linux systems, sensor integration, computer vision deployment, kernel and platform work, and the tooling needed to deploy and maintain systems in the field.
I spent years strengthening my understanding of computer architecture, operating systems, and software engineering fundamentals, to become competently able to reason (from the hardware up) how to improve performance, reliability, and scalability of complex systems.
On the side, I am currently expanding functionality for my own home-made programming language + compiler, and am separately building a custom game engine (for a passion project I started planning nearly a decade ago).
Experience
Embedded / Robotics Software Engineer
Correct-AIIndustrial robotics and safety systems work across NVIDIA Jetson edge devices, microcontroller boards, and the cloud plumbing needed to keep deployed hardware visible and supportable. Most of that time has been in C, C++, and Python on Linux-based systems for heavy equipment, vehicles, and industrial monitoring.
Software Engineer / Advisor
Quantum and Nanotechnologies Research Centre (NRC)Advised physics and chemistry graduate researchers on technical and programming work, while building camera control, image analysis, data collection, and scientific data visualization tools for solid-state battery experiments.
Skills
Primary languages
C, C++, Python, TypeScript
Core areas
Embedded Linux, systems programming, hardware integration, computer vision deployment, sensor integration (camera / LiDAR / microcontrollers), concurrency, performance debugging, robotics, and distributed systems
Supporting
AWS infrastructure, PostgreSQL, FastAPI, Qt/QML, GStreamer, ROS 2, and Next.js/React when the job calls for it
~12 years programming (since 2014), ~2 years professional software engineering, ~15 years total workforce experience across technical and customer-facing roles.
Recent Projects
Selected work
- PROX-EYE: Led the complete redesign of our edge vision stack from a tightly coupled NVIDIA Jetson/Python system into a modular C++ pipeline. Built the multi-camera GStreamer path, shared-memory preview and detection logic, inference scheduling, event recording, user authorization, and fault handling needed for unreliable field deployments. Reduced application start time from roughly 30 seconds to under 2 seconds, increased overall in-app performance, and reduced system resource usage (despite significantly more constrained hardware).
- FIELD-EYE - LiDAR Volume Analysis and Berm Height Violation Detection: Lead engineer for a LiDAR-based mining safety and earth-volume analysis system. Rebuilt the volume-calculation and point-cloud visualization interface for cleaner, faster operator review, while handling field-facing bug fixes, testing, and validation around berm height violation detection.
- nex & nexc compiler: Built the nex systems language and nexc reference compiler with hand-written frontend, typed IR, and MLIR/LLVM lowering to native executables via a C++/CMake toolchain.
- ESP32 Environment Sentinel: Personal ESP32 firmware project using ESP-IDF and FreeRTOS to build a low-power room monitor around environmental and air-quality sensors.
Additional work
- Autonomous Valet Parking (AVP): Wrote ESP32 firmware and ROS 2 code for a research platform that coordinates a Walter ESP32 board with an AGX Orin controller to ultimately autonomously park/retrieve vehicles.
- Jetson platform work: Made kernel, device tree, bootloader/UEFI, and OS-level customizations and optimizations on NVIDIA Jetson Orin NX and Xavier NX edge devices, cutting boot times by over 40 percent while maintaining our deployment and flashing workflows.
- Earlier PROX-EYE platform work: Earlier Jetson-based PROX-EYE work spanning deployment imaging, object detection, LiDAR processing, and the field tooling needed to keep units configurable and usable.
- Industrial analytics dashboard: Built a multi-tenant Next.js analytics dashboard for industrial vehicle event data, with Prisma/PostgreSQL, auth, mapping, and AWS-backed deployment and storage around it.
- Field device configuration tooling: Built a Tkinter/PostgreSQL interface that lets QA set up units, manage tenants and device records, push remote config changes, and selectively enable updates for specific systems in the field.
- CABIN-EYE driver monitoring system: Adapted embedded camera hardware into our own software stack for driver monitoring and integration with the rest of the platform.
Most of these are proprietary work for employers, so public details are necessarily limited. I am happy to discuss these projects in more detail privately, with respect for NDAs and proprietary information.
Education
Bachelor of Science - Computing Science Major, Psychology Minor
University of Alberta (Graduated April 2025)
Relevant coursework: Processor Architecture (RISC-V assembly), Systems Architecture, Operating Systems, Parallel & Distributed Systems, Compilers, Algorithms & Data Structures, Software Engineering, Practical Programming Methodology, Formal Systems & Logic.
Previously completed the majority of an Arts degree in Philosophy at MacEwan University.