- davidgraymi@gmail.com
- davidmgray.com
- Saint Louis, Missouri
- Resume
- GitHub
I am a highly driven Software Engineer and AI Specialist with 4+ years of professional experience in developing secure, high-performance, and real-time solutions across embedded systems and cloud platforms. Currently contributing deep expertise in C/C++, Go, and Linux to mission-critical systems at Boeing, where I have led efforts in platform portability, low-level kernel development, and anti-tamper security. My technical foundation is strengthened by advanced knowledge in AI/ML (TensorFlow, PyTorch), demonstrated through portfolio projects like a 98.8% accurate Sign Language Translator, and a strong background in full-stack development using Go, Vue, and AWS. I am pursuing a Master's degree in Computer Science at the University of Illinois Urbana-Champaign to further my specialization in cutting-edge computer science and engineering.
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Work Experience
Software Engineer
My tenure at Boeing has been defined by diving deep into the entire stack of real-time embedded software for our weapon systems and using all of my extra brain power to develop empathetic DevSecOps solutions for myself and my team. Being introduced to low-level programming early in my career has given me a deep understanding of the "magic" that I used to think was part of all great applications.
- Secured multi-million dollar military contracts for Boeing's weapon product lines
- Developed a go https server to streamline integration testing, reducing testing time by 10X
- Created a portable system library for any RTOS or bare metal systems using C++, Docker, Bazel, and GitLab, reducing engineering hours by 4X.
- Engineered a processor from the ground up (kernels, task scheduler, communication protocol, etc), using C and Ada. Now in production for global distribution
- Led reverse engineering efforts for critical cross-program missile interfacing application, improving real-time telemetry decoding and control functionalities, using C#, WPF, and XAML
- Conducted integration tests and data analysis for computer vision enhancements and requirements verification using Python, a simulation environment, and an experimental aircraft (I actually got to fly!)
- Optimized Jenkins and GitLab DevOps pipelines for efficiency gains using Python, Batch, and shell
- Support autonomous vehicle functions by retrieving and processing data from sensors like GPS, using Ada and C++
- Modernized security measures by adding warnings to an in-house Ada static code analysis app, using C++
Web Developer
As the web developer for the Computational Learning Systems Lab my job is to update the university webpages using the webpress software.
- Update the Computational Learning Systems Lab website with current information
- Validate local linking to important research papers and projects
- Maintain consistent format throughout the website during seasonal changes
Computer Lab Assistant
As a computer lab assistant at Missouri State University I help students and faculty on campus with any computer related issues. This normally consists of downloading and installing software, guiding software use, or troubleshooting connection issues. This experience has exposed me to a variety of softwares and computer issues giving me a well rounded understanding of personal computers, networks, applications, and general technology usage.
- Resolve university network issues on personal and university computers and lab equipment
- Communicate information to peers, work as a team to solve problems, and create documentation for issues
Quality Assurance Analyst
During my time at O’Reilly Autoparts I was tasked with daily challenges involving testing software and optimizing test workflow. Testing involved detailed documentation on Jira and Confluence. Optimizating the testing workflow consisted of writing SQL queries based on prexisting queries from an old database.
- Optimized SQL queries for quick, accurate results
- Reviewed, tested, and approved test cases on production level software
- Wrote detailed documents on bugs found when testing
Research Assistant
My main responsibilities in the lab included writing python programs for preprocessing high volumes of data to fit the algorithms under study, running the data through the algorithms, and recording results in a readable format using libraries like matplotlib, pandas, and scikitlearn. I presented my results to the professor and graduate students I worked under at the end of the month.
- Increased efficiency in a high paced work environment by developing data pipelines
- Assisted a published work on the effects of the TSNE algorithm on Traumatic Brain Injury data
- Ran algorithms on large datasets and analyzed the results
Projects
GitHub for everyone who doesn't use GitHub! Painless all-in-one document management service, document review lifecycle, team collaboration, search, and in browser editor. This solo side project, first started for my wife who complains about her works policy management platform, does not get the love it deserves from me. My hope is one day I hire some interns to do sales and clean up the list of backlog items I may never get to while I am in grad school.
This is a school project to create a NLP pipeline for a patient care portal. User queries are triaged to the correct team (insurance, scheduling, medical advice, etc.) and information retrieval is performed so patients can read relevant evidence based research while waiting for a professionals advice. I created the classifier using pytorch that uses the output from Google's latest Embedding Gemma 300m model to classify sentence embeddings.
In this project myself and four other seniors in the Computer Science program at MSU created a system that allows a user to control any smart technology (like a lightbulb) with American Sign Language by signing in front of a camera. Our system contains 3 modules, hand/landmark tracking, gesture classification, and grammer correction, and utilizes a client-server connection to prove that this software can be implemented and accessed by any smart device with a camera. The biggest task I dealt with was building, training, and testing the gesture classifier. For this task I built a convolutional neural network that classifies 14 hand gestures with 98.8% accuracy. For the source code, live demonstrations, papers, and more check out my github.
Handwriting Digit Recognizer Using KNN Algorithm with Weighted Voting and K-value Optimizer
I built software that uses the KNN algorithm to predict a handwirtten digit [0-9] from a grid of 784 pixels where each Each pixel contains an integer value between 0 and 255, inclusive and is arranged in a twenty-eight by twenty-eight array forming an image of the drawn digit. I went further and built a function that optimizes the k-value and reduces the number of times the KNN algorithm calculates distances for each unclassified object to one instance. Download my research report to read more.
ID3 Mushroom Classification: Edible vs. Poisonous
In this project a colleague and I created an ID3 algorithm that takes in mushroom attributes and outputs whether the mushroom is edible or poisonous. Download my research report to read more.
This was a fun project I did in school with the help from another classmate. Download the code here or see more on my github.
Healthcare Length of Stay Estimator
This project was for my data mining class. Download the code here or see more on my github.