I am an AI engineer with an MSc in Physics and advanced postgraduate training in AI and Computer Science. I design and build scalable agentic AI systems and retrieval-augmented generation (RAG) solutions, with hands-on experience delivering production-grade AI applications powered by robust DevOps practices. I focus on practical, scalable, and generalizable AI solutions and enjoy translating frontier agentic AI techniques into reliable real-world systems. I thrive at bridging research and deployment, building end-to-end pipelines, and collaborating with cross-functional teams to create observable, maintainable AI systems. I am passionate about guardrails, evaluation, and human-in-the-loop workflows, and I actively explore how to make advanced AI capabilities trustworthy and reliable in real-world settings.

Yi Zhang

I am an AI engineer with an MSc in Physics and advanced postgraduate training in AI and Computer Science. I design and build scalable agentic AI systems and retrieval-augmented generation (RAG) solutions, with hands-on experience delivering production-grade AI applications powered by robust DevOps practices. I focus on practical, scalable, and generalizable AI solutions and enjoy translating frontier agentic AI techniques into reliable real-world systems. I thrive at bridging research and deployment, building end-to-end pipelines, and collaborating with cross-functional teams to create observable, maintainable AI systems. I am passionate about guardrails, evaluation, and human-in-the-loop workflows, and I actively explore how to make advanced AI capabilities trustworthy and reliable in real-world settings.

Available to hire

I am an AI engineer with an MSc in Physics and advanced postgraduate training in AI and Computer Science. I design and build scalable agentic AI systems and retrieval-augmented generation (RAG) solutions, with hands-on experience delivering production-grade AI applications powered by robust DevOps practices. I focus on practical, scalable, and generalizable AI solutions and enjoy translating frontier agentic AI techniques into reliable real-world systems.

I thrive at bridging research and deployment, building end-to-end pipelines, and collaborating with cross-functional teams to create observable, maintainable AI systems. I am passionate about guardrails, evaluation, and human-in-the-loop workflows, and I actively explore how to make advanced AI capabilities trustworthy and reliable in real-world settings.

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Experience Level

Expert
Expert
Expert
Expert
Expert
Expert
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Expert
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Language

Chinese
Fluent
English
Fluent
French
Beginner
German
Beginner

Work Experience

Full Stack AI Engineer at University of Zurich
September 1, 2024 - September 1, 2025
Engineered an agentic RAG chat system with LangGraph and FastAPI over indexed knowledge bases and web content, including routing, guardrails, and observability/evaluation via LangSmith; delivered a lightweight conversational frontend.
AI / Data Engineer for Knowledge Systems (Intern) at IFRC
March 1, 2023 - March 1, 2024
Developed a prototype GraphRAG solution using Neo4j and FastAPI, integrating entity extraction and text-to-Cypher translation; deployed with Docker on Azure infrastructure. Enabled semantic querying over internal organizational reports for the first time.
Data Intern for Enterprise Data Architecture at IFRC
September 1, 2022 - March 1, 2023
Analyzed enterprise-wide data assets, access protocols, and conceptual data models across the IFRC Secretariat to support organizational data standardization efforts. Contributed to metadata management and conceptual data modeling initiatives to improve data accessibility.
Junior Researcher in High Energy Physics at CERN
April 1, 2018 - September 1, 2019
Performed data-driven anomaly detection and statistical analysis on petabyte-scale detector data from the CMS Hadron Calorimeter to improve detector reliability during live operation and post-upgrade validation. Conducted large-scale statistical analysis on proton–proton collision data at 13 TeV, applying a data-driven estimation method (Rebalance-and-Smear) to model background contamination in high-noise environments using C++ and the ROOT framework.

Education

Graduate Studies in Artificial Intelligence at University of Zurich
February 1, 2024 - September 1, 2025
Special Student at ETH Zurich
February 1, 2025 - September 1, 2025
Graduate Studies in Computer Science at University of Geneva
September 1, 2019 - September 1, 2023
Exchange Student at ETH Zurich
September 1, 2021 - February 1, 2022
Master of Science in Physics at University of California Riverside
September 1, 2016 - February 1, 2018
Bachelor of Science in Physics at Nanjing University
September 1, 2011 - July 1, 2015

Qualifications

Add your qualifications or awards here.

Industry Experience

Non-Profit Organization, Education, Software & Internet, Professional Services, Government