Open to opportunities

Sihan Chen

@sihanchen

Message

Machine Learning Engineer building reliable, auditable production AI systems with LLM integration.

United States

Message

What I'm looking for

I seek roles building production ML/LLM systems with strong engineering practices, model transparency, monitoring, and cross-functional impact.

I am a machine learning engineer focused on building safe, reliable, and compliant AI systems that drive measurable operational improvements. I have engineered production-grade RAG systems integrating Google Gemini with Weaviate and implemented end-to-end ML pipelines with strong engineering practices.

My work spans scalable data processing, containerized microservices in Go, and model optimization for resource-constrained hardware, delivering up to 90% efficiency gains and 30% throughput improvements. I emphasize model transparency, monitoring, and high test coverage to ensure accountability and maintainability.

I collaborate cross-functionally to deliver tooling and dashboards for model performance and auditability, and I have a track record of publishing research and winning innovation awards for applied ML solutions.

Experience

Work history, roles, and key accomplishments

Current

Generative AI & Machine Learning Intern

Current

Seagate Technology

May 2025 - Present (7 months)

Engineered a production-grade RAG system integrating Google Gemini with Weaviate to automate compliance-sensitive Q&A workflows and built real-time performance dashboards, improving transparency and auditability for cross-functional partners.

RAG Gemini Weaviate Python Docker Angular Model Monitoring

Software Development Intern

Dell Technologies

Oct 2023 - Jun 2024 (8 months)

Redesigned and deployed a high-performance Go microservice handling 100M+ daily files, containerized with Docker/Kubernetes and instrumented with Prometheus/Grafana, reducing processing time by 30% and increasing resource utilization by 40%.

Go Microservices Docker Kubernetes Prometheus Grafana CI CD

Deep Learning & Embedded Software Intern

Chinese Academy of Sciences

Aug 2023 - Dec 2023 (4 months)

Developed and optimized a real-time CNN eye-tracking model in C++ with pruning and quantization to achieve 98% accuracy and millisecond latency on constrained hardware, resulting in a peer-reviewed publication.

C++CNN Model Quantization Embedded Systems Model Evaluation Deep Learning Performance Optimization

Education

Degrees, certifications, and relevant coursework

Columbia University

Master of Science, Electrical Engineering

Pursuing a Master of Science in Electrical Engineering with specialization in data-driven analysis and computation; coursework includes Machine Learning, Deep Learning, and Cloud Computing.