About Me
Doug LaMaster is an AI/ML Engineer with 6+ years of experience developing machine learning solutions for defense and research applications. He specializes in agentic AI workflows, LLM integration, and automated ML pipelines.
At Leidos, Doug leverages GPS technologies to develop both defensive and offensive positioning capabilities while using LLMs to accelerate ISR/modeling development through custom VS Code extensions. Previously at Riverside Research with AFRL (Air Force Research Lab), he reduced computational requirements by 75% using ensemble Convolutional Neural Networks for cryptographic classification. He also led ML development that contributed to an AFRL contract win, designing algorithms for classifying cryptographic processes in microelectronics.
His technical expertise spans:
Agentic AI & LLMs: Model Context Protocol (MCP), LangChain, N8N workflow automation, OpenWebUI Deep Learning: Neural Networks (CNNs), TensorFlow, model explainability MLOps Infrastructure: Docker, Singularity, Portainer with containerized deployment
Active contributor to cutting-edge AI infrastructure including MCP, Doug's passion is using automation and machine learning to help people eliminate tedious workflows. He maintains a TS/SCI security clearance and bases his work on proven results: from processing $1.2B worth of product weekly at Intel as primary contact for lithography fleets, to achieving 35 t/s inference speeds on consumer NVIDIA hardware through custom CUDA pipelines.
Contact Details
Doug LaMaster
(928) 362-0986
doug@douglamaster.com
Education
Northern Arizona University
Master of Science in Mechanical Engineering • May 2024
Completed thesis and published papers on a novel thermodynamic model to predict the response of a magnetic shape memory alloy (MSMA) to magneto-mechanical loading.
Northern Arizona University
B.S. Mechanical Engineering • May 2012
Completed studies in Mechanical Engineering with an emphasis in solid mechanics and heavey extracurricular work in electronics. Researched, characterized, and manufactured structural super capacitors.
Northern Arizona University
B.S. Mathematics • May 2012
Completed studies in Mathematics. Emphasis in applied Mathematics.
Work
Leidos
PNT Engineer • June 2023 - Present
As a Position, Navigation, and Timing Engineer at Leidos, I have been responsible for determining methods to use GPS both defensively and offensively. Automated pipelines to allow for faster experimentation.
Riverside Research
Senior Research Engineer • August 2018 - June 2023
As a senior research engineer, I work to develop the tools to perform the data analysis to evaluate micro-electronics. Assessment involves development of machine learning algorithms for classification and evaluation. Experimented with Convolutional Neural Networks, Data analytics, pre-processing techniques, classification, data pipelines, and statistical models.
PreTalen
PNT Engineer • March 2017 - August 2018
As a Position, Navigation, and Timing engineer, I have become the subject matter expert for inertial systems and sensors at PreTalen.
Intel
Process Engineer • March 2016 - March 2017
As a process engineer and tool-owner in the high-volume manufacture of computer chips, I was responsible for keeping production running at full capacity. Within months, I became the primary point of contact for a fleet of lithography machines processing approximately $1.2B worth of product weekly.
Skills
My education in mechanical engineering and mathematics gave me a broad set of interests and experiences to draw from. The field I am most passionate about right now is AI.
Testimonials
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