About
Machine Learning Ops Engineer @ TikTok
"Every problem is an opportunity."
Kyle is a Machine Learning Ops Engineer at TikTok, owning reliability for PB-scale real-time data pipelines supporting ads recommendation models across multiple global data centers. Prior to TikTok, he built ML pipelines and data infrastructure for battery management systems at Element Energy, applying machine learning to predict and optimize battery performance at GWh scale.
His path started in Materials Science, and the instinct for tracing failures to their root cause followed him through research at NTHU and Stanford and into production ML systems. He is building toward full-stack ML infrastructure expertise: real-time pipelines, feature stores, model training, and serving at scale.
- Education: MS in Materials Science, Stanford University
- Location: San Jose, CA
- Email: ptlin84@alumni.stanford.edu
Outside of work, I enjoy reading📚, playing guitar🎸, swimming🏊, running🏃, and riding motorcycles🏍.
Skills
Software Development
| Category | Skills |
|---|---|
| Languages | Python, SQL, C/C++, Java, JavaScript, Bash, Linux |
| ML & MLOps | MLflow, TensorFlow, Docker, Kubernetes, CI/CD, Git, Bitbucket |
| Cloud & Infra | Google Cloud Platform (BigQuery, Cloud Run, GKE, Cloud Storage), Flink, Spark, system monitoring, logging |
| Python Tools | Pandas, NumPy, scikit-learn, PyTorch, FastAPI, Flask, Typer CLI, Pytest, Plotly Dash, Logging |
| Data Engineering | Databases (MongoDB, SQLite, Redis), Pipeline (Spark, Luigi), Visualization (Plotly) |
Materials Engineering
| Category | Skills |
|---|---|
| Processes | Welding, Thermal-Mechanical Processing |
| Microstructural Analysis | OM, SEM, EDS, EBSD, EPMA |
| Mechanical Properties | Tensile Testing, Hardness, Microhardness |
| Characterization | DSC, DTA, DIL, XRD, XPS, Electrochemistry |
| Automated Manufacturing | Laser Displacement Sensors, Metrology, Data Communications |
Resume
Summary
Kyle Lin
Cross-disciplinary engineer with expertise in software development, data engineering, and materials engineering. Proficient in leveraging diverse skills to solve complex problems and drive innovation.
Education
Master of Science
Materials Science and Engineering
Materials Science and Engineering
Stanford University, Stanford, CA
2021 - 2023
- President of Stanford Taiwanese Student Association
- Researcher in Professor William Chueh's group
- Winner of Treehacks, Stanford's biggest yearly hackathon
Bachelor of Science
Materials Science and Engineering
Materials Science and Engineering
+
Bachelor of Arts
Economics
Economics
National Tsing Hua University, Hsinchu, Taiwan
2014 - 2018
- Completed double majors in 4 years
- Research assistant at High Performance Alloys Lab
- Member of Blue Sky Juvenile Caring Club
Research Experience
Graduate Researcher
Professor William Chueh Group, Stanford University
2021 - 2023
- Studied the effect of surface contaminant removal processes on LLZO solid electrolyte to enhance interfacial ion conductivity
- Built 15+ coin/pouch cells in glovebox and performed EIS and cycling tests to evaluate cell performance
Research Assistant
High-Entropy Materials Center, National Tsing Hua University
2017 - 2020
- Led 4 projects, coauthored 6 publications (250+ citations), 1 patent, and presented in 3 academic conferences
- Led the collaboration with Tohoku University, Japan on the research of friction-stir welded high-entropy alloys
- Designed and executed experiments and analyses, including alloy fabrication, processing, microstructural analysis, and mechanical analysis (microhardness and tensile tests)
Leadership & Community
Board Member
North American Taiwanese Engineering & Science Association (NATEA)
Jan 2025 – Present
Head of Speaker Recruitment
TEDxWoodside
Apr 2023 – Mar 2024
Professional Experience
Machine Learning Ops Engineer
TikTok, San Jose, CA
Oct 2025 – Present
- Owns reliability for PB-scale real-time data pipelines supporting ads recommendation models across multiple global data centers
- Leads automated resource inspection and capacity modeling across thousands of cloud-native services (compute engines, YARN, HDFS, MQs)
- Collaborates with R&D and algorithm teams on ads recommendation systems supporting a multi-billion dollar revenue stream
Machine Learning Engineer
Element Energy, Menlo Park, CA
Jan 2025 – Aug 2025
- Designed and built scalable ML pipelines with Python and MLflow, automating workflows for large-scale time-series data and reducing retraining cycles by 4x with continuous training
- Led data storage migration from millions of local files to Google BigQuery, optimizing data ingestion and cutting feature loading time by 80%
- Managed CI/CD pipelines for cloud production deployment
Data Analyst
Element Energy, Menlo Park, CA
Aug 2023 – Jan 2025
- Led and developed a Python web app for format-agnostic data visualization and algorithm execution, reducing average dataset visualization time from 5 minutes using code to 10 seconds without code
- Developed a data dashboard from scratch using Plotly Dash and MongoDB Atlas, handling gigabytes of time-series battery data and incorporating dynamic data resampling to enhance rendering speed by over 10x
Engineer Intern
QuantumScape Corporation, San Jose, CA
Summer 2022
- Engineered automated data processing in Python, resulting in an 80% reduction in manual work by querying SQL database for electrical data of 300+ battery cells and classifying them with pandas and scikit-learn
Technical Support Engineer
Keyence Corporation, Taipei, Taiwan
2020 - 2021
- Built 15+ in-line measurement systems using laser displacement sensors, covering hardware/software integration, sensor configuration, and data processing
- Facilitated 10+ purchase orders and led 2-month technical training for 3 new hire sales engineers on principles and applications of laser sensors
Product Development Engineer
Successful Advanced Materials, Hsinchu, Taiwan
2019 - 2020
- Developed and patented metal matrix composite powders for high-hardness coatings in injection molding machines
- Prototyped electromagnetic acoustic transducers for injection molding process monitoring
Process Engineer Intern
Taiwan Semiconductor Manufacturing Company (TSMC), Hsinchu, Taiwan
Summer 2019
- Conducted experiments and proposed a mechanism that leads to target poisoning and process instability in a PVD tool
- Improved in-line Ta/TaN thin-film deposition process productivity by 400% after tweaking the process recipe
Certifications
- Google Cloud AI Agents — Google (2025)
- Google Cloud Digital Leader — Google (2025)
- Machine Learning Specialization — Stanford University (2025)
- BigQuery for Data Analysts — Google Cloud (2024)
- Stanford Ignite — Stanford GSB (2023)
- Neural Networks and Deep Learning — DeepLearning.AI (2022)
- SQL Essential Training — LinkedIn Learning (2021)
- The Complete JavaScript Course — Udemy (2021)
Portfolio
Below is my project portfolio, which includes research publications in Materials Science areas, applications built for course/side projects, and awards.
- All
- Publications
- Apps
- Projects
- Awards
