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Hi, I'm Yiling Peng, a passionate AI engineer and applied mathematician based in Boston. I specialize in developing secure, scalable software solutions with a focus on privacy, machine learning, and distributed systems. I enjoy creating innovative tools that enhance team productivity and data visualization. With a rich background in both computer science and mathematics, I have worked on projects ranging from decentralized knowledge graphs to advanced AI-powered SEO platforms. I'm always eager to learn new technologies and bring strong problem-solving skills to challenging roles.…Hi, I'm Yiling Peng, a passionate AI engineer and applied mathematician based in Boston. I specialize in developing secure, scalable software solutions with a focus on privacy, machine learning, and distributed systems. I enjoy creating innovative tools that enhance team productivity and data visualization. With a rich background in both computer science and mathematics, I have worked on projects ranging from decentralized knowledge graphs to advanced AI-powered SEO platforms. I'm always eager to learn new technologies and bring strong problem-solving skills to challenging roles.

Yiling Peng

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Hi, I'm Yiling Peng, a passionate AI engineer and applied mathematician based in Boston. I specialize in developing secure, scalable software solutions with a focus on privacy, machine learning, and distributed systems. I enjoy creating innovative tools that enhance team productivity and data visualization. With a rich background in both computer science and mathematics, I have worked on projects ranging from decentralized knowledge graphs to advanced AI-powered SEO platforms. I'm always eager to learn new technologies and bring strong problem-solving skills to challenging roles.…Hi, I'm Yiling Peng, a passionate AI engineer and applied mathematician based in Boston. I specialize in developing secure, scalable software solutions with a focus on privacy, machine learning, and distributed systems. I enjoy creating innovative tools that enhance team productivity and data visualization. With a rich background in both computer science and mathematics, I have worked on projects ranging from decentralized knowledge graphs to advanced AI-powered SEO platforms. I'm always eager to learn new technologies and bring strong problem-solving skills to challenging roles.

Available to hire

Hi, I’m Yiling Peng, a passionate AI engineer and applied mathematician based in Boston. I specialize in developing secure, scalable software solutions with a focus on privacy, machine learning, and distributed systems. I enjoy creating innovative tools that enhance team productivity and data visualization.

With a rich background in both computer science and mathematics, I have worked on projects ranging from decentralized knowledge graphs to advanced AI-powered SEO platforms. I’m always eager to learn new technologies and bring strong problem-solving skills to challenging roles.

Skills

Experience Level

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Language

English

Fluent

Chinese

Fluent

Work Experience

AI Engineer at 360 Advertisement

September 30, 2024 - July 25, 2025

Pioneered the initiative to self-host open-source large language models (LLMs), developing and deploying an in-house inference service to reduce dependency on costly third-party APIs. Engineered a 'just-in-time' GPU provisioning system that cut cloud infrastructure costs by over 80% by scheduling server activity aligned with business hours. Selected and deployed the GLM-4 model powered by the vLLM engine, leveraging bilingual capabilities for content generation. Developed a dynamic real-time retrieval-augmented generation (RAG) engine for competitive analysis by scraping and indexing top Google search results into query-specific Milvus vector collections. Created a Python tool to automate slide summarization and graph-based narrative visualization, enhancing content review efficiency.