I'm Holland Hargens, a computer engineering grad who never picked a layer — FPGA bring-up and bare-metal firmware on one end, ML pipelines and LLM-backed services on the other.
Currently building embedded systems.
Integrated the DPUCZDX8G IP in Vivado on an AUP-ZU3 (ZynqMP) board targeting pynq-dpu inference.
Read the details →
Contract, remote. Feature work across Radius Hire, Radius Find, and Compañero. Gemini-integrated candidate screening workflow, FastAPI services containerized on AWS, LLM output evaluation, data prototyping.
Built the preprocessing pipeline for 23-channel time-series sensor data, then trained PyTorch and TensorFlow regression and classification models against it — ~7% RMSE across 20+ tracked MLflow configurations.
3.6 GPA, Dean's Honor List. ECE 554 capstone with the Flex-PGA group, building a fitness tracker. IEEE member.
I studied computer engineering because I didn't want to choose between the hardware and the software. My favorite work happens where the abstraction leaks — a DPU that won't meet timing, a model that has to fit the resources you actually have, a service that has to stay up while you rewrite it.
Right now I'm looking for a new grad role in embedded, ML, or backend engineering — somewhere I can own something end to end and read a lot of other people's code.
Outside of that: golf, and a dog named Beau who is thoroughly unimpressed by all of this.
Recruiters, engineers, and people with a weird hardware problem all welcome. I reply within a day.