# Andrew Tseng

> 7 years of AI engineer experience wiring up DBs, pipelines, and serving infra for AI products.

Location: Bellevue, Washington, United States
Profile: https://flows.cv/andrewtseng

I wire up DBs, pipelines, and serving infra so AI products actually scale, and keep latency low and costs sane while the product team promises “instant answers”.

## Work Experience
### Senior Software Engineer, AI/ML @ ZoomInfo
Jan 2025 – Present | Waltham, Massachusetts, United States

### Software Engineer, AI/ML @ ZoomInfo
Jan 2024 – Jan 2025 | Waltham, Massachusetts, United States
Building Recommendation and Search Systems, MCP, Agents for ZoomInfo
● Built and owned the Contact Recommendation public API for ZoomInfo, serving 1M+ users in production and handling 700 QPS at peak load with P95 latency of 30ms. This system is a vector search engine that provides personalized contact recommendations (across 300M contacts) for sellers to engage with.
● Built streaming pipelines that process ~100M records daily for the ZoomInfo Homepage to recommend accounts to sellers.
● Large Language Model Serving: Built and maintained the ZoomInfo self-hosted LLM platform providing large-scale inference services (35k tokens/s) with TGI/vLLM, reducing costs by 79% compared to vendor APIs.
● Large Language Model Fine-tuning: Built and maintained the ZoomInfo self-hosted LLM platform providing LoRA fine-tuning services to serve internal teams building custom models.
● MLOps: Designed and operated production ML pipelines using Airflow, implemented monitoring and alerting with Datadog, and built CI/CD workflows with Jenkins and ArgoCD while managing infrastructure with Terraform.
● Built a Python MCP framework to enable internal teams to adopt existing services as MCPs.
● Built and managed several MCP servers used across the team.

### Senior Software Engineer, AI/ML @ Merck
Jan 2024 – Jan 2024 | Boston, Massachusetts, United States
Building the GenAI Hiring Platform for Merck

● Platform Development: Led a team to build the GenAI hiring platform from scratch, covering design, experimentation, implementation, and testing, in compliance with software development lifecycle (SDLC) standards.
● Efficiency Improvement: The platform saved 2 hours per job requisition creation.
● Scalability: Ensured the platform provided a smooth experience for 15,000 hiring managers generating job requisitions daily.
● Primary Responsibilities: Developed REST APIs, designed data pipelines (Databricks), and managed databases (RDS, Athena, DynamoDB).
● Secondary Responsibilities: Developed recommendation systems utilizing Large Language Models (LLMs) and a lot of prompt engineering with Langchain.

### Senior Data Scientist @ Deloitte
Jan 2021 – Jan 2024 | Boston, Massachusetts, United States
Deliver end-to-end AI solutions(ETL, model development, deployment)
● Time-series: Developed data pipelines with machining records of 12 million rows via Databricks, developed regression models, and deployed as Azure functions.
● Time-series: Developed Fraud detection model to identify anomalous activities in transaction data.
● NLP: Built entity recognition models to reduce 90% keying time for a financial company with MLflow pipelines to monitor model performance.
● NLP: Built an end-to-end document clustering(K-means, DB scan, t-SNE) pipeline to reduce 70% of human labor for a financial company with AWS Sagemaker.
● CV: Built an end-to-end video classification pipeline to reduce 80% of incorrectly broadcasted streaming content for a streaming company via Azure ML.

### Machine Learning Engineer @ Modzy
Jan 2019 – Jan 2021 | McLean, Virginia, United States
Develop features for an MLOps platform.
● Creating standard project templates that incorporates MLOps, including CI/CD, monitoring, retraining
● Build tools for governance of model lifecycle and performance, including memory profiling, drift detection, and explainability
● Building, containerizing, and deploying ML models with Azure and AWS platforms.
Develop data and modeling pipelines for an MLOps platform
● Develop web scraping tools to extract form data from websites.
● Develop complex SQL queries for extracting information on structured data.
● Develop scripts for cleaning and processing unstructured data. 
● Computer Vision and NLP model development (object detection, sentiment analysis and machine translation models)
● One paper accepted in CVPR 2021 on Explainable AI (https://arxiv.org/abs/2005.10284)

### Research Assistant @ University of Maryland
Jan 2017 – Jan 2019 | College Park, Maryland, United States
● Developed a GPU-based Parallel Computing code for large-scale complex multibody systems.
● Developed a Recurrent Neural Network model for the prediction of extreme events on deep water waves.

### Research Assistant @ National Center for Research on Earthquake Engineering
Jan 2014 – Jan 2016 | Taiwan, Taiwan
● Developed a predictive model for building damage assessment using finite element simulation data.
● Built Anomaly Detection models (autoencoders) to detect defect transistors.


## Education
### Master's degree in Computer Science
Georgia Institute of Technology

### Master's degree in Civil Engineering
National Cheng Kung University

### Bachelor's degree in Engineering
National Chiao Tung University


## Contact & Social
- LinkedIn: https://linkedin.com/in/andrewtseng1120
- GitHub: https://github.com/atseng17

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Source: https://flows.cv/andrewtseng
JSON Resume: https://flows.cv/andrewtseng/resume.json
Last updated: 2026-03-31