cv

Basics

Name Yike Tan
Label Machine Learning Engineer
Email yiketn@gmail.com
Phone +1-412-583-0350
Url http://likegiver.github.io
Summary Graduate student at Carnegie Mellon University specializing in Artificial Intelligence Engineering and Information Security with a strong foundation in machine learning and software development.

Work

  • 2024.07 - 2024.08
    Machine Learning Engineer Intern
    Epoching AI
    Developed an end-to-end watermark removal service and optimized training pipelines for e-commerce imagery.
    • Fine-tuned pre-trained ViT model, achieving 30% accuracy improvement.
    • Deployed scalable FastAPI/Docker service with Prometheus monitoring.
  • 2023.09 - 2024.03
    Machine Learning Engineer Intern
    Ytell Network Technology Co., Ltd.
    Designed and implemented multimodal knowledge bots and automated pipelines for order processing.
    • Integrated VLMs with backend, improving response accuracy by 10%.
    • Developed automated ETL workflows processing 1,000+ daily requests with 95% accuracy.

Education

  • 2023.08 - 2025.12

    Pittsburgh, PA

    Master of Science
    Carnegie Mellon University
    Artificial Intelligence Engineering - Information Security
    • Large Language Models
    • AI Systems and Tool Chains
    • Computer Systems
  • 2020.08 - 2024.07

    Beijing, China

    Bachelor of Engineering
    University of International Business and Economics
    Data Science and Big Data Technology
    • Machine Learning
    • Data Structure and Algorithm
    • Natural Language Processing
    • Big Data Analysis

Projects

  • 2024.10 - 2024.10
    Memory Allocator
    Implemented a high-performance dynamic memory allocator in C with tools for debugging and optimization.
    • Achieved 75%+ memory utilization through boundary tag coalescing.
    • Integrated GDB debugging tools for block alignment validation.
  • 2024.09 - 2024.09
    Transformer Decoder
    Built a decoder-only Transformer with custom tokenizer and training pipeline.
    • Published trained model to HuggingFace Hub.
    • Integrated Weights & Biases for experiment tracking.
  • 2024.05 - 2024.06
    Self-LLM: Open-Source LLMs Deployment Guide
    Collaborated on deployment guides for GLM4, enabling developers to build advanced LLM applications.
    • 10k+ GitHub stars for deployment guides.
  • - Present
    Keep Knowledge in Perception: Zero-shot Image Aesthetic Assessment
    Developed a novel zero-shot framework for fine-grained aesthetic assessment, outperforming SOTA approaches.
    • ICASSP 2024 Oral Presentation.
    • Created a large-scale aesthetic dataset with 175k expert critiques.

Skills

Programming Languages
Python
C
C++
Java
JavaScript
SQL
R
Packages and Frameworks
React
Node.js
Django
Flask
NumPy
Pandas
PyTorch
TensorFlow
Jax
SparkML
Tools
Git
Docker
Kafka
Neo4j
Google Cloud Platform
Unix
LaTeX

Languages

English
Fluent
Chinese
Native