01 — Projects
Selected Work
Projects across AI, VR, and data engineering.
02 — About
Behind
the work
Houston, TX
I got my start building recommendation systems and tuning databases, which turned into a lasting interest in intelligent, data-driven applications. Over the past 3+ years I've worked across AI and data engineering — predictive models, NLP systems, scalable backend services, and real-time analytics platforms.
Toolbox
ReactNext.jsTypescriptNode.jsPythonGoPostgresDockerKubernetesJavaC++MongoDBRedisElasticsearchKafkaSparkAirflow
Journey
ATSER Systems
Database Administrator · May 2026 — Present
- Manage production PostgreSQL and SQL Server databases, covering backups, disaster recovery, schema changes, and user access.
- Tune slow queries and indexes, and added connection pooling and read replicas to handle traffic spikes.
- Built ETL pipelines that prepare business data for AI features, including vector search and LLM-based reporting.
- Set up automated monitoring and alerting for database health and capacity planning.
Handshake AI
Applied AI Research Engineer · Feb 2026 — Present
- Write and refine domain-specific prompts for LLMs used in research workflows, improving response quality and consistency.
- Review model outputs for accuracy, relevance, and adherence to domain guidelines.
- Run structured tests comparing prompt variants and dig into failures to improve model behavior.
- Document prompt patterns and evaluation findings so other researchers can reproduce results.
Future State University
Associate AI Engineer · Nov 2025 — Feb 2026
- Built RAG systems that let transformer models answer questions over the company's business datasets.
- Developed AI agents with contextual memory to automate workflows across departments.
- Deployed models to production with monitoring, validation, and performance tracking.
- Set up experiment pipelines with repeatable, clearly defined evaluation metrics.
Arizona State University
AI Researcher · March 2024 — Sept 2025
- Built a virtual human in Unreal Engine with real-time speech-to-text, text-to-speech, and RAG retrieval so it could hold natural conversations.
- Fine-tuned domain-specific models to improve answer accuracy and cut inference latency.
- Added FAISS vector indexing to speed up semantic search over large knowledge bases.
- Quantized and optimized multimodal models so they could serve responses in real time.
- Built the model-serving layer with request batching to keep latency low under load.
Infosys LTD
Machine Learning Engineer · August 2022 — August 2023
- Developed ML microservices in Python, TensorFlow, and PyTorch for enterprise automation.
- Built models that classify, tag, and route business documents and workflow data.
- Deployed containerized services with Docker on AWS and Azure.
- Added drift detection and performance monitoring for models running in production.
- Worked with engineering and business teams to fold the models into existing applications.
Darwin Box
Data Scientist · March 2022 — Aug 2022
- Built regression and classification models for predictive analytics.
- Cleaned data and engineered features from structured and semi-structured datasets.
- Evaluated models with cross-validation, ROC-AUC, and precision-recall.
- Automated recurring reporting and analytics workflows.