Open to opportunities

Adrianh Dao

@adrianhdao

Message

Results-driven ML engineer building scalable, production-grade AI systems and operationalizing ML for business impact.

United States

Message

What I'm looking for

I seek senior ML roles focused on production ML, MLOps, and scalable AI infrastructure where I can build secure, observable, and high-impact systems with fast iteration cycles.

I am a results-driven machine learning engineer with 9+ years building production-grade AI systems across healthcare, fitness, enterprise, and consumer tech. I specialize in fine-tuning LLMs (LLaMA, BERT), architecting Retrieval-Augmented Generation (RAG) and multimodal agentic systems, and operationalizing AI with strong observability, CI/CD, and human-in-the-loop feedback loops.

I have deep expertise in vector databases (PGVector, Pinecone, OpenSearch), cloud-native infrastructure (AWS Lambda, ECS, SageMaker, CDK/Terraform), microservices, and MLOps. My work includes benchmarking and optimizing vector stores, deploying secure, serverless RAG pipelines, building agentic chatbots, and delivering maintainable ML platforms that drive measurable product and business outcomes.

Experience

Work history, roles, and key accomplishments

Current

Senior AI/ML Consultant

Current

Prudentia Sciences

Mar 2025 - Present (10 months)

Evaluated and benchmarked vector databases and built serverless RAG microservices, achieving 150ms query and 200ms indexing times while refactoring Databricks notebooks into production-ready services and implementing CI/CD and IaC.

Vector Databases RAG AWS Lambda DynamoDB AWS CDK Terraform Python LangGraph CI CD

Staff Machine Learning Engineer

eSimplicity

Nov 2023 - Mar 2025 (1 year 4 months)

Fine-tuned LLaMA 3.1 for GraphRAG to generate Cypher queries and built serverless ingestion and retrieval pipelines, achieving improved BLEU/Exact Match metrics and multimodal retrieval with VLMs.

Lang Chain LLaMA PEFT Hugging Face AWS Sagemaker Graph RAG AWS Step Functions LangChain LangGraph Docker

Senior Machine Learning Engineer

iFIT

Apr 2021 - Nov 2023 (2 years 7 months)

Deployed foundational LLMs on SageMaker and built a scalable real-time vector search and microservices architecture, improving search retrieval speeds by over 300% and enabling millions of concurrent AI interactions.

Amazon SageMaker MongoDB Atlas AWS ECS AWS Kinesis Personalize PyTorch fastAPI CI CD

Machine Learning Engineer

Apple

Jul 2019 - Apr 2021 (1 year 9 months)

Designed on-device QA using a fine-tuned BERT exported to Core ML, implemented speech-to-text and TTS pipelines, and optimized models for the ANE to enable privacy-first offline QA experiences.

BERT TensorFlow Core ML Swift AVFoundation

Machine Learning Engineer

DataRobot

Jul 2016 - Jul 2019 (3 years)

Developed ensemble and NLP-driven fraud detection features, improved model accuracy using XGBoost/LGBM and optimized ETL and data pipelines for production deployments.

XGBoost NLP Pyspark Apache Airflow Python SQL

Machine Learning Intern

DataRobot

May 2015 - Jul 2016 (1 year 2 months)

Owned end-to-end ML model lifecycle tasks including data collection, feature engineering, model training and deployment, and produced statistical analyses and visualizations for model evaluation.

Statistical NLP Python SQL Hadoop Tableau Model Evaluation Data Wrangling

Education

Degrees, certifications, and relevant coursework

Arizona State University

Bachelor of Science, Computer Science

2011 - 2015

Completed a Bachelor of Science in Computer Science at Arizona State University, focusing on core computer science principles and applied software engineering.