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Cristian Vega

@cristianvega1

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I’m a Senior AI/ML engineer delivering measurable Generative AI and RAG solutions.

United States

Message

What I'm looking for

I’m looking to build production-ready Generative AI (RAG, agents, multimodal) in cloud environments, partnering cross-functionally to improve accuracy, latency, and user experience.

I’m an AI Engineer specializing in Generative AI, Retrieval-Augmented Generation (RAG), and cloud-native deployments. I develop domain-specific AI systems that drive measurable business impact across industries, with hands-on expertise in LangChain, LangGraph, MCP Server, and Azure Cloud.

Most recently at Morf Health, I spearheaded a voice-enabled AI assistant that delivered real-time clinical decision support in active hospital environments. I built RAG systems with FAISS and Weaviate, architected multi-agent workflows with LangGraph and CrewAI, and fine-tuned GPT and LLaMA models using LoRA/QLoRA (PEFT) on proprietary clinical data.

I also lead end-to-end LLMOps and deployment efforts—using MLflow, Weights & Biases, and human-in-the-loop review to support reliability, traceability, and HIPAA-compliant lifecycles. Earlier roles included NLP/semantic enrichment at GumGum and anomaly-detection research at ClearBlade, alongside production Python data engineering at Dell.

Experience

Work history, roles, and key accomplishments

Senior AI Engineer

Morf Health

Sep 2022 - Nov 2025 (3 years 2 months)

Spearheaded a voice-enabled AI assistant and multi-agent RAG platform for clinical decision support, integrating medical guidelines and EHR context for more reliable clinician responses. Built LLM fine-tuning with LoRA/QLoRA, HIPAA-oriented LLMOps, multimodal posture evaluation, and deployed voice-first mobile/web experiences with scalable backend services.

LangGraph Retrieval Augmented Generation (RAG)Weaviate Faiss Model Context Protocol (MCP)

Data Scientist

GumGum

Jan 2021 - Aug 2022 (1 year 7 months)

Developed NLP and semantic enrichment models to extract sentiment, intent, and product attributes for contextual intelligence used in CTV and ad targeting. Built evaluation workflows (offline metrics and A/B tests) and analytics dashboards to monitor semantic tagging performance and impact on engagement and content-to-ad matching accuracy.

NLP Topic modeling Sentiment Analysis Clustering A B Testing Tableau Amazon Quicksight Snowflake Entity Linking

Machine Learning Researcher

ClearBlade

May 2019 - Nov 2020 (1 year 6 months)

Led applied research in anomaly detection and unsupervised learning for fraud, cyber intrusion, and operational risk detection across enterprise systems. Built and benchmarked clustering, autoencoders, Bayesian inference, and graph-based models, then transitioned Python prototypes into production-grade real-time analytics pipelines.

Anomaly Detection Unsupervised Learning Clustering scikit learn TensorFlow Fraud Detection

Python Data Engineer

Dell Technologies

Jun 2017 - May 2019 (1 year 11 months)

Engineered Python-based ETL pipelines for large-scale operational and product telemetry to support Dell’s analytics and AI-driven decision systems. Improved ingestion and storage reliability using PostgreSQL, Hadoop, and AWS S3, and automated data quality checks with NumPy/Pandas/scikit-learn, reducing pipeline failures and inconsistent records by 30%.

ETL PostgreSQL Hadoop AWS S3 NumPy Pandas scikit learn REST APIs Data Quality

Education

Degrees, certifications, and relevant coursework

University of Texas at Austin

Bachelor of Computer Science, Computer Science

2013 - 2017

Activities and societies: Research Assistant; Teaching Assistant; Object Oriented Programming; Department of Computer and Communication System Engineering

Earned a Bachelor of Computer Science from the University of Texas at Austin (2013–2017). Served as a research assistant and teaching assistant in the Department of Computer and Communication System Engineering.