Isaac Chung is a Staff Machine Learning Scientist with six years of hands-on experience building scalable, production-grade multimodal retrieval and LLM-based systems, currently focused on evaluation and benchmarking for customer support workflows at Zendesk. He has driven production deployments and custom ML solutions at Clarifai—improving vector search scalability, automating annotation pipelines, and translating research into client-facing products—and recently led product-oriented LLM research at Wrike. Proficient in Python, Go, PyTorch, Docker, Kubernetes and AWS, Isaac blends research depth from a MASc in Machine Learning with practical engineering to ship reliable systems. He contributes to open-source (notably helping maintain MTEB) and brings a customer-first mindset from extensive hands-on work with enterprise deals. Outside of engineering, he’s an endurance athlete who channels the same iterative, metrics-driven approach into swim/bike/run racing and travel.
6 years of coding experience
8 years of employment as a software developer
St. Michaels University School
Master of Applied Science - MASc Machine Learning, Master of Applied Science - MASc Machine Learning at University of Toronto
Contributions:78 pushes, 18 branches, 1 tag in 11 months
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Isaac Chung - Staff Machine Learning Scientist at Zendesk