# Moya Zhu

> Software Engineer @ Nvidia  ♦ ex-Amazon Robotics Data Science intern

Location: San Francisco Bay Area, United States
Profile: https://flows.cv/moya

I am a Software Engineer with strong Machine Learning and Data Science background. At Shoreline.io, I design and implement semantic search solutions for website and remediation runbook catalog using large language models and embedding techniques. 

Prior to joining Shoreline.io, I completed my MS degree in Data Science from Columbia University, where I learned and applied various data analysis, machine learning, and deep learning methods to text, image, audio, and protein structure data. I also gained valuable industry experience as a data science intern at Amazon Global Robotics and UNDP, where I designed and implemented data preprocessing and modeling pipelines using AWS SageMaker. 

I am open for job opportunities in Software Engineer, machine learning engineering, and data analytics in general.

## Work Experience
### Software Engineer @ NVIDIA
Jan 2024 – Present | Santa Clara, California, United States

### Software Engineer @ Shoreline.io (Acquired by NVIDIA)
Jan 2023 – Jan 2024 | Redwood City, California, United States
Semantic Search for website and runbook catalog
• Designed and applied four comprehensive GPT prompt-based test metrics to assess search results and embedding models
• Evaluated embedding models(Ada, Multiqa), chunked and embedded runbooks into FAISS and sqlite databases using langchain
• Established a Git workflow for automated embedding files generation and Docker image creation for deployment
• Implemented a responsive search endpoint for 800 runbooks with associated commands, achieving 500 ms response time
• Developed server-specific custom search index workflow, allowing users to perform searches on their private runbooks using an optimistic concurrency control approach, caching with S3 storage and Redis background workers
• Mentored and supervised two interns through onboarding, collaborating to successfully launch search endpoint on production

End-to-end data pipelines for ticketing tools(Pagerduty, Opsgenie, Servicenow)
• Created and configured multiple Airbyte connectors(TypeScript) and data streaming scripts for data extraction, transformation, daily synchronization, and loading into PostgreSQL, providing user with near-instance data access
• Unified diverse data sources schema and migrated 14000 tables using Flask and SQLAlchemy, optimizing codebase clarity • Implemented interactive UI data visualization reports(React.js), transforming backend SQL queries into filter-enabled graphs • Enabled runbook generation utilizing GPT-3.5 and prompt techniques to auto-create Generative AI incident remediation

### Data Science Intern @ Amazon Global Robotics
Jan 2022 – Jan 2022
•	Designed and implemented data preprocessing and modeling pipeline using AWS SageMaker for dynamically chute mapping update on sortation floor to replace expensive runtime simulator 
•	Embedded high dimensional destination distribution data with station spatial location into multi-channel tensors and scatter images with aggregation to extract floor information, built surrogate models with Multi-layer Perceptron that improved 28.8% MAE and 0.527 R2 from Baseline to predict package throughput evaluation metrics
•	Compared approaches performance with PCA reduced Linear Regression, MLP, CNN and pretrained networks, interpreted features measures floor congestion, and developed recommendations for further modeling improvement

### Data Visualization Scientist Intern @ UNDP
Jan 2022 – Jan 2022
Analyzed the website data impact and visualized into dashboard by using web scrapping and Google Analytic tools

### FairVision researcher @ Purdue University CAM2
Jan 2020 – Jan 2022
Co-lead of the FairVision Cam2 subteam. Utilizing Generative Adversarial Network(GAN) to remove image dataset biases in the training data of image recognition and classification algorithms.

### S.O.S challenge participant @ TechPoint
Jan 2020 – Jan 2020
- Developed a one-stop-shop COVID-19 web-app that providing COVID forecasts, News, State Policies, and Realtime safe place to travel with the team
- Prototyping and design the UI of the app
- Implementing all features into the app and ensure interactive and smooth transition
- Creating Policy checker feature by collecting states social distancing policy and visualizing into interactive geomap

### Computational Biomolecular & Mesoscopic Physics Group-Research Assistant @ Purdue University
Jan 2020 – Jan 2020
• Analyzing and superimposing protein structures with Python Bio.PDB and calculating RMSD between structures
• Manipulating, scratching, and visualizing protein residue sequence using software including Pymol, Chimera and Discovery Studio


## Education
### Master of Science - MS in Data Science
Columbia University
Jan 2021 – Jan 2022

### Bachelor of Science - BS in Applied Statistics and Data Science
Purdue University
Jan 2017 – Jan 2021


## Contact & Social
- LinkedIn: https://linkedin.com/in/moya-zhu-b93283173

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Source: https://flows.cv/moya
JSON Resume: https://flows.cv/moya/resume.json
Last updated: 2026-03-22