Senior AI/ML Engineer Data Scientist AI Researcher

Owen Bailey

Senior Artificial Intelligence Engineer ML Engineer Data Engineer

320-***-**** ****.******.**@*****.*** College Station, TX LinkedIn PROFESSIONAL SUMMARY

Senior AI/ML Engineer with 9+ years of experience delivering production-grade AI solutions across the full lifecycle—from R&D to large-scale MLOps. Expert in architecting Agentic Workflows, RAG pipelines, and LLM orchestration using Python, LangGraph, and PyTorch. Proven track record of leading cross-functional teams to integrate custom AI into enterprise legacy systems, resulting in millions of dollars in operational savings. Committed to building secure, scalable, and cost-optimized AI ecosystems that bridge the gap between cutting-edge research and measurable business ROI. TECHNICAL SKILLS

● Generative AI & LLMs: Agentic Orchestration (LangGraph, AutoGen), RAG Architectures, Multi-modal Models, Fine-tuning (PEFT, QLoRA), Prompt Engineering, AI Safety/Red-Teaming.

● Machine Learning Engineering: PyTorch, TensorFlow, Scikit-learn, Deep Learning, Computer Vision, Model Quantization (TensorRT), Evaluation Metrics (ROUGE, BLEU).

● Python & Software Architecture: Expert Python (Asyncio, Pydantic, Ruff), FastAPI, RESTful APIs, Distributed Systems (Ray), Microservices, Design Patterns.

● MLOps & Cloud Infrastructure: AWS (Bedrock, SageMaker), GCP (Vertex AI), Docker, Kubernetes, CI/CD for ML, MLflow, Weights & Biases, Arize AI (Observability).

● Data & Vector Systems: Vector Databases (Pinecone, Milvus, Weaviate), SQL (PostgreSQL), NoSQL

(MongoDB, Redis), Apache Spark, Data Ingestion Pipelines (ETL).

● Cloud & Data: AWS (Bedrock, SageMaker), GCP, Vector Databases (Pinecone, Milvus), SQL, Spark.

● Leadership: AI Governance & Safety, Team Mentoring, System Architecture, ROI-driven AI Strategy. PROFESSIONAL EXPERIENCE

Intelagen Saint Petersburg, FL Nov 2023 - Jan 2026 Senior AI/ML Engineer & GenAI Engineer Remote

● Engineered a multi-agent orchestration system using AutoGen and LangGraph, allowing autonomous AI agents to execute complex, multi-step business workflows with 90% task completion accuracy.

● Developed and enforced a comprehensive AI Governance and Safety framework, implementing automated red-teaming and PII-masking layers to ensure enterprise-grade security for LLM deployments.

● Pioneered the use of Parameter-Efficient Fine-Tuning (PEFT) and QLoRA to adapt open-source models (Llama 3/Mistral) for niche industry domains, outperforming GPT-4 baseline metrics by 12% on specialized tasks.

● Built a real-time AI observability dashboard using Weights & Biases and Arize AI to monitor model drift and latency, maintaining sub-200ms inference times across global production environments.

● Championed the adoption of Serverless AI Inference using AWS Bedrock and Lambda, reducing infrastructure overhead costs by 50% while improving auto-scaling capabilities.

● Mentored a cross-functional team of 12 engineers and data scientists, establishing the internal "AI Center of Excellence" to standardize Python coding standards and model evaluation protocols.

● Integrated custom AI solutions into existing legacy ERP systems via robust API architectures, resulting in an estimated $2.5M in annual operational savings through automated data processing and decision-making.

3ALICA Glendora, CA Mar 2021 - Oct 2023

Senior AI Engineer & LLM Specialist Remote

● Spearheaded the integration of Large Language Models (LLMs) into core product offerings, utilizing Hugging Face Transformers and LangChain to automate complex document summarization for enterprise clients.

● Architected a Retrieval-Augmented Generation (RAG) pipeline using Pinecone vector databases, decreasing hallucination rates in AI-generated responses by 35%.

● Directed the transition from monolithic model deployments to a distributed Ray Serve architecture on Google Cloud Platform (GCP), enhancing system scalability to support 50k+ concurrent API requests.

● Established a comprehensive MLOps framework using MLflow for experiment tracking and model versioning, reducing the deployment cycle from weeks to days.

● Led technical cross-functional workshops to align AI capabilities with business KPIs, resulting in the successful launch of two new AI-driven revenue streams.

● Optimized model inference performance by implementing quantization and pruning techniques

(TensorRT), reducing GPU compute costs by 40% without compromising predictive accuracy. Inventive Austin, TX May 2018 – Feb 2021

Machine Learning Engineer(GNN Specialist) Hybrid

● Designed and implemented an end-to-end recommendation engine using PyTorch and Flask, resulting in a 15% increase in user engagement for a flagship e-commerce client.

● Engineered scalable data pipelines using Apache Spark and Python to process multi-terabyte datasets, reducing model training time by 40%.

● Architected and deployed containerized ML microservices using Docker and AWS SageMaker, streamlining the transition from research to production.

● Automated model evaluation and hyperparameter tuning workflows, improving model precision by 12% across three different client projects.

● Mentored junior developers on Python best practices and asynchronous programming (Asyncio), increasing the engineering team's sprint velocity by 10%. Ighty Support Carrollton, Texas Sep 2016 – Apr 2018 Junior AI/ML Developer & Data Scientist On-site

● Developed Python-based automation scripts to streamline internal ticket classification, reducing manual triage time by 30%.

● Built and deployed a supervised machine learning model using Scikit-learn to predict hardware failure patterns, improving proactive maintenance by 20%.

● Optimized data ingestion pipelines by migrating legacy shell scripts to robust Python ETL workflows, ensuring 95% data consistency.

● Collaborated with senior engineers to implement NLP techniques for sentiment analysis on customer feedback to drive service improvements.

EDUCATION

Texas Tech University Lubbock, TX

Master of Science in Computer Science 2018

● Specialization: Artificial Intelligence & Machine Learning

● Research: High-performance computing and data-intensive applications at the Data-Intensive Scalable Computing Laboratory (DISCL).

Bachelor of Science in Computer Science 2016

● Honors: Magna Cum Laude (Top 10% of class)

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