Yecheng Tan
@yechengtan
Senior full-stack software engineer building MLOps and data platforms for real AI workloads.
United StatesWhat I'm looking for
I’m a Senior Full-Stack Software Engineer with 8+ years of experience building production web services and large-scale data platforms that power real AI and machine learning workloads. I started with data collection systems for social media analytics, then moved into scalable backend pipelines, and later developed core networking infrastructure for EC2 VPC at AWS.
At Google, I lead teams to build Vertex AI, Google Cloud’s flagship ML platform, delivering MLOps infrastructure and developer experiences. I’ve spearheaded full-stack development for Universal App Campaigns, architected core Vertex AI components like Pipelines, Feature Store, and Experiment Tracker, and helped accelerate model deployment cycles significantly.
I also build enterprise-grade capabilities—such as explainable AI using modern visualization and ML tooling—and deliver developer-facing assets like Python SDKs, Jupyter Notebook integrations, and visual ML builders. I’m passionate about shipping reliable AI platforms that help teams deploy and manage models effectively in real enterprise environments.
Experience
Work history, roles, and key accomplishments
Led a 20+ person engineering team to build Vertex AI, delivering MLOps infrastructure and developer experiences. Developed UAC full-stack features for thousands of advertisers and architected core Vertex AI components (Pipelines, Feature Store, Experiment Tracker) enabling 80% faster model deployment cycles.
Built Python (FastAPI) backend services using Redis and PostgreSQL to automate data ingestion and ML training pipelines, increasing job throughput by 35%. Developed internal dashboards and improved model iteration time by 20%, and participated in migrating from Google's legacy Sibyl system to TensorFlow Extended.
Developed production full-stack web services using Python, Boto3, React, and TypeScript to build internal EC2 VPC management platforms for enterprise customers. Built AI-enhanced network analytics with Python and TensorFlow and implemented scalable web APIs and automation with CloudFormation for secure, high-throughput infrastructure management.
Developed production full-stack web services and large-scale data pipelines using Python, AWS Glue, and Apache Spark for audience measurement platforms. Built scalable ETL systems and internal APIs to automate ingestion, transformation, and real-time reporting, and implemented monitoring dashboards to improve data quality visibility.
Student Programmer
George Washington University
Nov 2015 - Sep 2017 (1 year 10 months)
Developed secure full-stack web services for social media data collection using Python, Scrapy, Flask, and MySQL while applying cybersecurity best practices. Built backend data pipelines with AWS EC2, S3, and RDS to securely process high-volume datasets as a foundation for future AI-driven analytics.
Education
Degrees, certifications, and relevant coursework
The George Washington University
Cybersecurity in Computer Science
2015 - 2017
Studied cybersecurity in computer science at The George Washington University from 2015 to 2017.
Hohai University
Bachelor’s Degree, Computer Science and Technology
2008 - 2012
Completed a Bachelor’s degree in Computer Science and Technology at Hohai University from 2008 to 2012.
Tech stack
Software and tools used professionally
Availability
Location
United StatesAuthorized to work in
Job categories
Skills
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