Python
Language
AI / ML Engineer
Dominick
Martinez
About
AI/ML engineer with experience in scientific machine learning, distributed computing, computer vision, and research software. My work has included atmospheric simulation, computational immunology, synthetic data generation, and deployable ML systems.
Stack
PyTorch
Machine learning
FastAPI
Backend
Next.js
Web
React
Interface
PostgreSQL
Data
Docker
Infrastructure
Hugging Face
AI ecosystem
Databricks
Data + AI
ROS 2
Robotics
Git
Development
Linux
Systems
Experience
Berkeley Lab
Researcher
Machine learning infrastructure and scientific ML surrogate models for climate science and computational immunology.
- Implemented distributed neural-network training and inference workflows across CPU and GPU HPC environments.
- Developed surrogate modeling pipelines for atmospheric simulations using neural approximations of cloud microphysics.
- Built parallel simulation infrastructure for synthetic T-cell trajectories that reproduced experimental speed distributions within 1%.
Northern New Mexico College
Machine Learning Engineer
Machine learning, data analysis, and numerical simulation projects spanning biology, computer vision, and fluid dynamics.
- Created a scalable data pipeline for large T-cell microscopy datasets used in quantitative modeling and peer-reviewed research.
- Fine-tuned Vision Transformer models with LoRA and quantization for an on-device plant identification application.
- Generated synthetic ML datasets with Navier-Stokes computational fluid dynamics simulations.
Adult Education Instructor, January - August 2022 / Tutor, August 2021 - May 2022
Projects
Autonomous systems / Multi-agent reinforcement learning
StoatSwarm
An AI training and simulation platform for teaching coordinated drone swarms to autonomously explore tunnels and indoor structures.
Designed around tactical reconnaissance, defense, public-safety, and inspection scenarios where autonomous drones can map and assess complex spaces before people enter.
PythonPyTorchPyBulletMuJoCoROS 2PX4Docker
View repository 
Generative AI / Creator operations
Belskap
A web and mobile platform for creating, developing, and managing AI-powered virtual creators across social and subscription platforms.
Combines persistent character identity, agent-driven workflows, content generation, and publishing operations—including mature-audience media—within one production system.
The name joins Old French “belle,” meaning beauty, with Old Norse “skap,” meaning shape.
Next.jsReactFastAPIPythonLangGraphPostgreSQLMCPAI agents
View repository Education
The University of Texas at Austin
Master of Science in Artificial Intelligence
Graduate degree
Northern New Mexico College
Bachelor of Science in Mathematics
Summa Cum Laude
The University of New Mexico
Non-degree Student
Coursework
Certifications
Academy Accreditation - AI Agent Fundamentals
Databricks
Fundamentals of MCP
Hugging Face
Deep Learning
The University of Texas at Austin
Natural Language Processing
The University of Texas at Austin
AI in Healthcare
The University of Texas at Austin
Contact
dominick.n.martinez99@gmail.com