MATTHEW WNUK  E.I.T.                                                                                                     [email protected]                                                                                                                                
CERTIFICATES AND PATIENTS
NVIDIA-Certified: Generative AI Multimodal                                                                                                                                                                            December 2024
NVIDIA-Certified: Generative AI LLMs                                                                                                                                                                                        December 2024
Visual Speech Recognition from CTC Loss                                                                                                                                                                         US2023/0106951 AI
NLP Lip Reading Prediction Correction                                                                                                                                                020699-119300US/SYP340532US02
             
EDUCATION AND HONORS
MSEE - University of California San Diego
BSEE - San Diego State University
Eta Kappa Nu (HKN) electrical engineering scholastic honor society – President 
Tau Beta Pi (TBP) interdisciplinary engineering honor society 
                                                                                                      
WORK HISTORY
Senior Software Engineer (ML / Perception) – Symbotic                                                                                                                                        January 2023 - Present
  • Tech Lead: CaseID
    • Project development for large scale production system from ideation, through literature review, model development and experimentation, through production deployment and monitoring.
    • Image embedding with Vision Transformers (ViT)
    • Model training and development on Azure and GCP
    • Containerization, memory management, and deployment of onnx model in resource limited embedded ROS environment on NVIDIA Jetson
    • Design and development of deep learning pipeline using technologies such as OpenCV, PyTorch, pandas

Senior Machine Learning Engineer – Modern Intelligence
  • Development of custom multi-modal retrieval system for maritime awareness
  • Implemental scalable system for dataset versioning, model versioning, experiment tracking, and production monitoring to mitigate the reproducibility problem
  • Developed standard of system performance metrics for maritime reidentification 

Staff Machine Learning Engineer – Sony Electronics                                                                                                                                       February 2020 to Aug 2022
  • Senior MLE: Machine Learning for Retail
    • Customization of YoloV5 architecture for embedded product recognition
    • Quantization and deployment of tflite on embedded camera
  • Tech Lead: Visual Speech Recognition
    • Design and development of deep learning sequence to sequence pipeline for
    • VSR using technologies such as OpenCV, Pytorch, Tensorflow, pandas, sci-kit learn
    • NLP for language understanding
    • Design of custom spatiotemporal CNN (3D) architectures in TensorFlow 2
    • Large-scale in-house data curation and preprocessing chain development 100+ terabytes of data managed with Postgres SQL 

Machine Learning Engineer – SPAWAR                                                                                                                                                        January 2016 to February 2020
  • Tech Lead: Machine Learning for Self Defense
    • Random forest classifier using RF parametrics
    • Data cleaning and relational data base design (MySQL)
  • Lead MLE: Radio Frequency Machine Learning Systems
    • Variational Autoencoders for HW fingerprinting and anomaly detection
    • DB-Scan (density-based clustering) in latent space
    • Manifold learning (t-sne embedding) for visualization of latent space
    • Large scale data curation for DARPA’s RFML competition
    • Use of GAN for adversarial machine learning (early Generative AI)
    • Sci-kit Learn (sklearn) - random forest classifier using RF parametrics
    • Data cleaning and relational data base design (MySQL)
  • Trainer – Machine Learning
    • Topics include deep learning, linear regression, logistic regression, Naïve Bayes, Principal Component Analysis (PCA), unsupervised Learning, gradient descent, normalization techniques, Boosting and Bagging (ensemble methods), objective functions, and data augmentation 

Center of Interdisciplinary Science – UCSD Research Lab                                                                                                                               January 2018 to June 2018
  • Python Software development for Intel Aero Embedded Linux Environment
  • SLAM – lidar based, occupancy grid.
  • Particle filter for state estimation
  • low level peripherals such as IMU & Magnetometer via SPI and I2C
  • 9DOF Sensor Fusion for quaternion orientation via Madgwich Filter

Intern – NASA Langley Research Center                                                                                                                                                                   May 2015 to August 2015
  • Redesign of optical receiver for advanced lidar system
  • Circuit design using RF design principals
  • PCB Layout in Altium Design Suite
​
AUVSI Robosub Competition                                                                                                                                                                               June 2014 to December 2015
  • First Place Team 2015 AUVSI International robotic submarine competition
  • Designed and Built Custom Sonar System for Signal Localization and navigation
  • Analog signal conditioning
  • Coded 16-bit DSP for direction of arrival algorithm in embedded C

RF Engineer Intern – Northrop Grumman                                                                                                                                                            June 2014 to January 2015
  • Software Development for Automation
  • Macros for HFSS written in python
  • Matlab scripting for development of database tools 

Military Analyst – Office of Naval Intelligence                                                                                                                                           July 2010 to August 2013
  • Digital signal processing and timely analysis of acoustic signal for the intelligence community
  • Analysis of acoustic signatures for operational and tactical significance
  • Development of detection, classification and target motion analysis techniques and tools



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