Summary
Machine Learning Engineer with experience taking ambiguous 0-to-1 AI systems from dataset and modeling design through evaluation, deployment, monitoring, APIs, infrastructure, and user-facing workflows. Hands-on depth in LLM agents and retrieval systems, physics simulation, Bayesian optimization, computer vision, and production Python/C++ services, with a focus on measurable decisions, uncertainty, and verification. Ph.D. in Mechanical Engineering. U.S. citizen.
Professional Experience
Machine Learning Engineer III, Agentic AI Systems
Blue Origin, Renton, WA · 06/2025 - Present
- Applied AI and machine learning systems. Details available on request.
Senior Machine Learning Software Engineer, Simulation AI Systems
Dyno Nobel, Salt Lake City, UT · 04/2024 - 06/2025
- Led a 4-person team productionizing a cloud-native simulation and optimization platform around patent-pending C++ physics models (AWS Fargate, API Gateway, ALB, CI/CD).
- Designed a tool-using multi-agent system that invoked simulation services, evaluated candidate blast plans, and generated recommendations under domain constraints.
- Created the company's first RAG platform from ingestion and indexing through prompt tuning, evaluation, API serving, and rollout.
Machine Learning Engineer II, Industrial AI Systems
T.D. Williamson, Salt Lake City, UT · 10/2022 - 04/2024
- Built a distributed predictive-maintenance system from sensor ingestion and LSTM training through C++ edge deployment, validation, and monitoring, helping prevent failures worth up to $500,000 per rerun.
- Built a real-time corrosion-detection workflow (FPN with ResNeXt-50 encoder) from dataset preparation through on-prem serving, with an ICMLA 2023 publication.
Data / Software Engineer
Iran Host · 03/2012 - 12/2015
- Modeled seasonal customer behavior from sales data with frequency analysis and autoregressive methods for targeted marketing decisions.
- Implemented real-time C++ data-compaction services for scalable analytics pipelines.
Research Experience
Postdoctoral AI Materials Discovery Researcher
Texas A&M University, College Station, TX · 12/2021 - 08/2022
- Built a three-model surrogate and Bayesian-optimization workflow for closed-loop materials discovery, from simulation-data curation through acquisition-driven candidate selection and experiment planning, for a $1.7M AI integration project.
Computational Materials ML Scientist Intern
Tokyo Electron US, Austin, TX · 06/2021 - 12/2021
- Developed atomistic-simulation workflows (Quantum ESPRESSO, VASP) and automated Phonopy and AMSET post-processing into ML-ready datasets and decision-ready model inputs.
Graduate Computational Materials ML Research Assistant
Utah State University, Logan, UT · 08/2016 - 06/2021
- Ran large-scale LAMMPS molecular-dynamics campaigns and processed more than 2 TB of simulation data with parallel Python pipelines.
- Applied Monte Carlo simulation, uncertainty analysis, and optimization to quantify materials-model risk; improved HPC workflows with multiprocessing and automated analysis.
Education
Ph.D., Mechanical Engineering
Utah State University · 12/2021
10+ peer-reviewed publications
B.Sc., Mechanical Engineering
Sharif University of Technology · 02/2012
Core Skills
ML & Experimentation: LLM/RAG and Graph-RAG, agentic systems, VLMs, prompt/model tuning, Bayesian optimization, surrogate modeling, uncertainty analysis, Monte Carlo simulation, benchmark evaluation
Engineering: Python, C++, SQL, GraphQL, React, FastAPI, APIs, data pipelines, distributed/edge systems
Production & Platform: AWS, Docker, Kubernetes, Terraform, CI/CD, observability, monitoring, HPC job orchestration
Scientific Computing: DFT (VASP, Quantum ESPRESSO), MD (LAMMPS), Phonopy, AMSET
Quick Information
Education
Ph.D. in Mechanical Engineering
Utah State University
Current Role
Machine Learning Engineer III
Agentic AI Systems, Blue Origin
Location
Bellevue, WA
United States
Expertise
LLM Agents & Evaluation
Simulation-Driven AI
Production ML