Wei-Hsien (Rachel) Wang — Machine Learning Engineer (LLM Systems & MLOps)

Professional Experience

Forward Deployed Engineer

Stealth Startup, San Jose, CA Feb 2026 – Aug 2026

Built and deployed full-stack AI enterprise applications for 6+ customers, owning architecture, implementation, testing, and production rollout across LLM workflows, Python, APIs, cloud infrastructure, and JavaScript frontend frameworks
Conducted 20+ architecture and code reviews across customer applications, identifying performance, reliability, and scalability improvements while establishing engineering best practices
Delivered 15+ technical deep-dives and architecture reviews, authored deployment documentation, and reduced customer onboarding time by 40% through reusable implementation patterns

LLM Workflows Python APIs Cloud Infrastructure JavaScript System Architecture

Machine Learning Engineer

Tatung Company, Taipei, Taiwan Jul 2025 – Sep 2025

Developed a production chatbot platform in Node.js/TypeScript with Redis caching and Azure infrastructure, reducing latency by 45% and lowering compute costs by 50%
Fine-tuned a PyTorch transformer classifier achieving 89% intent accuracy, using confidence thresholds to automate 70% of support requests while reducing unnecessary escalations by 35%
Designed a RAG architecture using OpenAI embeddings, FAISS, and REST services, improving retrieval relevance and increasing CSAT by 8 percentage points

Node.js TypeScript Redis Azure PyTorch OpenAI FAISS RAG

AI Engineer

Praxis Solutions, San Diego, CA Mar 2025 – Jun 2025

Engineered an AI extraction pipeline with LangGraph and OpenAI, processing 500K+ emails and achieving 87% precision through human-in-the-loop validation
Developed a GraphRAG chatbot using FAISS, Neo4j, and OpenAI, reducing task discovery time by 65% through graph-based retrieval and relationship analysis
Delivered a Streamlit executive dashboard with workflow scheduling integrations, coordinating cross-functional stakeholders and reducing project delays by 40%

LangGraph OpenAI GraphRAG FAISS Neo4j Streamlit

Research Assistant

Soochow University, Taipei, Taiwan Oct 2023 – Mar 2024

Developed PAD (Prediction And Decision) methodology bridging ML predictions with business strategy implementation
Presented at the 2024 International Conference on Big Data and Enterprise Resource Management
Demonstrated automated marketing strategies and ROI improvement through targeted customer segmentation

R Machine Learning RFM Analysis Public Presentation

Data Analyst Intern

Virbac, Taipei, Taiwan Sep 2023 – Dec 2023

Built SQL ETL pipelines populating a centralized analytics data warehouse from 18 branches for executive ad-hoc reporting
Designed Tableau dashboards illustrating profitability and OPEX/CAPEX trends, enabling ~10% cost optimization
Streamlined reporting workflows with Excel, reducing manual processing time by 32%

SQL Tableau Excel Financial Analysis

Teaching Assistant

Soochow University, Taipei, Taiwan Sep 2022 – Jan 2023

Teaching Assistant for Applications of Data Science course
Led sentiment analysis and text mining projects in R on visitor reviews for the museums in Taiwan
Supported students in data analysis while fostering an inclusive learning environment

R Text Mining Sentiment Analysis

Data Scientist Intern

Growth Strategy, Taipei, Taiwan Jun 2022 – Aug 2022

Analyzed eCommerce history data in R for a cosmetics store (120K+ customers) to identify retention and churn
Applied K-Means clustering and a rule-based New-Exist-Sleep segmentation to classify customer life stages and engagement
Built Logistic Regression (85% accuracy, AUC = 0.88) and Linear Regression (R² = 0.713) models to estimate CLV, and simulated marketing ROI through A/B testing of campaign cost vs uplift in purchase probability

R K-Means Clustering Logistic Regression A/B Testing Predictive Modeling Customer Segmentation

AI Agents

🔧

Eric's Auto Care — AI Assistant

Small Business AI Agent

Conversational AI assistant for a local auto repair shop using Groq (LLaMA) tool use. Answers service questions, books appointments, and handles inquiries in any language via a stateless Python serverless backend with Supabase persistence.

                                    
                                    LLM-driven tool use — agent collects info over multiple turns then calls
                                        book_appointment or submit_inquiry

Mobile-first React + Tailwind chat UI with analytics dashboard

LLaMA React Supabase Vercel Serverless Python

🎙️

Live Suggestion Agent

Real-Time AI Meeting Copilot

Listens to live mic audio and continuously surfaces 3 AI-powered suggestions based on conversation context. Built with Groq Whisper + GPT-OSS on Next.js 16 with streaming chat responses.

                                    
                                    Real-time transcription via Groq Whisper with context-aware suggestion
                                        classification (QUESTION_ASKED, CLAIM_MADE, TOPIC_SHIFT)

                                    
                                    Two-layer deduplication: prompt-level avoidance + Jaccard word-overlap
                                        filtering

Next.js 16 Groq Whisper GPT-OSS Streaming API Vercel

🎧

Muse.AI: The Agentic Music Curator

Gemini 3 Hackathon, Google DeepMind

Agentic music curation system using Gemini 3 Flash + LangGraph. Multi-agent workflow (Vision, Search, Curator) analyzes photos for mood and curates personalized playlists with a Critic agent for quality control and Firestore-backed long-term memory.

                                    
                                    Multi-agent orchestration with LangGraph — Vision, Search, Curator, and Critic
                                        agents

Firestore long-term memory learns user preferences over time

Gemini LangGraph Spotify API Next.js Google Cloud Run

🌍

AI Recruitment Hub

Deep Learning & GenAI for Business

Full-stack AI recruitment system automating the hiring lifecycle from resume parsing to offer letter generation using LLaMA + Gemini APIs.

                                    
                                    Automated resume parsing, Calendly scheduling, and dynamic PDF offer
                                        generation

Containerized deployment with Python Shiny frontend

Team: Ryosuke Aoguchi, Nicole Ou, Wei-Hsien (Rachel) Wang

LLaMA Gemini API Python Shiny Docker

📧

Email Intelligence System

Email Intelligence System @ Praxis Solutions

Neuro-symbolic AI that transforms enterprise emails into a queryable knowledge graph using LangGraph, Neo4j, and Gemini with GraphRAG retrieval and human-in-the-loop validation.

                                    
                                    GraphRAG architecture — Neo4j knowledge graph + FAISS vector search with natural
                                        language Cypher queries

LangGraph ETL pipeline with human-in-the-loop validation

LangGraph GraphRAG Neo4j Gemini GCP

🍽️

Recipe Recommendation System

Web Mining & Recommender Systems

Recommendation system combining collaborative filtering (SVD) and content-based filtering (TF-IDF). Achieved 79% accuracy on multi-cuisine prediction.

Collaborative filtering with SVD + content-based filtering with TF-IDF

Multi-cuisine classification with XGBoost

Team: Darren Trieu, Wei-Hsien (Rachel) Wang, Akshay Ghosh, Mathew Luo

Collaborative Filtering SVD TF-IDF XGBoost

Modeling & Experiments

📂

Customer Analytics Cases

Customer Analytics

Comprehensive business analytics covering predictive modeling, A/B testing, and profit optimization across real-world customer scenarios.

Tuango: Mobile app message targeting with logistic regression

TZ Gaming: Optimal mobile ad targeting with ROME analysis

Intuit: QuickBooks upgrade prediction using neural networks

Creative Gaming: Propensity-to-buy & uplift modeling

Pentathlon: Next product recommendation system

S-Mobile: Customer churn prediction and retention strategy

FiTech: Customer adoption and value forecasting

Team: Ryosuke Aoguchi, Wei-Hsien (Rachel) Wang, Jaqueline Vallejo, Qiyong Zhang

Logistic Regression XGBoost Neural Networks Random Forest A/B Testing Uplift Modeling

🎼

Generative AI & Audio Processing

Machine Learning for Music

Complete progression through modern music AI, from audio signal processing to symbolic and generative modeling using state-of-the-art techniques.

MAESTRO 2018 dataset for piano performances

Markov chains + LSTM for melody generation

REMI tokenization & Transformer decoder

Diffusion models for audio generation

Task 1: Unconditioned Symbolic Generation

Separate harmony and melody generation using Markov chains and LSTM
Temporal and harmonic alignment evaluation

Task 2: Conditioned Symbolic Generation

Multi-instrument music with REMI tokenization
Structured generation with intro, climax, and resolution
Expressive decoding with MLP regressors

LSTM Transformer Markov Chains REMI Diffusion Models Audio Processing

🎆

NLP & Deep Learning

Analyzing Unstructured Data

Comprehensive exploration of NLP and deep learning for unstructured data, covering traditional text classification, embeddings, and prototype-based learning.

Sentiment Classification: TF-IDF + logistic regression on Financial Phrase Bank

Word Embeddings: Word2Vec vs. GloVe comparison and n-gram modeling

Phrase Mining: AutoPhrase on CS papers with domain-specific embeddings

Restaurant Classification: Multi-class classification with 81% F1 score

Image Prototyping: MNIST classification via K-Means + KNN vs CNNs

Final Project Team: Ryosuke Aoguchi, Nicole Ou, Wei-Hsien (Rachel) Wang

TF-IDF Word2Vec GloVe AutoPhrase CNN K-Means

Data & Cloud Engineering

🔁

AWS Cloud Analytics

Scalable Analytics

Comprehensive cloud-based analytics using PySpark, AWS EMR, and SageMaker. Projects include large-scale text processing, airline delay analysis, and salary prediction.

AWS EMR for distributed computing

SageMaker for ML deployment

Performance benchmarking

Production-level workflows

PySpark AWS EMR SageMaker XGBoost Distributed Computing

⚡

Distributed Systems Engine with Ray

Scalable Data Systems

Built production-grade distributed data processing systems using Ray for parallel computing and GPT for intelligent data transformation.

                                    
                                    Built ETL pipeline with Ray Data API and
                                        GPT to process 100K+ Amazon reviews via
                                        streaming execution
                                

                                    
                                    Implemented MapReduce to distribute word-count processing
                                        across eight parallel workers, validating 2.8K+ unique
                                        terms
                                

                                    
                                    Engineered and benchmarked three AllReduce algorithms
                                        (recursive-doubling BDE, binary-tree MST, Ray builtin) using
                                        PyTorch tensors, profiling 257 MB/s bandwidth
                                        with <1% variance
                                

Course: Scalable Data Systems, Halıcıoğlu Data Science Institute

Ray MapReduce AllReduce PyTorch GPT Distributed Computing ETL

📦

Cloud Data Warehouse with Snowflake

SQL & ETL

Advanced SQL and ETL workflows across PostgreSQL and Snowflake. Integrated multi-format datasets with automated ingestion and materialized views for business intelligence.

PostgreSQL & Snowflake integration

Recursive CTEs & fuzzy matching

Cloud-based materialized views

BI pipeline design

Final Project: Automated ingestion of CSV, XML, PostgreSQL, and Marketplace APIs into Snowflake using Python. Computed PO amounts, invoice discrepancies, and joined purchasing and weather data for analytics on price variance under different temperature conditions.

Team: Yangqi Huang, Wei-Hsien (Rachel) Wang, Zewei Chen, Guoxuan Li

PostgreSQL Snowflake Python ETL SQL Data Pipelines

Education

🎓

Master of Science in Business Analytics

Rady School of Management, UC San Diego

Aug 2024 - Dec 2025

Relevant Courses:

Customer Analytics Scalable Data Systems SQL & ETL Web Mining & Recommender Systems Deep Learning & GenAI Machine Learning for Music Analyzing Unstructured Data

🏛️

Bachelor of Business Administration, International Business

Soochow University, Taipei, Taiwan

Sep 2020 - Jun 2024

Certificates & Achievements

AWS Certified Cloud Practitioner

Amazon Web Services

Introducing Generative AI with AWS

Amazon Web Services

Microsoft Azure AI Engineer Associate (AI-102)

Microsoft

SAS Cortex Participant

SAS Institute

IBM Deep Learning Essentials

IBM

Conference Presentation

2024 International Conference on Big Data and Enterprise Resource Management